Develop an internal memorandum, create a workflow analysis flow chart
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Scenario
Healthy Dynamics is a corporate wellness company that provides a broad range of wellness services for clients seeking to improve the health and wellbeing of their employees. One of the clients of Healthy Dynamics is not happy with their employee wellness program participation rates. Healthy Dynamics is not meeting the contract requirements of 60% engagement, resulting in lost revenue for the company and no return on investment (ROI) for the client. According to the contractual agreement, Healthy Dynamics must pay back the client $200,000,000 if the annual participation percentage is not met. Currently the client’s wellness program includes financial incentives for the employees if they complete the following wellness offerings (health assessment, biometric screening, and telephonic health coaching). The Healthy Dynamics CEO is now foreseeing a need to offer other healthcare services. The CEO has asked the Account Manager to create a business plan focused on increasing revenue and identifying risk that might negatively impact their continued relationship with the client. The Account Manager has tasked you, the Strategic Planning Manager, with preparing an internal memo to present to the CEO and to communicate to your internal team what you are envisioning as a desired future focus area to increase the bottom line for Healthy Dynamics and improve current and future client satisfaction rates.
Instructions
Develop an internal memorandum that includes:
- A detailed description defining the differences between business planning and strategic planning in healthcare.
- Identify a specific focus area in the healthcare industry that could increase revenue.
- Create key questions that you will need to address in the development of your strategic plan for your focus area.
Create a workflow analysis flow chart that includes:
- A list of healthcare leadership team members (e.g., CEO, Strategic Planning Manager, Account Manager, Marketing Manager, Project Manager, Financial Analyst, etc.,)
- A comprehensive analysis of each team member’s roles and responsibilities in the development of the strategic plan.
- Your assignment should include a title page, a reference page, and a minimum of three scholarly sources, two of which must be retrieved from the Rasmussen Library (See attached and choice 2 articles).
Rubric:
-Detailed description defining the differences between business planning and strategic planning in healthcare in a well-written internal memorandum.
-Clearly identified a specific focus area in the healthcare industry that could increase revenue in a well-written internal memorandum.
-Created detailed questions needed to address the development of a strategic plan in a well-written internal memorandum.
-Created a comprehensive list of healthcare leadership team members in the workflow analysis flow chart.
-Created a comprehensive analysis of each team member’s roles and responsibilities in the development of the strategic plan.
-Used and identified three or more credible sources in the memorandum.
https://doi.org/10.11613/BM.2019.020601 Biochem Med (Zagreb) 2019;29(2):020601
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Abstract
The Balanced Scorecard (BSC) is a tool for strategic management that is used in many companies and organizations worldwide, both in the public
and private sector. With this purpose it has also been used in healthcare organizations and institutions but there are not many studies on the imple-
mentation of BSC methodology in the day-to-day clinical laboratory. This review shows the strategy for the development of a BSC, which includes
theoretical perspective objectives, as well as some indicators and goals with which the monitoring and quantitative measurement of the achieve-
ments of a strategic plan in a clinical laboratory can be done. Moreover, the results of the indicators allow the prioritization of the initiatives to be
implemented each year.
The methodology for the development of the proposed BSC includes the following steps: definition of theoretical objectives of each of the perspec-
tives most used in the management of a clinical laboratory (customers, financial, internal processes and learning) taking into account the vision and
the organizational model of the laboratory; creation of a strategic map of perspective objectives; definition of the relevant indicators to follow up on
the objectives in a quantitative manner and establishment of the goals. Whether or not the laboratory is a reference laboratory, in which specific and
infrequent analysis and health population programs are performed, is another fact to take into account. In this review a BSC for a reference clinical
laboratory of the Spanish public sector is shown.
Keywords: balanced scorecard; clinical laboratory; management; strategic plan
Received: November 21, 2018 Accepted: February 27, 2019
A balanced scorecard for assessing a strategic plan in a clinical laboratory
Luisa Alvarez*1, Anna Soler1, Leonor Guiñón1, Aurea Mira2
1Quality Unit, Biomedical Diagnostic Center, Hospital Clínic, Barcelona, Spain
2Managing Director, Biomedical Diagnostic Center, Hospital Clínic, Barcelona, Spain
*Corresponding author: [email protected]
Short review
Introduction
Many organizations still present the results ob-
tained from the application of a strategic plan as a
list of achievements reached, sometimes accom-
panied by budget compliance but without using
any other type of analysis, which includes the
study of the impact of their results on the whole.
In this regard, a tool that can be used to track and
obtain quantitative data of the degree of achieve-
ment of the strategic plan’s objectives is the Bal-
anced Scorecard (BSC). The BSC is one of the most
popular performance management tools, which
categorizes the quantifiable objectives of an or-
ganization into four perspectives: financial, cus-
tomer, learning and internal processes (1). For each
objective, indicators and their goals are defined in
order to provide objective and quantitative infor-
mation about the achievements. It was introduced
by Kaplan and Norton in the 1990 and, although it
was originally used in industry, over time its use
has been extended to applications beyond that of
strategic management in this field (2,3). Shortly af-
ter its creation it was introduced for the measure-
ment of performance in healthcare organizations
and institutions in the USA, Canada and in Europe
(4-9). Although the BSC was applied as a tool for
strategic management in laboratory analysis as
early as 2003, few studies have been developed
since then (10). Among them there are those of
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Alvarez L. et al. Balanced scorecard for a strategic plan in a laboratory
Salinas, that use indicators of the laboratory pro-
cesses classified according to the four perspectives
cited and of Salas which orders the indicators ac-
cording to the perspective of the internal process
(11-13). It is worth highlighting this shortage of
studies in Spain, despite the fact that in 2008, the
Spanish Society of Laboratory Medicine (SEQCML)
defined Recommendations for the development
of a BSC in the clinical laboratory (14). Moreover,
there are no studies on the implementation of its
use to assess results of the application of a BSC for
monitoring long-term strategic plans.
Given that the BSC’s usefulness for evaluating a
strategic plan in hospital management has been
shown, we hypothesized that the BSC would pro-
vide a useful tool for the Managing Board of clini-
cal laboratories, both to describe the vision and
strategy of their laboratories and to manage im-
plementation and assess the achievements of a
four-year strategic plan. Thus, the aim of this re-
view is to show the strategy that should be fol-
lowed for the development of a BSC, which in-
cludes perspective objectives as well as the indica-
tors and goals with which the monitoring and
quantitative control of the achievements can be
carried out, in the short and long-term of a strate-
gic plan.
Strategy for the development of the BSC
The Managing Board has to take into account the
vision of the clinical laboratory and the manage-
ment model of the organizational structure when
designing a BSC.
The strategy to use includes the following steps:
1. Definition of theoretical perspective objec-
tives
These objectives arise from the answers to the
questions that are formulated considering the four
main perspectives that exist in the management
of a laboratory’s activity:
Customer perspective: How to increase the value
with which customers perceive our activity? What
are their needs and expectations? As some au-
thors have indicated, health institutions have to
devote the greatest efforts to this perspective,
since they are the ultimate recipients of the ac-
tions of improvement and the objectives defined
in all perspectives (8,15). Recipients of the activity
of the clinical laboratory are: citizens, patients and
clinical physicians of the hospital. Furthermore, in
the case of a reference clinical laboratory, physi-
cians or users of other laboratories who send sam-
ples for analysis should be included. As well, in
some clinical laboratories the Ministry of Health of
a country’s Government, that commissions the
laboratory population health programs, will be in-
corporated.
Among the objectives to take into account in this
perspective is the improvement of patient safety
in order to prevent patients from potential risks in
all phases of the analytical process, as Plebani has
shown (16). On the other hand, the clinical labora-
tories that have implemented the ISO 15189 stand-
ard, from the 2012 version have to demonstrate
that they are managing the risks that can affect
patient safety (17).
Financial perspective: How should providers of
financial resources perceive us? How should the
clinical laboratory achieve additional incomes to
those of the Ministry of Health of a country’s Gov-
ernment? Taking into account the comments in
the customer perspective, in healthcare organiza-
tions the objectives of this perspective should go
after those of the customer’s perspective, as indi-
cated by Kaplan and Norton.
Internal process perspective: In which processes
should laboratory staff focus their efforts on and
be excellent in satisfying their customers? Can an
increase in efficacy and efficiency in these pro-
cesses be shown?
Learning perspective: How to achieve a greater
involvement of staff that encourages greater effi-
ciency, higher quality and more innovation? It is an
established fact that in all organizations it is neces-
sary to manage the human factor to a high stand-
ard. Both the one that occupies strategic positions
and the one directly in charge of performing the
analysis, since this factor is what the organization
is based on and that which allows the organization
to achieve excellence. Professionals appreciate the
fact that the Managing Board of a clinical labora-
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Alvarez L. et al. Balanced scorecard for a strategic plan in a laboratory
tory is concerned with satisfying all those require-
ments that impact the work environment. There-
fore, a large number of the objectives of the learn-
ing perspective must be aimed at enhancing the
acquisition of greater skills for the personnel and
their professional development, and improving
their motivation and increasing satisfaction.
Finally, the objectives of the strategic plan are in-
cluded in the theoretical perspective’s objectives.
At this point, it has to be mentioned that real ob-
jectives of the strategic plan can have very differ-
ent scopes, particularly in clinical laboratories that
include the activity of all specialties. In such clini-
cal laboratories it can be observed, on the one
hand, that some of the objectives of the strategic
plan (i.e. “extension of existing technologies and
procedures for biomedical diagnosis”) may be in-
cluded in a single perspective (i.e. internal pro-
cess), but is carried out in all Departments. On the
other hand, other objectives of the strategic plan
(i.e. “reorganization of a department”) may be di-
rected to a single department, but initiatives to
achieve the objective may be included in all per-
spectives.
2. Design of the strategic map of the perspec-
tive’s objectives.
The map is developed analysing the cause-effect
relationships of the different objectives among
them. It represents, in graphic form, how the ob-
jectives are linked within their perspective, and
also their relationships between the four perspec-
tives, constituting what is called the alignment of
the objectives. This alignment helps the coher-
ence between them to be understood and shows
how the achievement of some objectives leads to
the achievement of others in the form of a cas-
cade. This strategic map begins with the human
factor, in terms of learning objectives, and then fi-
nally develops into the customer objectives.
3. Definition of indicators and goals of the
perspective’s objectives.
In order to monitor the perspective objectives, rel-
evant indicators and goals have to be designed
which will allow the results obtained to be dis-
played in a quantitative manner. In this regard, it
should be noted that the results of some indica-
tors may assess more than one objective, whether
or not it belongs to the same perspective. Moreo-
ver, in defining the indicators, the organizational
characteristics of the clinical laboratory (if it has
autonomy of management or a system of promo-
tion of professionals, among others) and its type (if
it is a reference clinical laboratory or not) have to
be taken into account. For better management in-
dicators should show, in a clear and understanda-
ble way, to the whole organization the contribu-
tion of the initiatives defined each year in the
achievement of the strategic plan.
The results of the indicators, defined in the cus-
tomer perspective, have to measure the intangible
aspects of the organization as those that demon-
strate the capacity of its professionals to advise
any client or user when they performs a consulta-
tion. As well as, they must show the ability of the
clinical laboratory’s Managing Board to respond to
complaints and incidents that may arise from lab-
oratory performance. In the case of a reference
clinical laboratory, indicators should communicate
the ability to make the laboratory into a leader
based on the excellence of its activity.
One important aspect to consider is the fact that
the results of the objective’s indicators of the BSC’s
financial perspective must be able to demonstrate,
to the entire organization, the leadership capacity
of the clinical laboratory’s Managing Board to
achieve budget compliance. Moreover, the ability
to generate sufficient self-financing will enable
them, on the one hand, to invest in those techno-
logical resources necessary for a better service to
citizens and, on the other hand, to increase the
training of all its professionals.
On the basis of the results obtained, indicators
from the internal process perspective have to
demonstrate the improvement of diagnostic and
analytical process efficiency. Results of these indi-
cators can also demonstrate the greater efficacy of
the analytical process that must be reflected in a
better compliance with the turnaround time and
in obtaining higher quality results. In a reference
clinical laboratory it should also show its capacity
to innovate laboratory medicine.
The results of the learning perspective’s indicators,
in conjunction with those from the perspective of
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Alvarez L. et al. Balanced scorecard for a strategic plan in a laboratory
internal processes, must allow the Managing
Board to know at all times the dedication it has,
both to overcome the resistance to change, and to
increase the professional competence of person-
nel in responding to new orientations that the
clinical laboratory will incorporate.
Once the BSC is designed, it is important to inform
the laboratory professionals of the objectives de-
fined. Moreover, as the first results of the indica-
tors are obtained, they must be shown to these
professionals, with values that clearly demonstrate
both their degree of participation and the achieve-
ments derived from their activity. This will syner-
gistically orient their capacity and efforts with
those of the Managing Board in order to obtain
the achievements of the clinical laboratory.
Application of the BSC to assess the four
year strategic plan in a reference clinical
laboratory
The organizational structure of the clinical labora-
tory located in Catalonia (Spain) includes the De-
partments of the different specialties of the labo-
ratory (Pathology, Clinical Biochemistry, Haematol-
ogy, Immunology and Microbiology). In addition
to these Departments, there are two Operational
Areas where automated activity is performed,
both in equipment for analysis based on molecu-
lar absorption spectrophotometry and in immu-
nological techniques (Core Laboratory), as well as
in equipment for carrying out studies based on
molecular biology (Core Molecular Biology). It also
has six transversal support units: client manage-
ment, quality, economic-administrative manage-
ment area, teaching, research and information sys-
tems coordination. The activity performed in the
clinical laboratory each year, more than 7.000,000
determinations or diagnostic studies from a cata-
logue of more than 2800 tests, is carried out by
430 professionals. It is also a reference center for
almost 300 laboratories in Spain which send their
specialised tests to perform. Moreover, in this clini-
cal laboratory different population programs are
carried out, such as newborn screening in the de-
tection of congenital conditions, prenatal screen-
ing tests, histocompatibility studies for solid or-
gan and stem cell transplantation (e.g. HLA typing
and viral serologies for all organ transplants) and
program for early detection of colorectal cancer in
Catalonia.
It has to be stated that the elaboration of a BSC
was facilitated because laboratories have imple-
mented quality management systems (both ISO
9001 and ISO 15189), which allow the Managing
Board of the clinical laboratory to acquire greater
Perspective Objectives
Customers
1. To increase customer satisfaction
2. To improve the image and prestige of the laboratory
3. To improve patient safety
4. To meet the health needs and expectations of the population
Financial
1. Compliance with the strategic budget
2. Generation of sufficient self-financing to meet the objectives of the laboratory mission
Internal Process
1. To innovate laboratory medicine
2. To improve the diagnostic and process efficiency
3. To improve the quality and efficacy of the process and product
Learning
1. To motivate the personnel
2. To increase the training of strategic personnel
3. To increase staff competence
4. To increase internal communication
Table 1. Perspective objectives
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Alvarez L. et al. Balanced scorecard for a strategic plan in a laboratory
Figure 1. Strategic map of perspective objectives
knowledge of the organization and its context.
Moreover, the Managing Board uses the annual re-
view report of the quality management system to
know about the improvement actions that are
needed to be implemented, as well as the annual
initiatives that are required (18).
The perspective objectives established for this
clinical laboratory, whose vision is to lead labora-
tory medicine generating and integrating new
knowledge and technological changes and be rec-
ognized as a clinical laboratory of excellence, are
shown in Table 1. In these theoretical objectives,
the annual initiatives defined to achieve the objec-
tives of the four-year strategic plan are classified.
The strategic plan of the laboratory was elaborat-
ed taking into account the guidelines of the Man-
aging Board of the Hospital. Moreover, there is an
alignment between both strategic plans whose
priority areas are: patients (the reason of being of
the Hospital); professionals (their engine) and re-
sources (which make continuity and innovation
possible in care).
In Figure 1 the relationship between the objec-
tives of the same perspective and the relationships
of the objectives between the four perspectives
are shown.
To meet the health
needs and
expectations of the
population
To improve
patient safety
To improve the image
and prestige of the
laboratory
To increase
customer
satisfaction
Generation of
sufficient self-financing
to meet the objectives
of the laboratory
mission
Compliance with
the strategic budget
To improve the
diagnostic and
process efficiency
To improve the
quality and efficacy
of the process and
product
To innovate
laboratory
medicine
To increase
internal
communication
To increase the
training of strategic
personnel
To increase
staff
competence
To motivate
the personnel
Financial perspective: economic
type objectives
Learning perspective: objectives for
the improvement of the human factor
Internal process perspective:
objectives for the improvement
of the efficacy, efficiency and
quality of processes and products
Customer perspective:
objectives representing the
value provided to customer
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Alvarez L. et al. Balanced scorecard for a strategic plan in a laboratory
Objectives Indicators Goals
Customer perspective
1. To increase customer satisfaction Degree of satisfaction internal and external customers (assessment of
treatment, reliability of results and overall evaluation)
NSI > 75
Number of complaints received from users ≤ 12 / year
2. To improve the image and
prestige of the laboratory
Degree of external client satisfaction for the advice received in case of
consultation
NSI > 75
Number of publications in scientific journals with impact factor ≥ previous year
3. To improve patient safety Number of incidents reported by Hospital staff due to laboratory performance ≤ previous year
Percentage of turnaround time compliance > 95%
4. To meet the health needs and
expectations of the population
Percentage of population programs that are carried out in the laboratory ≥ previous year
Percentage of tests included in catalogue addressed to the oncological
patient in relation to all the incorporated tests
≥ 10%
Financial perspective
1. Compliance with the strategic
budget
Percentage of deviation of the budget in consumables material,
personnel and total budget
0 – 1%
2. Generation of sufficient
self-financing to meet the objectives
of the laboratory mission
Annual variation in the number of patients and requests received in the
laboratory
0 – 1%
Annual variation in the billing to external clients 0 – 1%
Customer loyalty: the percentage variation of billing to clients who
requested analysis to the laboratory in the last two years
> 10%
Annual variation in the number of clients: percentage of new clients and
percentage of lost clients
0 – 5%
Internal process perspective
1. To innovate laboratory medicine Percentage of tests incorporated in the Catalog in response to new areas
of knowledge in relation to all incorporated tests
> 10%
2. To improve the diagnostic and
process efficiency
Percentage of tests incorporated to increase the diagnostic efficiency
thanks to technological development of the total test incorporated
> 10%
3. To improve the quality and
efficacy of the process and product
Percentage of determinations with defaults that do not meet the
turnaround time every month of the year
< 3%
Percentage of results of external quality assurance programs to be
reviewed according to the criteria of the organizer
< 3.5%
Percentage of annual initiatives achieved > 80%
Learning perspective
1. To motivate the personnel Degree of professional satisfaction (the assessment of actions dedicated
to improve their quality of life and human and professional promotion)
NSI > 75
Percentage of personnel who have improved their professional category > 10% triannual
Percentage of absenteeism < 2%
2. To increase the training of
strategic personnel
Number of training activities aimed at professionals who carry out
strategic activities
> 1 / year
3. To increase staff competence Percentage of specific training activities to increase professional competence > 10%
Percentage of technicians in a laboratory who can develop the same
activity with respect to the total number of technicians
> 20%
4. To increase internal communication Number of actions carried out to increase the internal communication > 3 / year
NSI – normalized satisfaction index. An NSI between 75 and 85 reflects a good valuation and more than 85 an excellent valuation.
Table 2. Indicators and goals of the customer perspective objectives
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Alvarez L. et al. Balanced scorecard for a strategic plan in a laboratory
The indicators and goals of the objectives of each
perspective are shown in Table 2.
Furthermore, that indicators have to be defined
taking into account the objectives and goals of the
Government of the country. In this way, since 2005
in Catalonia, patient safety is one of the main pri-
orities of the Ministry of Health of the Govern-
ment’s objectives. So, in the proposed BSC those
aspects in which the performance of the clinical
laboratory can give rise to incidents in other points
of the Hospital, or those caused by the delay in the
delivery of a result or a diagnostic study, are espe-
cially assessed.
As it can be seen in Table 2, some of the goal’s val-
ues are expressed as NSI (Normalized Satisfaction
Index) which is obtained from a calculation devel-
oped by International Business Machines Corpora-
tion (IBM) that is based on the penalty of the low-
est scores.
NSI = [(Ax0) + (Bx25) + (Cx50)
+ (Dx75) + (Ex100)] / N
Where: A = number of responses with a satisfac-
tion score of 1 (very bad), B = number of responses
with a satisfaction score of 2 (bad), C = number of
responses with a satisfaction score of 3 (regular), D
= number of responses with a satisfaction score of
4 (good), E = number of responses with a satisfac-
tion score of 5 (very good) and N = A + B + C + D + E.
The organizational structure of this reference clini-
cal laboratory, that it is based on management au-
tonomy, allows the Managing Board to promote,
on the one hand, efficiency in the management of
human and technological resources and, on the
other, the dedication of resources to special tests,
which are in development or that are not request-
ed frequently. That is why the objectives of the
strategic plan and its annual initiatives are aimed
at implementing the most cutting-edge services
using the latest technology. Sometimes this in-
cludes the use of the latest large equipment which
allows the automated generation of a large num-
ber of results, or the use of innovative technolo-
gies not generally implemented in the network of
healthcare clinical laboratories. It is important to
note that the results of the indicators of the finan-
cial perspective allow the efficiency of the clinical
laboratory in the budget management approved
by the Hospital Managing Board to be demon-
strated, both in the costs of consumables and
equipment, as well as personnel. Likewise, the
greater efficacy of all internal processes, especially
the strategic planning of the organization and per-
sonnel management processes, will be shown in
the achievement of a larger number of the initia-
tives defined annually.
Furthermore, in this reference clinical laboratory, it
is important to consider the results of the learning
perspective indicator, “Percentage of professionals
who have improved their professional category”,
because they will reflect the effort made by all the
laboratory’s personnel to maintain and improve
their competence and their participatory and col-
laborative spirit.
Concluding remarks
A comprehensive BSC that includes theoretical ob-
jectives for each perspective, as well as indicators
and the goals to be achieved, can be a valid, man-
ageable and simple tool in the clinical laboratory
to monitor and quantitatively measure the degree
of achievement of the objectives of a strategic
plan in those organizations that, due to their com-
plexity, have numerous objectives and each year
define a large number of very different initiatives.
This model of BSC has the particularity of having the-
oretical objectives of perspectives rather than the
original strategic objectives. It is adaptable to any or-
ganizational model and to the resources available.
Yet, like all BSCs, its use allows us to demonstrate the
laboratory’s strategy in carrying out its mission.
The BSC is a useful tool to demonstrate to the hos-
pital Managing Board the effectiveness of the clin-
ical laboratory’s managing board and profession-
als both in achieving the initiatives defined annu-
ally, as well as in the development of the strategic
plan. Moreover, it also shows how it can fulfil its
capacity to generate self-financing that allows it to
carry out initiatives of greater risk oriented to cus-
tomers. The annual results of the indicators allow
us to identify in which perspectives the efforts
have to be prioritized.
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Alvarez L. et al. Balanced scorecard for a strategic plan in a laboratory
Acknowledgments
We thank the Managing Board and all profession-
als of the clinical laboratory for their work and val-
uable contribution.
11. Salinas La Casta M, Flores Pardo E, Uris Selles J. Cuadro de
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Potential conflict of interest
None declared.
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Copyright of Biochemia Medica is the property of Biochemia Medica and its content may not
be copied or emailed to multiple sites or posted to a listserv without the copyright holder’s
express written permission. However, users may print, download, or email articles for
individual use.
Toward a New Strategic Public Health
Science for Policy, Practice, Impact,
and Health Equity
Rebecca Bunnell, PhD, MEd, Juliet Ryan, MPH, Charlotte Kent, PhD, and the CDC Office of Science and
CDC Excellence in Science Committee
See also Brownson, p. 1389.
The COVID-19 pandemic and its social and health impact have underscored the need for a new strategic
science agenda for public health. To optimize public health impact, high-quality strategic science addresses
scientific gaps that inform policy and guide practice.
At least 6 scientific gaps emerge from the US experience with COVID-19: health equity science, data science
and modernization, communication science, policy analysis and translation, scientific collaboration, and
climate science. Addressing these areas within a strategic public health science agenda will accelerate
achievement of public health goals.
Public health leadership and scientists have an unprecedented opportunity to use strategic science to
guide a new era of improved and equitable public health. (Am J Public Health. 2021;111(8):1489–1496.
https://doi.org/10.2105/AJPH.2021.306355)
COVID-19 has exposed majorunmet needs in our nation’s public
health system related to workforce,
diagnostics, preparedness, health dis-
parities, information systems, and
response capacity. While there have
been numerous calls for creating and
sustaining a robust public health infra-
structure and for prioritizing science,
antiscience sentiments have also been
widespread. Without a thoughtful,
strategic approach to scientific
research; rigorous evaluation of pro-
grams; and development of evidence-
based public health policy and com-
munication strategies, the United
States will be underprepared again
when the next pandemic occurs.
Ensuring impactful science as the bed-
rock for decision-making will set a
sound foundation for the future, and
lessons from COVID-19 can provide
direction for a strategic approach to
public health science.1
Public health has a mandate to
reduce morbidity and mortality and
advance health equity at the popula-
tion level. Metrics and frameworks
used to rank the impact and value of
public health science vary, often
reflecting stakeholder perspectives.
They frequently include a focus on
tangible health benefits, concern about
return on investment, interest in spe-
cific diseases, or prioritization of bib-
liometrics and scientometrics.2,3 Ret-
rospective metrics alone are
insufficient to guide strategic science;
effective action requires a prospective
approach. We believe strategic science
begins with a public health goal in mind,
systematically identifies and then
builds an evidence base to inform
practice and policy, and ultimately
results in improvement in health and
equity outcomes. To optimize public
health impact, high-quality strategic
science addresses scientific gaps that
inform policy and guide practice.
A prioritized strategic science agenda
can help guide use of limited public
health scientific resources to fill the evi-
dence gaps that will have the largest
impact on population health. Many
examples of the impact of strategic sci-
ence exist,4 ranging from counterbio-
terrorism efforts informed by the small-
pox research agenda,5 smoke-free
policies that protect millions based on
research documenting adverse effects
of second-hand smoke exposure,6
increased vaccine coverage following
implementation research, coordinated
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evidence-based actions to reduce anti-
microbial resistance informed by sur-
veillance,7 and millions of lives saved by
HIV antiretroviral therapy resulting from
applied research on effective delivery
strategies. A strategic pursuit of public
health science that provides direction,
has delineated measurable goals, and
provides opportunities for stakeholders
and affected communities to engage is
needed more than ever. Developing and
implementing an effective strategy is
crucial for a new public health era.
The COVID-19 pandemic has illumi-
nated at least 6 key themes that are
central to a science strategy for improv-
ing public health: health equity science;
data science and modernization; com-
munication science; policy analysis and
translation; scientific, including labora-
tory, collaboration; and climate science.
With a US domestic focus, for each of
these 6 themes, we first summarize
related COVID-19 lessons. Second, we
discuss their implications to help inform
a strategic public health science agenda
for a new era (Box 1).
HEALTH EQUITY SCIENCE
Structural racism, long-standing injusti-
ces, and neglect of factors that cause
health inequities in the United States
have worsened the consequences of the
COVID-19 pandemic and resulted in
substantial disparities in COVID-19
incidence, hospitalization, and mortality.
Social determinants of health (SDOH)
andvitalconditions such as employment
settings lacking employee protections
and insecure or crowded housing have
impeded the use of mitigation measures
like social distancing and mask wearing.
These factors contributed to 1.4- to 1.8-
times-higher COVID-19 incidence, 2- to
3-times-higher hospitalization, and 3- to
5-times-higher mortality rates among
Black and Hispanic/Latino persons
compared with White persons.8 In addi-
tion to elevated environmental expo-
sure risk, racial/ethnic minority popula-
tions have less access to health care and
higher prevalence of uncontrolled
chronic lung, heart, kidney, liver, and
metabolic conditions associated with
more severe COVID-19 outcomes.9 Race
and ethnicity data have been incom-
plete, particularly in the beginning of the
epidemic, and SDOH data were not
widely leveraged, leaving the effects of
structural racism, environmental injus-
tice, and other socioeconomic factors
largely unexplored. In addition, adverse
impacts of the pandemic on employ-
ment, education, and other determi-
nants of health could widen future dis-
parities as well because Black, Hispanic/
Latino, older, rural, and underinsured
populations were more likely to experi-
ence unemployment and education
setbacks.10,11
Future strategic scientific work can
advance health equity by both building
on existing recommendations and
identifying new effective program and
policy interventions. Rigorous evalua-
tions of clinical, community, environ-
mental, and policy interventions that link
social determinants with health out-
comes and assess impact on health
inequities are essential.12 To expand the
evidence base, evaluation of real-world
impact and the effect of interlocking
contextual systems will be important to
supplement experimental efficacy stud-
ies.12 Expanding use of validated meth-
ods to document SDOH and assess
social and environmental factors will be
fundamental to this work.13 This work
can also elucidate how failure to address
health disparities leads to less-effective
preparedness and how health dispar-
ities can be exacerbated during a crisis.
Research is needed to identify ways in
which better data from modernization
and innovation can be used to acceler-
ate health equity.14 Given how SDOH,
structural racism, and health disparities
contributed to the impact of this pan-
demic, implementation science should
inform preparedness approaches that
recognize health equity as a core pillar of
future pandemic preparedness efforts.
DATA SCIENCE AND
MODERNIZATION
Existing surveillance and data systems
have proven inadequate for COVID-19
response efforts. Public health data
systems have been historically under-
supported and were unable to acquire,
share, and transmit data efficiently. The
lack of systematic data collection and
automated linkages between
laboratory-derived data, clinical data,
andcase investigationdata hasimpeded
COVID-19 response speed. Outdated
policies and regulatory processes inhibit
data collection and sharing at local,
state, national, and international levels.
Interconnectivity across a vast array of
public–private sector systems in the
United States has been nascent, slowing
utilization of electronic health records in
response efforts. While contact tracing
can be an important public health tool to
interrupt disease transmission, its
application for COVID-19, particularly in
the initial months of the pandemic and
during spike periods, was largely inade-
quate. Data science could have greatly
improved contact-tracing efforts by
providing real-time information to those
exposed to reduce transmission. Finally,
the public health workforce has had
limited expertise and access to new
tools, policies, and approaches to data
visualization, methods, and analytics
including epidemiological modeling and
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BOX 1— COVID-19 Lessons and Implications for Strategic Public Health Science
Themes COVID-19 Lessons Public Health Science Opportunities
Health equity science � COVID-19 magnified and widened health disparities and
other inequities.
� Incomplete data on race, ethnicity, and SDOH limited
some analyses.
� Race/ethnicity interacted with causal SDOH factors and
historical inequities.
� Historic neglect of factors that cause health disparities
resulted in worse pandemic outcomes.
� Assess how addressing health disparities is part of
pandemic preparedness.
� Document SDOH, including how they intersect to magnify
risk.
� Build evidence on intervention effectiveness.
� Generate health equity evidence needed by policymakers.
� Research how data modernization and innovation can
accelerate health equity.
Data science and
modernization
� Public health data systems were unable to acquire, share,
and transmit data efficiently.
� Lack of systematic linkages among laboratory, clinical,
and case investigation data impeded response speed.
� Outdated policies and regulatory frameworks inhibited data
sharing at local, state, national, and international levels.
� Public health workforce expertise was insufficient for
data linkages and new analytic methods.
� Public- and private-sector partnerships were nascent,
slowing progress.
� Accelerate modernization to make public health science
current.
� Expand methods for use of multisectoral data sources,
including environmental and climate, community SDOH,
geospatial, genomic, and biomarker data.
� Evaluate new surveillance and outbreak signal approaches.
� Equip public health workforce with data science, genomics,
informatics, and analytic skills.
� Provide scientific leadership using public health data.
Communication
science
� A COVID-19 “infodemic” occurred together with more
than 90 million Facebook misinformation warnings
� Misinformation and disinformation undermined public
health messaging and response efforts.
� Public trust in scientific integrity was undermined
during COVID-19.
� Evaluate approaches to counter misinformation, such as
engaging online influencers.
� Expand communication science; assess impact of new
technologies and social media.
� Strengthen communication strategy as part of research
planning.
� Evaluate effective methods to amplify research
dissemination.
� Accelerate pace of science dissemination.
Policy analysis and
translation
� Need for universal access to free testing, treatment, and
vaccination for COVID-19 was evident.
� COVID-19 made intersection of health and other sectors
visible, raising plethora of policy issues (e.g., employment,
housing, transportation).
� Policy barriers hindered consistent mitigation approaches
across jurisdictions, (e.g., mask, restaurant, and business
opening policies).
� Clear, consistent messaging was needed across all levels of
policymakers.
� COVID-19’s postacute health effects (cardiovascular,
pulmonary, mental health, and neurologic) raised policy
issues in other health care domains.
� Telehealth expansion demonstrated both feasibility and
need for attention to equitable access.
� Expand use of policy analyses to assess public health
impacts.
� Utilize strongest methods possible for public health policy
research, including randomized and nonrandomized
designs.
� Leverage partnerships to accelerate dissemination and
implementation of evidence-based policy options.
� Assess core capacities, policies, and systems, and ethical
frameworks needed for future preparedness and resource
distribution during public health threats.
� Assess incidence, duration, severity, and societal impact of
long-term sequelae.
� Evaluate approaches to address policy and resource
barriers that ensure equitable access as telework expands.
Scientific collaboration � SARS-CoV-2 sequence was published online in 72 h, setting
precedent.
� Proliferation of COVID-19 preprints and rapid publications
accelerated pace of dissemination.
� Community engagement was critical to build trust and
mitigation adherence.
� Data from multiple sectors and disciplines helped to identify
risks and assess mitigation feasibility and effectiveness,
including political science, behavioral science, and data
science.
� Implement transdisciplinary and convergence research
studies.
� Pursue research innovation; develop novel methods, such
as improving specimen collection or using host genomics to
explain health outcomes and responses to treatments and
vaccines.
� Conduct community participatory research; use tools of
collaborative implementation science to enhance public
health outcomes.
� Facilitate rapid sharing of applied laboratory advances.
Climate science � Air pollution can aggravate underlying respiratory conditions
that lead to more severe COVID-19 outcomes.
� Extreme heat, fire, and severe weather complicated COVID-19
mitigation efforts.
� New COVID-19 guidance was needed for climate-related
emergency response.
� Lockdowns and reduced mobility and travel rapidly improved
air quality.
� Implement research focused on climate-vulnerable
populations.
� Leverage predictive analytics to forecast adverse climate
effects and intervention needs.
� Expand methods and routinely incorporate a climate lens
into public health research.
� Evaluate effectiveness and impact of interventions
designed to mitigate climate change to build evidence
base.
Note. SARS-CoV-2 5 severe acute respiratory syndrome coronavirus 2; SDOH 5 social determinants of health.
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disease forecasting as a routine part of
pandemic planning and response.15
As public health strives to keep pace
with rapidly advancing technologic
innovation, scientists are poised to ben-
efit from advanced data analytic skills,
including those for conducting natural
language processing and leveraging
machine learning and artificial intelli-
gence. Strategic public health science
coupled with innovative use of technol-
ogy could help transform contact tracing
methods for the future. Furthermore,
development of, building consensus
around, and utilization of new and nim-
ble regulatory, legislative, and ethical
frameworks for data collection, sharing,
quality, and privacy are needed to
reduce risks and maximize benefits
associated with rapid modernization.
Strategic public health science will require
expanded scientific methods and analytic
approaches for multisectoral data sour-
ces, including community SDOH, envi-
ronmental and climate, genomic and
bioinformatics, social media, and geo-
spatial data. As transdisciplinary data sci-
entistsincreasinglyusepublichealthdata,
public health scientific leadership is
needed to establish core method, ana-
lytic, ethical, and policy approaches.
COMMUNICATION
SCIENCE
The COVID-19 pandemic has called
attention to the cultural, structural, and
technological barriers that hamper dis-
semination and acceptance of accurate
messages informed by science. Misin-
formation and disinformation have
spread rapidly in social media. Face-
book, for example, reported placing
warning labels on more than 90 million
pieces of content deemed COVID-19
misinformation.16 COVID-19
misinformation undermined accurate
public health messaging; greater expo-
sure to misinformation was associated
with lower compliance with mask wear-
ing and social distancing guidelines.17
Disinformation, defined as deliberately
misleading or biased information, has
been used to intentionally fuel anti-
science views and sentiments, particu-
larly among targeted subpopulations.18
In addition, the sheer volume of
evidence-based information and the
speed and frequency with which infor-
mation evolved made consistent and
effective risk communication more
challenging and led the World Health
Organization (WHO) to declare an
“infodemic” around COVID-19 in May
2020.19 The inconsistency of clear
COVID-19 messaging across public-
sector authorities at local, national, and
global levels further undercut mitigation
efforts.
Strategic science can leverage com-
munity engagement, behavioral eco-
nomics, and communications science to
study the impact of new technologies
and strategies to counter misinforma-
tion and antiscience disinformation,
including engagement of online influ-
encers and trusted messengers to pro-
vide a steady flow of evidence-based
information.20 Research to identify
effective interventions can assist both
health organizations and social media
platforms as they work to counter mis-
and disinformation.21 Planning for
strategic dissemination, monitoring
audience knowledge and sentiment, and
countering misinformation are standard
practices for all public health scientists to
incorporate into daily practice. Coupled
with proactive, consistent messaging
that employs sound risk communication
principles, strategic science can help
rebuild trust in public health.22–24
POLICY ANALYSIS AND
TRANSLATION
COVID-19 has illuminated the potential
of policy as a public health tool and
impediment. For example, policy deci-
sions to reduce economic barriers for
vaccination and testing increased
uptake.25 COVID-19 has also raised
a plethora of multisectoral policy chal-
lenges that have an impact on trans-
mission risk, including workplace
safety, housing density, and transpor-
tation. Inconsistent mitigation policies
have hindered the response across
sectors and jurisdictions, including
mask mandates and restaurant, bar,
and other business operating policies.
Furthermore, the public has often been
confused by inconsistent communica-
tions about the importance of mitiga-
tion policies. COVID-19 has had
numerous collateral and lasting
impacts, both at the societal and indi-
vidual level. Public- and private-sector
entities will be confronted with poten-
tially millions of people with long-term
cardiovascular, pulmonary, mental
health, and neurological sequelae,26
raising policy needs across health care
domains.27 One success has been the
rapid expansion of telehealth28; poli-
cies to ensure equitable access going
forward will be needed.29
Assessment of the positive and nega-
tive impacts of policies and use of
mathematicalmodelingtopredictfuture
impacts are key tools for scientific
inquiry. A component of this work will be
the identification of the core capacities,
policies, and systems needed for pre-
paredness. This includes advance
assessment of the epidemiological and
ethical implications of policy approaches
to distribute resources during public
health emergencies. Characterizing
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overall COVID-19 collateral impacts will
be an important research area to inform
broader health care policy, starting with
assessment and monitoring of the inci-
dence, duration, severity, and societal
impact of long-term sequelae. Transla-
tional science, which includes both
implementation and dissemination
approaches and moves knowledge to
action by ensuring effective and wide-
spread use of evidence-based policies,
can leverage policy analysis and imple-
mentation research to accelerate
action.30 For example, policy analysis can
be used to identify effective mitigation
interventions to support those
experiencing long-term impacts, assess
SDOH, and achieve widespread impact
by applying findings through implemen-
tation and dissemination strategies. Suc-
cessofthispolicyresearchwilldependon
utilization of the strongest designs pos-
sible, including both randomized and
nonrandomized methods.12
SCIENTIFIC
COLLABORATION
Within 72 hours of the Chinese and WHO
announcement of a novel coronavirus,
Chinese researchers shared the full
sequence for SARS-CoV-2 online, spur-
ring a global effort toward vaccine and
therapeutics development.31 UNESCO
accelerated Open Science efforts with
122 nations32; the Open COVID Pledge
engaged patent holders and the private
sector33; and more than 150 scientific
institutions and journals reaffirmed their
commitment to share data and expand
open access during the public health
emergency.34 Peer-review timelines
have shortened dramatically for COVID-
19 scientific information, with rapid
review processes and preprint post-
ings.35 Dissemination of COVID-
19–related information exploded; more
than 16 000 scientific publications,
including greater than 6000 on preprint
servers, were posted in just 4 months.
Online and digital technologies sup-
ported low-cost and timely remote sci-
entific collaborations.36 Collaborative
scientific innovation on mRNA technol-
ogy greatly accelerated vaccine devel-
opment,37 and scientists in multiple
settings worked rapidly to build the evi-
dence base on the effectiveness of
masking for both source control and
user protection. The pandemic acceler-
ated scientific collaboration and pro-
moted new norms around transparency
and sharing.
Sustaining a culture of scientific col-
laboration positions public health sci-
ence to be enriched with innovation and
cross-sectoral expertise, including with
sectors outside of health.38 Concerted
effort by scientists will be needed to
implement transdisciplinary and con-
vergence research39; advance applied
laboratory science; conduct community
participatory research; pursue research
innovation and develop novel methods,
such as transdisciplinary environmental
health disparities research40; and host
transparent genomics studies to explain
health outcomes and vaccine
response.41 Creative public health prac-
tice and academic linkages as well as
transdisciplinary team-based research
approaches could help drive innovation
going forward, including laboratory
advancements.42,43 Improved labora-
tory capacities are foundational to
enhanced public health science, includ-
ing not only laboratory quality and safety
but also advancements in specimen
collection, pathogen inactivation, trans-
port, and rapid characterization; multi-
pathogen and point-of-care assays; and
biomarker-based diagnostics. Collabo-
rative sequence-based pathogen sur-
veillance reinforced by a global network
of reference laboratories can more
swiftly identify new and emerging
pathogens. Scientists can improve pro-
cesses for rapidly posting sequences
and early findings to accelerate evidence
generation for diagnostics, program
implementation, and policy develop-
ment. Modelingthecostsandbenefitsof
reducing chronic disease burden before
the next infectious disease outbreak
could inform a new paradigm for pre-
paredness. Scientists are poised to
continue greater collaboration, which
could be enhanced with local, national,
and global leadership.
CLIMATE SCIENCE
Health threats from climate change are
well-documented,44 and the interplay
between COVID-19 and climate and
environmental factors is multifaceted.40
Environmental determinants of health,
including deforestation and increasing
human presence in wildlife habitats,
have fueled both climate change and
emergence of zoonotic infections.45 Cli-
mate change, especially changes in
temperature and precipitation, can
result in changes in the distribution,
seasonality, and prevalence of infectious
diseases.46 Air pollution can aggravate
underlying respiratory conditions that
lead to more severe COVID-19 out-
comes.47 Extreme weather events,
including fires and storms, complicated
COVID-19 mitigation efforts48; in turn,
COVID-19 complicated responses to
these disasters.49 COVID-19 also com-
plicated the ability of local health
departments to run climate-relevant
congregate facilities, such as cooling
centers and disaster shelters.50,51 Lock-
downs and reduced mobility and travel
improved air quality, but these positive
impacts rapidly eroded as mobility
increased again.52 Our collective
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response to COVID-19 has been
described as “a rapid learning experi-
ment about how to cope with climate
change.”53 Indeed, COVID-19 and cli-
mate change mitigation share similar
policy challenges, including the impor-
tance of speedy and decisive action to
avoid global financial and public health
impact, the difficulties of gaining public
support for stringent mitigation policies
given politicization of the issues, and the
need to address health disparities and
counter misinformation.54
A strategic public health science
agenda creates the opportunity to
identify effective approaches for these
shared policy challenges. Other key pri-
orities include expanding research on
the relationship between climate and
health outcomes and emerging pan-
demic threats and improving surveil-
lance for climate-sensitive pathogens
and vectors that identify locations and
populations at greatest risk. In addition,
use of predictive analytics and forecast-
ing can help build an evidence base for
early warning systems and for interven-
tions that effectively counter adverse
climate effects, particularly for popula-
tions experiencing environmental injus-
tice,55 such as migrant and refugee
populations.56 Given that climate
impacts span across public health, from
environmental health to chronic and
infectious disease and mental health, an
interdisciplinary approach can support
scientists to expand methods and dem-
onstrate the value of new mandates to
routinely incorporate a climate lens in
public health research.57,58
A NEW ERA OF PUBLIC
HEALTH STRATEGIC
SCIENCE
The COVID-19 pandemic and its impacts
continue to grow, fueling the imperative
to create a new era of public health
guided by strategic science. The 6
themes emerging from COVID-19 expe-
rience discussed here—health equity
science, data science and moderniza-
tion, communication science, policy
analysis and translation, scientific col-
laboration, and climate science—can
help formulate a strategic public health
science agenda that accelerates
achievement offuture public health goals
(Box 1). To succeed, public health science
should be grounded in scientific integrity
and supported by a larger, sustained,
well-trained, and innovative workforce.
Workforce expansion,diversification, and
development will be needed at multiple
levels, including for epidemiologists, data
scientists, and leadership.59 This
enhanced public health workforce could
help break the cycle of panic and neglect
that has characterized public health
attention and resources for decades.60
Given the impact of COVID-19, it is pos-
sible that public health will remain
prominent, especially as vaccination cov-
erage expands, other efforts to reduce
community transmission continue, and
researchers learn more about COVID-
19’s long-term effects. Public health
leaders and scientists have an unprece-
dented opportunity to use strategic sci-
ence to guide and implement a new era
of improved and equitable public health.
ABOUT THE AUTHORS
Rebecca Bunnell and Juliet Ryan are with the Office
of Science, Centers for Disease Control and Pre-
vention (CDC), Atlanta, GA. Charlotte Kent is with
Morbidity and Mortality Weekly Report, Center for
Surveillance, Epidemiology, and Laboratory Serv-
ices, CDC.
Note. The findings and conclusions in this
report are those of the authors and do not nec-
essarily represent the views of the CDC or the
Agency for Toxic Substances and Disease Registry.
CORRESPONDENCE
Correspondence should be sent to Rebecca E.
Bunnell, PhD, MEd, Centers for Disease Control
and Prevention, Atlanta, GA 30333 (e-mail: [email protected]
cdc.gov). Reprints can be ordered at http://www.
ajph.org by clicking the “Reprints” link.
PUBLICATION INFORMATION
Full Citation: Bunnell R, Ryan J, Kent C, CDC Office of
Science, and CDC Excellence in Science Committee.
Toward a new strategic public health science for
policy, practice, impact, and health equity. Am J
Public Health. 2021;111(8):1489–1496.
Acceptance Date: April 15, 2021.
DOI: https://doi.org/10.2105/AJPH.2021.306355
CONTRIBUTORS
R. Bunnell wrote the article with the support of
C. Kent and J. Ryan. Senior scientists from CDC’s
Office of Science and Excellence in Science Com-
mittee, listed in the Acknowledgments, all reviewed
and contributed to multiple drafts and the final
version of this publication.
ACKNOWLEDGMENTS
The CDC Office of Science and CDC Excellence in
Science Committee provided critical ideas and
feedback to help shape the article and revisions.
Members of the CDC Excellence in Science Com-
mittee were Elise Beltrami, MD, MPH (National
Center for Emerging and Zoonotic Infectious Dis-
eases), Amy M. Branum, MSPH, PhD (National
Center for Health Statistics), Dogan Eroglu, PhD
(Office of the Associate Director for Communica-
tion), Susan Goldstein, MD (National Center for
Immunization and Respiratory Diseases), Arlene
Greenspan, DrPH, MS, MPH (National Center for
Injury Prevention and Control), Kimberly Hummel,
PhD (National Center for Emerging and Zoonotic
Infectious Diseases), Vikas Kapil, DO, MPH (Center
for Global Health), Rachel Kaufmann, PhD, MPH
(National Center for Chronic Disease Prevention
and Health Promotion), Wendi Kuhnert-Tallman,
PhD (Office of the Deputy Director for Infectious
Diseases), Aun Lor, PhD, MA, MPH (Center for
Global Health), Sandra Naoom, PhD, MSPH (Office
of the Deputy Director for Public Health Service
and Implementation Science), Sherry M. Owen,
PhD (National Center for HIV/AIDS, Viral Hepatitis,
STD, and TB Prevention), Ana Penman-Aguilar, PhD,
MPH (Office of Minority Health and Health Equity),
Celeste M. Philip, MD, MPH (Office of the Deputy
Director for Non-infectious Diseases), John D. Pia-
centino, MD, MPH (National Institute for Occupa-
tional Safety and Health), Richard Puddy, PhD, MPH
(Office of Associate Director for Policy and Strat-
egy), Tom Savel, MD (Office of Chief Information
Officer), James W. Stephens, PhD (Center for Sur-
veillance, Epidemiology, and Laboratory Services),
Benedict Truman, MD, MPH (National Center for
HIV/AIDS, Viral Hepatitis, STD, and TB Prevention),
Robin Wagner, PhD, MS (Office of the Deputy
Director for Public Health Science and Surveil-
lance), David Williamson, PhD, MS (National Center
for Environmental Health and Agency for Toxic
Substances and Disease Registry), and Andrea
Young, PhD, MS (Center for State, Tribal, Local, and
Territorial Support). Members of the CDC Office of
Science were Micah Bass, MPH, Joanne Cono, MD,
RESEARCH & ANALYSIS
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ScM, Juliana Cyril, PhD, Maryam Daneshvar, PhD,
MS, Julie Fishman, MPH, Locola Hayes, MBA, Rosa
Herrera, BS, Muin Khoury, MD, PhD, Jennifer Lay-
den, MD, PhD, Mary Reynolds, MS, PhD, Shambavi
Subbarao, MSc, PhD, and Bao-Ping Zhu, MD, PhD.
CONFLICTS OF INTEREST
The authors have no potential or actual conflicts of
interest with the content presented in this article.
HUMAN PARTICIPANT
PROTECTION
This activity did not involve human participant
research, was reviewed by CDC, and was con-
ducted consistent with applicable federal law and
CDC policy (see, e.g., 45 CFR 46; 21 CFR 56; 42 USC
§241(d); 5 USC §552a; 44 USC §3501 et seq.).
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Copyright of American Journal of Public Health is the property of American Public Health
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- TF1
Toward a New Strategic Public Health
Science for Policy, Practice, Impact,
and Health Equity
Rebecca Bunnell, PhD, MEd, Juliet Ryan, MPH, Charlotte Kent, PhD, and the CDC Office of Science and
CDC Excellence in Science Committee
See also Brownson, p. 1389.
The COVID-19 pandemic and its social and health impact have underscored the need for a new strategic
science agenda for public health. To optimize public health impact, high-quality strategic science addresses
scientific gaps that inform policy and guide practice.
At least 6 scientific gaps emerge from the US experience with COVID-19: health equity science, data science
and modernization, communication science, policy analysis and translation, scientific collaboration, and
climate science. Addressing these areas within a strategic public health science agenda will accelerate
achievement of public health goals.
Public health leadership and scientists have an unprecedented opportunity to use strategic science to
guide a new era of improved and equitable public health. (Am J Public Health. 2021;111(8):1489–1496.
https://doi.org/10.2105/AJPH.2021.306355)
COVID-19 has exposed majorunmet needs in our nation’s public
health system related to workforce,
diagnostics, preparedness, health dis-
parities, information systems, and
response capacity. While there have
been numerous calls for creating and
sustaining a robust public health infra-
structure and for prioritizing science,
antiscience sentiments have also been
widespread. Without a thoughtful,
strategic approach to scientific
research; rigorous evaluation of pro-
grams; and development of evidence-
based public health policy and com-
munication strategies, the United
States will be underprepared again
when the next pandemic occurs.
Ensuring impactful science as the bed-
rock for decision-making will set a
sound foundation for the future, and
lessons from COVID-19 can provide
direction for a strategic approach to
public health science.1
Public health has a mandate to
reduce morbidity and mortality and
advance health equity at the popula-
tion level. Metrics and frameworks
used to rank the impact and value of
public health science vary, often
reflecting stakeholder perspectives.
They frequently include a focus on
tangible health benefits, concern about
return on investment, interest in spe-
cific diseases, or prioritization of bib-
liometrics and scientometrics.2,3 Ret-
rospective metrics alone are
insufficient to guide strategic science;
effective action requires a prospective
approach. We believe strategic science
begins with a public health goal in mind,
systematically identifies and then
builds an evidence base to inform
practice and policy, and ultimately
results in improvement in health and
equity outcomes. To optimize public
health impact, high-quality strategic
science addresses scientific gaps that
inform policy and guide practice.
A prioritized strategic science agenda
can help guide use of limited public
health scientific resources to fill the evi-
dence gaps that will have the largest
impact on population health. Many
examples of the impact of strategic sci-
ence exist,4 ranging from counterbio-
terrorism efforts informed by the small-
pox research agenda,5 smoke-free
policies that protect millions based on
research documenting adverse effects
of second-hand smoke exposure,6
increased vaccine coverage following
implementation research, coordinated
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evidence-based actions to reduce anti-
microbial resistance informed by sur-
veillance,7 and millions of lives saved by
HIV antiretroviral therapy resulting from
applied research on effective delivery
strategies. A strategic pursuit of public
health science that provides direction,
has delineated measurable goals, and
provides opportunities for stakeholders
and affected communities to engage is
needed more than ever. Developing and
implementing an effective strategy is
crucial for a new public health era.
The COVID-19 pandemic has illumi-
nated at least 6 key themes that are
central to a science strategy for improv-
ing public health: health equity science;
data science and modernization; com-
munication science; policy analysis and
translation; scientific, including labora-
tory, collaboration; and climate science.
With a US domestic focus, for each of
these 6 themes, we first summarize
related COVID-19 lessons. Second, we
discuss their implications to help inform
a strategic public health science agenda
for a new era (Box 1).
HEALTH EQUITY SCIENCE
Structural racism, long-standing injusti-
ces, and neglect of factors that cause
health inequities in the United States
have worsened the consequences of the
COVID-19 pandemic and resulted in
substantial disparities in COVID-19
incidence, hospitalization, and mortality.
Social determinants of health (SDOH)
andvitalconditions such as employment
settings lacking employee protections
and insecure or crowded housing have
impeded the use of mitigation measures
like social distancing and mask wearing.
These factors contributed to 1.4- to 1.8-
times-higher COVID-19 incidence, 2- to
3-times-higher hospitalization, and 3- to
5-times-higher mortality rates among
Black and Hispanic/Latino persons
compared with White persons.8 In addi-
tion to elevated environmental expo-
sure risk, racial/ethnic minority popula-
tions have less access to health care and
higher prevalence of uncontrolled
chronic lung, heart, kidney, liver, and
metabolic conditions associated with
more severe COVID-19 outcomes.9 Race
and ethnicity data have been incom-
plete, particularly in the beginning of the
epidemic, and SDOH data were not
widely leveraged, leaving the effects of
structural racism, environmental injus-
tice, and other socioeconomic factors
largely unexplored. In addition, adverse
impacts of the pandemic on employ-
ment, education, and other determi-
nants of health could widen future dis-
parities as well because Black, Hispanic/
Latino, older, rural, and underinsured
populations were more likely to experi-
ence unemployment and education
setbacks.10,11
Future strategic scientific work can
advance health equity by both building
on existing recommendations and
identifying new effective program and
policy interventions. Rigorous evalua-
tions of clinical, community, environ-
mental, and policy interventions that link
social determinants with health out-
comes and assess impact on health
inequities are essential.12 To expand the
evidence base, evaluation of real-world
impact and the effect of interlocking
contextual systems will be important to
supplement experimental efficacy stud-
ies.12 Expanding use of validated meth-
ods to document SDOH and assess
social and environmental factors will be
fundamental to this work.13 This work
can also elucidate how failure to address
health disparities leads to less-effective
preparedness and how health dispar-
ities can be exacerbated during a crisis.
Research is needed to identify ways in
which better data from modernization
and innovation can be used to acceler-
ate health equity.14 Given how SDOH,
structural racism, and health disparities
contributed to the impact of this pan-
demic, implementation science should
inform preparedness approaches that
recognize health equity as a core pillar of
future pandemic preparedness efforts.
DATA SCIENCE AND
MODERNIZATION
Existing surveillance and data systems
have proven inadequate for COVID-19
response efforts. Public health data
systems have been historically under-
supported and were unable to acquire,
share, and transmit data efficiently. The
lack of systematic data collection and
automated linkages between
laboratory-derived data, clinical data,
andcase investigationdata hasimpeded
COVID-19 response speed. Outdated
policies and regulatory processes inhibit
data collection and sharing at local,
state, national, and international levels.
Interconnectivity across a vast array of
public–private sector systems in the
United States has been nascent, slowing
utilization of electronic health records in
response efforts. While contact tracing
can be an important public health tool to
interrupt disease transmission, its
application for COVID-19, particularly in
the initial months of the pandemic and
during spike periods, was largely inade-
quate. Data science could have greatly
improved contact-tracing efforts by
providing real-time information to those
exposed to reduce transmission. Finally,
the public health workforce has had
limited expertise and access to new
tools, policies, and approaches to data
visualization, methods, and analytics
including epidemiological modeling and
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BOX 1— COVID-19 Lessons and Implications for Strategic Public Health Science
Themes COVID-19 Lessons Public Health Science Opportunities
Health equity science � COVID-19 magnified and widened health disparities and
other inequities.
� Incomplete data on race, ethnicity, and SDOH limited
some analyses.
� Race/ethnicity interacted with causal SDOH factors and
historical inequities.
� Historic neglect of factors that cause health disparities
resulted in worse pandemic outcomes.
� Assess how addressing health disparities is part of
pandemic preparedness.
� Document SDOH, including how they intersect to magnify
risk.
� Build evidence on intervention effectiveness.
� Generate health equity evidence needed by policymakers.
� Research how data modernization and innovation can
accelerate health equity.
Data science and
modernization
� Public health data systems were unable to acquire, share,
and transmit data efficiently.
� Lack of systematic linkages among laboratory, clinical,
and case investigation data impeded response speed.
� Outdated policies and regulatory frameworks inhibited data
sharing at local, state, national, and international levels.
� Public health workforce expertise was insufficient for
data linkages and new analytic methods.
� Public- and private-sector partnerships were nascent,
slowing progress.
� Accelerate modernization to make public health science
current.
� Expand methods for use of multisectoral data sources,
including environmental and climate, community SDOH,
geospatial, genomic, and biomarker data.
� Evaluate new surveillance and outbreak signal approaches.
� Equip public health workforce with data science, genomics,
informatics, and analytic skills.
� Provide scientific leadership using public health data.
Communication
science
� A COVID-19 “infodemic” occurred together with more
than 90 million Facebook misinformation warnings
� Misinformation and disinformation undermined public
health messaging and response efforts.
� Public trust in scientific integrity was undermined
during COVID-19.
� Evaluate approaches to counter misinformation, such as
engaging online influencers.
� Expand communication science; assess impact of new
technologies and social media.
� Strengthen communication strategy as part of research
planning.
� Evaluate effective methods to amplify research
dissemination.
� Accelerate pace of science dissemination.
Policy analysis and
translation
� Need for universal access to free testing, treatment, and
vaccination for COVID-19 was evident.
� COVID-19 made intersection of health and other sectors
visible, raising plethora of policy issues (e.g., employment,
housing, transportation).
� Policy barriers hindered consistent mitigation approaches
across jurisdictions, (e.g., mask, restaurant, and business
opening policies).
� Clear, consistent messaging was needed across all levels of
policymakers.
� COVID-19’s postacute health effects (cardiovascular,
pulmonary, mental health, and neurologic) raised policy
issues in other health care domains.
� Telehealth expansion demonstrated both feasibility and
need for attention to equitable access.
� Expand use of policy analyses to assess public health
impacts.
� Utilize strongest methods possible for public health policy
research, including randomized and nonrandomized
designs.
� Leverage partnerships to accelerate dissemination and
implementation of evidence-based policy options.
� Assess core capacities, policies, and systems, and ethical
frameworks needed for future preparedness and resource
distribution during public health threats.
� Assess incidence, duration, severity, and societal impact of
long-term sequelae.
� Evaluate approaches to address policy and resource
barriers that ensure equitable access as telework expands.
Scientific collaboration � SARS-CoV-2 sequence was published online in 72 h, setting
precedent.
� Proliferation of COVID-19 preprints and rapid publications
accelerated pace of dissemination.
� Community engagement was critical to build trust and
mitigation adherence.
� Data from multiple sectors and disciplines helped to identify
risks and assess mitigation feasibility and effectiveness,
including political science, behavioral science, and data
science.
� Implement transdisciplinary and convergence research
studies.
� Pursue research innovation; develop novel methods, such
as improving specimen collection or using host genomics to
explain health outcomes and responses to treatments and
vaccines.
� Conduct community participatory research; use tools of
collaborative implementation science to enhance public
health outcomes.
� Facilitate rapid sharing of applied laboratory advances.
Climate science � Air pollution can aggravate underlying respiratory conditions
that lead to more severe COVID-19 outcomes.
� Extreme heat, fire, and severe weather complicated COVID-19
mitigation efforts.
� New COVID-19 guidance was needed for climate-related
emergency response.
� Lockdowns and reduced mobility and travel rapidly improved
air quality.
� Implement research focused on climate-vulnerable
populations.
� Leverage predictive analytics to forecast adverse climate
effects and intervention needs.
� Expand methods and routinely incorporate a climate lens
into public health research.
� Evaluate effectiveness and impact of interventions
designed to mitigate climate change to build evidence
base.
Note. SARS-CoV-2 5 severe acute respiratory syndrome coronavirus 2; SDOH 5 social determinants of health.
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disease forecasting as a routine part of
pandemic planning and response.15
As public health strives to keep pace
with rapidly advancing technologic
innovation, scientists are poised to ben-
efit from advanced data analytic skills,
including those for conducting natural
language processing and leveraging
machine learning and artificial intelli-
gence. Strategic public health science
coupled with innovative use of technol-
ogy could help transform contact tracing
methods for the future. Furthermore,
development of, building consensus
around, and utilization of new and nim-
ble regulatory, legislative, and ethical
frameworks for data collection, sharing,
quality, and privacy are needed to
reduce risks and maximize benefits
associated with rapid modernization.
Strategic public health science will require
expanded scientific methods and analytic
approaches for multisectoral data sour-
ces, including community SDOH, envi-
ronmental and climate, genomic and
bioinformatics, social media, and geo-
spatial data. As transdisciplinary data sci-
entistsincreasinglyusepublichealthdata,
public health scientific leadership is
needed to establish core method, ana-
lytic, ethical, and policy approaches.
COMMUNICATION
SCIENCE
The COVID-19 pandemic has called
attention to the cultural, structural, and
technological barriers that hamper dis-
semination and acceptance of accurate
messages informed by science. Misin-
formation and disinformation have
spread rapidly in social media. Face-
book, for example, reported placing
warning labels on more than 90 million
pieces of content deemed COVID-19
misinformation.16 COVID-19
misinformation undermined accurate
public health messaging; greater expo-
sure to misinformation was associated
with lower compliance with mask wear-
ing and social distancing guidelines.17
Disinformation, defined as deliberately
misleading or biased information, has
been used to intentionally fuel anti-
science views and sentiments, particu-
larly among targeted subpopulations.18
In addition, the sheer volume of
evidence-based information and the
speed and frequency with which infor-
mation evolved made consistent and
effective risk communication more
challenging and led the World Health
Organization (WHO) to declare an
“infodemic” around COVID-19 in May
2020.19 The inconsistency of clear
COVID-19 messaging across public-
sector authorities at local, national, and
global levels further undercut mitigation
efforts.
Strategic science can leverage com-
munity engagement, behavioral eco-
nomics, and communications science to
study the impact of new technologies
and strategies to counter misinforma-
tion and antiscience disinformation,
including engagement of online influ-
encers and trusted messengers to pro-
vide a steady flow of evidence-based
information.20 Research to identify
effective interventions can assist both
health organizations and social media
platforms as they work to counter mis-
and disinformation.21 Planning for
strategic dissemination, monitoring
audience knowledge and sentiment, and
countering misinformation are standard
practices for all public health scientists to
incorporate into daily practice. Coupled
with proactive, consistent messaging
that employs sound risk communication
principles, strategic science can help
rebuild trust in public health.22–24
POLICY ANALYSIS AND
TRANSLATION
COVID-19 has illuminated the potential
of policy as a public health tool and
impediment. For example, policy deci-
sions to reduce economic barriers for
vaccination and testing increased
uptake.25 COVID-19 has also raised
a plethora of multisectoral policy chal-
lenges that have an impact on trans-
mission risk, including workplace
safety, housing density, and transpor-
tation. Inconsistent mitigation policies
have hindered the response across
sectors and jurisdictions, including
mask mandates and restaurant, bar,
and other business operating policies.
Furthermore, the public has often been
confused by inconsistent communica-
tions about the importance of mitiga-
tion policies. COVID-19 has had
numerous collateral and lasting
impacts, both at the societal and indi-
vidual level. Public- and private-sector
entities will be confronted with poten-
tially millions of people with long-term
cardiovascular, pulmonary, mental
health, and neurological sequelae,26
raising policy needs across health care
domains.27 One success has been the
rapid expansion of telehealth28; poli-
cies to ensure equitable access going
forward will be needed.29
Assessment of the positive and nega-
tive impacts of policies and use of
mathematicalmodelingtopredictfuture
impacts are key tools for scientific
inquiry. A component of this work will be
the identification of the core capacities,
policies, and systems needed for pre-
paredness. This includes advance
assessment of the epidemiological and
ethical implications of policy approaches
to distribute resources during public
health emergencies. Characterizing
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overall COVID-19 collateral impacts will
be an important research area to inform
broader health care policy, starting with
assessment and monitoring of the inci-
dence, duration, severity, and societal
impact of long-term sequelae. Transla-
tional science, which includes both
implementation and dissemination
approaches and moves knowledge to
action by ensuring effective and wide-
spread use of evidence-based policies,
can leverage policy analysis and imple-
mentation research to accelerate
action.30 For example, policy analysis can
be used to identify effective mitigation
interventions to support those
experiencing long-term impacts, assess
SDOH, and achieve widespread impact
by applying findings through implemen-
tation and dissemination strategies. Suc-
cessofthispolicyresearchwilldependon
utilization of the strongest designs pos-
sible, including both randomized and
nonrandomized methods.12
SCIENTIFIC
COLLABORATION
Within 72 hours of the Chinese and WHO
announcement of a novel coronavirus,
Chinese researchers shared the full
sequence for SARS-CoV-2 online, spur-
ring a global effort toward vaccine and
therapeutics development.31 UNESCO
accelerated Open Science efforts with
122 nations32; the Open COVID Pledge
engaged patent holders and the private
sector33; and more than 150 scientific
institutions and journals reaffirmed their
commitment to share data and expand
open access during the public health
emergency.34 Peer-review timelines
have shortened dramatically for COVID-
19 scientific information, with rapid
review processes and preprint post-
ings.35 Dissemination of COVID-
19–related information exploded; more
than 16 000 scientific publications,
including greater than 6000 on preprint
servers, were posted in just 4 months.
Online and digital technologies sup-
ported low-cost and timely remote sci-
entific collaborations.36 Collaborative
scientific innovation on mRNA technol-
ogy greatly accelerated vaccine devel-
opment,37 and scientists in multiple
settings worked rapidly to build the evi-
dence base on the effectiveness of
masking for both source control and
user protection. The pandemic acceler-
ated scientific collaboration and pro-
moted new norms around transparency
and sharing.
Sustaining a culture of scientific col-
laboration positions public health sci-
ence to be enriched with innovation and
cross-sectoral expertise, including with
sectors outside of health.38 Concerted
effort by scientists will be needed to
implement transdisciplinary and con-
vergence research39; advance applied
laboratory science; conduct community
participatory research; pursue research
innovation and develop novel methods,
such as transdisciplinary environmental
health disparities research40; and host
transparent genomics studies to explain
health outcomes and vaccine
response.41 Creative public health prac-
tice and academic linkages as well as
transdisciplinary team-based research
approaches could help drive innovation
going forward, including laboratory
advancements.42,43 Improved labora-
tory capacities are foundational to
enhanced public health science, includ-
ing not only laboratory quality and safety
but also advancements in specimen
collection, pathogen inactivation, trans-
port, and rapid characterization; multi-
pathogen and point-of-care assays; and
biomarker-based diagnostics. Collabo-
rative sequence-based pathogen sur-
veillance reinforced by a global network
of reference laboratories can more
swiftly identify new and emerging
pathogens. Scientists can improve pro-
cesses for rapidly posting sequences
and early findings to accelerate evidence
generation for diagnostics, program
implementation, and policy develop-
ment. Modelingthecostsandbenefitsof
reducing chronic disease burden before
the next infectious disease outbreak
could inform a new paradigm for pre-
paredness. Scientists are poised to
continue greater collaboration, which
could be enhanced with local, national,
and global leadership.
CLIMATE SCIENCE
Health threats from climate change are
well-documented,44 and the interplay
between COVID-19 and climate and
environmental factors is multifaceted.40
Environmental determinants of health,
including deforestation and increasing
human presence in wildlife habitats,
have fueled both climate change and
emergence of zoonotic infections.45 Cli-
mate change, especially changes in
temperature and precipitation, can
result in changes in the distribution,
seasonality, and prevalence of infectious
diseases.46 Air pollution can aggravate
underlying respiratory conditions that
lead to more severe COVID-19 out-
comes.47 Extreme weather events,
including fires and storms, complicated
COVID-19 mitigation efforts48; in turn,
COVID-19 complicated responses to
these disasters.49 COVID-19 also com-
plicated the ability of local health
departments to run climate-relevant
congregate facilities, such as cooling
centers and disaster shelters.50,51 Lock-
downs and reduced mobility and travel
improved air quality, but these positive
impacts rapidly eroded as mobility
increased again.52 Our collective
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response to COVID-19 has been
described as “a rapid learning experi-
ment about how to cope with climate
change.”53 Indeed, COVID-19 and cli-
mate change mitigation share similar
policy challenges, including the impor-
tance of speedy and decisive action to
avoid global financial and public health
impact, the difficulties of gaining public
support for stringent mitigation policies
given politicization of the issues, and the
need to address health disparities and
counter misinformation.54
A strategic public health science
agenda creates the opportunity to
identify effective approaches for these
shared policy challenges. Other key pri-
orities include expanding research on
the relationship between climate and
health outcomes and emerging pan-
demic threats and improving surveil-
lance for climate-sensitive pathogens
and vectors that identify locations and
populations at greatest risk. In addition,
use of predictive analytics and forecast-
ing can help build an evidence base for
early warning systems and for interven-
tions that effectively counter adverse
climate effects, particularly for popula-
tions experiencing environmental injus-
tice,55 such as migrant and refugee
populations.56 Given that climate
impacts span across public health, from
environmental health to chronic and
infectious disease and mental health, an
interdisciplinary approach can support
scientists to expand methods and dem-
onstrate the value of new mandates to
routinely incorporate a climate lens in
public health research.57,58
A NEW ERA OF PUBLIC
HEALTH STRATEGIC
SCIENCE
The COVID-19 pandemic and its impacts
continue to grow, fueling the imperative
to create a new era of public health
guided by strategic science. The 6
themes emerging from COVID-19 expe-
rience discussed here—health equity
science, data science and moderniza-
tion, communication science, policy
analysis and translation, scientific col-
laboration, and climate science—can
help formulate a strategic public health
science agenda that accelerates
achievement offuture public health goals
(Box 1). To succeed, public health science
should be grounded in scientific integrity
and supported by a larger, sustained,
well-trained, and innovative workforce.
Workforce expansion,diversification, and
development will be needed at multiple
levels, including for epidemiologists, data
scientists, and leadership.59 This
enhanced public health workforce could
help break the cycle of panic and neglect
that has characterized public health
attention and resources for decades.60
Given the impact of COVID-19, it is pos-
sible that public health will remain
prominent, especially as vaccination cov-
erage expands, other efforts to reduce
community transmission continue, and
researchers learn more about COVID-
19’s long-term effects. Public health
leaders and scientists have an unprece-
dented opportunity to use strategic sci-
ence to guide and implement a new era
of improved and equitable public health.
ABOUT THE AUTHORS
Rebecca Bunnell and Juliet Ryan are with the Office
of Science, Centers for Disease Control and Pre-
vention (CDC), Atlanta, GA. Charlotte Kent is with
Morbidity and Mortality Weekly Report, Center for
Surveillance, Epidemiology, and Laboratory Serv-
ices, CDC.
Note. The findings and conclusions in this
report are those of the authors and do not nec-
essarily represent the views of the CDC or the
Agency for Toxic Substances and Disease Registry.
CORRESPONDENCE
Correspondence should be sent to Rebecca E.
Bunnell, PhD, MEd, Centers for Disease Control
and Prevention, Atlanta, GA 30333 (e-mail: [email protected]
cdc.gov). Reprints can be ordered at http://www.
ajph.org by clicking the “Reprints” link.
PUBLICATION INFORMATION
Full Citation: Bunnell R, Ryan J, Kent C, CDC Office of
Science, and CDC Excellence in Science Committee.
Toward a new strategic public health science for
policy, practice, impact, and health equity. Am J
Public Health. 2021;111(8):1489–1496.
Acceptance Date: April 15, 2021.
DOI: https://doi.org/10.2105/AJPH.2021.306355
CONTRIBUTORS
R. Bunnell wrote the article with the support of
C. Kent and J. Ryan. Senior scientists from CDC’s
Office of Science and Excellence in Science Com-
mittee, listed in the Acknowledgments, all reviewed
and contributed to multiple drafts and the final
version of this publication.
ACKNOWLEDGMENTS
The CDC Office of Science and CDC Excellence in
Science Committee provided critical ideas and
feedback to help shape the article and revisions.
Members of the CDC Excellence in Science Com-
mittee were Elise Beltrami, MD, MPH (National
Center for Emerging and Zoonotic Infectious Dis-
eases), Amy M. Branum, MSPH, PhD (National
Center for Health Statistics), Dogan Eroglu, PhD
(Office of the Associate Director for Communica-
tion), Susan Goldstein, MD (National Center for
Immunization and Respiratory Diseases), Arlene
Greenspan, DrPH, MS, MPH (National Center for
Injury Prevention and Control), Kimberly Hummel,
PhD (National Center for Emerging and Zoonotic
Infectious Diseases), Vikas Kapil, DO, MPH (Center
for Global Health), Rachel Kaufmann, PhD, MPH
(National Center for Chronic Disease Prevention
and Health Promotion), Wendi Kuhnert-Tallman,
PhD (Office of the Deputy Director for Infectious
Diseases), Aun Lor, PhD, MA, MPH (Center for
Global Health), Sandra Naoom, PhD, MSPH (Office
of the Deputy Director for Public Health Service
and Implementation Science), Sherry M. Owen,
PhD (National Center for HIV/AIDS, Viral Hepatitis,
STD, and TB Prevention), Ana Penman-Aguilar, PhD,
MPH (Office of Minority Health and Health Equity),
Celeste M. Philip, MD, MPH (Office of the Deputy
Director for Non-infectious Diseases), John D. Pia-
centino, MD, MPH (National Institute for Occupa-
tional Safety and Health), Richard Puddy, PhD, MPH
(Office of Associate Director for Policy and Strat-
egy), Tom Savel, MD (Office of Chief Information
Officer), James W. Stephens, PhD (Center for Sur-
veillance, Epidemiology, and Laboratory Services),
Benedict Truman, MD, MPH (National Center for
HIV/AIDS, Viral Hepatitis, STD, and TB Prevention),
Robin Wagner, PhD, MS (Office of the Deputy
Director for Public Health Science and Surveil-
lance), David Williamson, PhD, MS (National Center
for Environmental Health and Agency for Toxic
Substances and Disease Registry), and Andrea
Young, PhD, MS (Center for State, Tribal, Local, and
Territorial Support). Members of the CDC Office of
Science were Micah Bass, MPH, Joanne Cono, MD,
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ScM, Juliana Cyril, PhD, Maryam Daneshvar, PhD,
MS, Julie Fishman, MPH, Locola Hayes, MBA, Rosa
Herrera, BS, Muin Khoury, MD, PhD, Jennifer Lay-
den, MD, PhD, Mary Reynolds, MS, PhD, Shambavi
Subbarao, MSc, PhD, and Bao-Ping Zhu, MD, PhD.
CONFLICTS OF INTEREST
The authors have no potential or actual conflicts of
interest with the content presented in this article.
HUMAN PARTICIPANT
PROTECTION
This activity did not involve human participant
research, was reviewed by CDC, and was con-
ducted consistent with applicable federal law and
CDC policy (see, e.g., 45 CFR 46; 21 CFR 56; 42 USC
§241(d); 5 USC §552a; 44 USC §3501 et seq.).
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Original Article
Copyright © 2021 Tehran University of Medical Sciences.
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International license https://creativecommons.org/licenses/by-nc/4.0/).
Non-commercial uses of the work are permitted, provided the original work is properly cited.
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The second strategic plan of medical ethics: a national report
*Corresponding Author
Bagher Larijani
Address: No. 10, Next to Shariati Hospital, Jalal
Al-Ahmad St., Chamran Hwy., Tehran, Iran.
Postal Code: 1411713136
Tel: (+98) 21 88 63 12 95 -7
Email: [email protected]
Received: 10 Jul 2021
Accepted: 25 Nov 2021
Published: 2 Dec 2021
Citation to this article:
Parsapour A, Shamsi Gooshki E, Malekafzali H,
Zahedi F, Larijani B. The second strategic plan
of medical ethics: a national report. J Med
Ethics Hist Med. 2021; 14: 17.
Alireza Parsapour1, Ehsan Shamsi Gooshki1, Hossein Malekafzali2, Farzaneh Zahedi3, Bagher Larijani4*
1.Assistant Professor, Medical Ethics and History of Medicine Research Center, Tehran University of Medical Sciences,
Tehran, Iran.
2.Professor, Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical
Sciences, Tehran, Iran.
3.Researcher, Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences
Institute ,Tehran University of Medical Sciences, Tehran, Iran.
4.Professor, Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences
Institute ,Tehran University of Medical Sciences, Tehran, Iran.
Abstract
Medical ethics faces several challenges in different aspects
of education, research, and treatment in medicine and
healthcare practice. Design and implementation of a
national strategic plan can pave the way for the
development of a roadmap in various countries to
strengthen ethics and address these challenges.
To create a comprehensive plan compatible with the Iranian
healthcare system, a multidisciplinary team of main
stakeholders compiled a national strategic plan of medical
ethics following several focus group discussion sessions and
two workshops (2014-2017). Ultimately, the plan was
confirmed by the Supreme Council for the Medical Ethics
of the Ministry of Health and Medical Education.
The current paper is a national report of the process and the
medical ethics strategic plan in Iran. We have also tracked
signs of progress and achievements in the country.
In conclusion, this valuable effort has led to significant
success in the implementation of medical ethics in clinical
medicine, medical research, and education by using all the
resources in our country. The participation of all the stakeholders, especially healthcare professionals in
this way is required.
Keywords: Strategic plan; Medical ethics; Health policy; Islamic ethics; Iran.
The second strategic plan of medical ethics: a national report
2 J Med Ethics Hist Med. 2021(December); 14:17.
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Introduction
Along with other advancements in
healthcare during the recent decades in Iran
(1, 2), there have been great efforts to
strengthen medical and healthcare ethics to
build up the country’s ethics capacity (3, 4).
Accordingly, some progress has been made
in various fields of research, education, and
clinical ethics in Iran in the past years (5, 6).
Medical knowledge and related technologies
are rapidly evolving in all disciplines. This
requires the close attention of policymakers,
healthcare professionals, and bioethicists to
provide proper ethical responsiveness and
support. Moreover, establishing and
sustaining an ethical infrastructure at the
national level is necessary to solve the
controversial and complex issues that have
emerged in the field of bioethics in the past
decades.
Strategic planning of the ethics activities to
address the key priorities is one of the
elements on which the success of integrative
ethics initiatives relies (7). Medical ethics
strategic planning paves the way for the
integration of ethics in the healthcare
environment and strengthening ethics in
various fields.
There are several advantages to strategic
planning in the field of medical ethics. These
include assessment of the current situation,
evaluation of strengths and weaknesses,
ability to set goals at the national level, and
empowerment of ethical infrastructure to
ensure ethical standards in healthcare
practice, education, and research.
Activities toward integration, sustainability,
and accountability in clinical bioethics have
been carried out through strategic planning
in several countries. For instance, the
Clinical Ethics Group at the Joint Centre for
Bioethics at the University of Toronto has
formulated its strategy to “foster an ethical
climate and strengthen ethics capacity
broadly throughout healthcare settings as
well as create models in clinical bioethics
that are excellent and effective” (8).
To address the demands in Iran, the first
strategic plan in the field of medical ethics
was introduced and implemented by the
Ministry of Health and Medical Education
(MOHME) in 2002 (4). The vision, mission,
specific goals, and main activities of the plan
were reviewed in a paper published in the
Developing World Bioethics journal in 2006
(4).
To review the progress and discuss the
achievements and challenges, several
workshops and expert panels were held. The
Academy of Medical Sciences of the Islamic
Republic of Iran1 (AMS), in collaboration
with the Medical Ethics and History of
Medicine Research Center (MEHMRC) of
the Tehran University of Medical Sciences
(TUMS), Medical Council2 of the Islamic
Republic of Iran, and Supreme Council of
Medical Ethics of MOHME made
substantial efforts to compile the second
version of the country’s National Strategic
Plan for Medical Ethics (2015-2017). The
Supreme Council of Medical Ethics, known
as the highest-level medical ethics
1 . http://www.ams.ac.ir
2 . http://irimc.org/?LANG=EN
Parsapour A., et al.
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authoritative body inside MOHME, has been
involved in developing this strategic plan.
This was done through active and organized
participation of the council secretariat and
some key members of the council. All the
documents and information required for the
development of the strategic plan have been
provided by this secretariat for the project
team.
It is worth mentioning that the second
strategic plan is not merely an update of the
first one. This article reviews the second
national strategic plan for medical ethics and
discusses its advantages in comparison to the
initial version. We will also mention some
similar plans in other countries.
Methods
The draft of the strategic plan was prepared
by the “Philosophy, Ethics and Biomedical
Sciences Department” of the AMS in
collaboration with the MEHMRC of the
TUMS following several focus group
discussion sessions. The first outline of the
strategic plan was prepared by the steering
committee of the project, which consisted of
the vice president and secretary of the
Supreme Council of Medical Ethics,
Secretary of the National Committee for
Ethics in Biomedical Research, one
professor of Methodology, and the chairman
of medical ethics group of Iranian AMS.
The first draft was discussed in two
workshops on 9th and 30th January 2014.
The 55-member advisory group who
discussed and expanded that first outline
consisted of 31 medical ethics specialists
and Ph.D. Candidates, 13 specialists of
various medical sciences disciplines, six
specialists from the legal and forensic
aspects of medical practice, one religious’
scholar, and one philosopher. Following a
series of study group meetings at the AMS,
the second draft was introduced during the
annual summit of the chairmen of medical
sciences universities, and their opinions
were gathered. The third draft was assessed
and finalized by holding a workshop on 14th
October in 2015. Ultimately, the compiled
national strategic plan of medical ethics was
confirmed by the Supreme Council for
Medical Ethics of MOHME, then published
and widely disseminated as a booklet in
summer 2017.
Experts from various fields of medicine,
medical ethics, law, and jurisprudence
participated in the workshops and other
sessions. Individuals who contributed to this
review process are listed in the
acknowledgments section.
Result
The “Philosophy, Ethics, and Biomedical
Sciences Department” of the AMS decided
to reassess the national medical ethics
strategic plan in collaboration with other
stakeholders after 11 years. The creation of
the strategic plan was initiated by
contemplating the vision and the mission
(Table 1).
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Table 1- Vision and mission statement of national medical ethics strategic plan
Element Definition
Vision
To institutionalize knowledge and practice of medical ethics based on the Islamic
and humane values reflected in all individuals and all pillars of the Iranian health
system, aiming to establish a responsive system with the utmost respect for human
dignity.
Mission
To strive for achieving thorough knowledge and inclusive management (including
needs assessment, policymaking, planning, implementation, monitoring, evaluation,
and rescheduling) of medical ethics in the fields of education, research, and health
services according to the Islamic-Iranian values and by respecting for human
dignity and justice in health.
SWOTs Analysis
The analysis of strengths (S), weaknesses
(W), opportunities (O), and threats (T)
(SWOTs) was conducted as a key
component of the strategic planning process.
SWOTs’ analysis was carried out
comprehensively to identify the internal
(strengths and weaknesses) and external
(opportunities and threats) factors that
intervene with achieving the goals set for the
plan. Table 2 summarizes the output of
SWOTs analysis based on a wide spectrum
of the contributing factors.
Goals, Objectives and Activities
As the next step, the measurable goals and
objectives towards the fulfillment of the
mission were defined and the related
activities were stated. The goals were
prioritized based on the existing
infrastructure and resources.
Table 3 illustrates the defined eight main
goals.
Table 2- Medical Ethics SWOTs Analysis.
S
tre
n
g
th
s
• The presence of executives’ decision-makers and professionals with insights on the Islamic-
Iranian model of progress.
• The stakeholders’ attention towards new issues of medical ethics.
• Feeling the need to work on the new issues of medical ethics due to the raised cultural awareness
and knowledge of the health services recipients and their increasing demands as well as the
development of science and technology in medical sciences.
• Existence of departments for education, research, and services related to medical ethics.
• Existence of a former version of the strategic plan, the National Comprehensive Health Plan, and
other high-level documents.
• Specified structures in the field of medical ethics in the country and the possibility of the
formation of new structures based on the emerging needs.
• Educating and training the ethics professionals and promoting the presence of the graduates in
medical ethics-related fields.
• Availability of scientific resources related to medical ethics.
• Availability of guidelines and codes on issues related to medical ethics.
• Possibility of studying in medical ethics-related fields.
• Possibility of centralized policy-making in the field of medical ethics.
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W
e
a
k
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e
sse
s
• Lack of transparency in the national macro-management policies in the field of medical ethics and
instability of the administratorship in the related fields.
• Lack of a coherent theoretical Islamic–Iranian framework to address medical ethics issues in practice.
• Limited access to basic and applied research and updated original Iranian-Islamic literature in medical
ethics.
• Lack of communication, interdisciplinary, inter-sectoral cooperation, and interaction, particularly between
the universities and the Islamic seminaries.
• Inadequate numbers of medical ethics experts and uncertainty of their position in the organizational chart
of the healthcare system.
• Insufficient access to the international scientific resources and communications in the related fields.
• Unavailability of the necessary resources to support medical ethics research.
• Weakness of the educational content and implementation processes of medical ethics educational
curriculums.
• Ignoring the professional ethical capability in recruiting, the assessment, and promotion of the learners,
faculty members, and providers of health services.
• Lack of appropriate and consistent rules, regulations, and bylaws about several issues of medical ethics.
• Lack of efficient system for monitoring and surveillance of medical ethics.
• Absence of an institutional mechanism for ethical appraisal of policies, rules, and regulations in the health
system.
• Absence of nationwide structures and national, provincial, and organizational ethics committees in areas
other than research, e.g., the absence of national committees of clinical ethics and ethics in medical
education.
• Weaknesses in the management of medical ethics research to direct them towards solving ethical problems
of the healthcare system.
O
p
p
o
rtu
n
itie
s
• Emphasis of the Supreme leader on theorizing in the field of humanities, knowledge-producing, and
discourse based on ethical-spiritual values.
• Numerous areas for research in the field of medical ethics.
• Islamic-Iranian noble resources of knowledge related to medical ethics.
• Growing demand for the ethical improvement of education and research among the scientific and medical
community as well as the stakeholders.
• Support of the high-level national documents, including the constitution, development plans, and national
comprehensive scientific map, for ethical development.
• Researchers interested in medical ethics.
• Religious beliefs, inner conscious, unconscious ethical, and common cultural, ethical, or moral beliefs
among the society.
• Active related intellectual fields such as jurisprudence, philosophy, sociology, etc.
• Potential stakeholders’ desire to enter this field.
• Research and educational institutes in medical universities that are active in the field of medical ethics.
T
h
re
a
ts
• The negative influence of the public ethics issues on professional medical ethics.
• Reduced public trust in the medical community.
• Reduced motivation of healthcare community to work effectively due to the socio-economic conditions.
• Insufficient justification of the stakeholders of medical ethics discourse and lack of common language
among the clergy, doctors, lawyers, philosophers, and other stakeholders.
• Governance of technical-empirical paradigm (worldview) over the humanities worldview in the country.
• Growing tendency to use the medical methods and devices for non-medical purposes
• Lack of sufficient sensitivity to vulnerable groups including migrants, refugees, and slumdogs.
• Lack of public awareness and misunderstanding of medical ethics debates.
• Wrong and restrictive perception of laws and regulations affecting the implementation of medical ethics.
• Lack of the explanation of the consistency between the Islamic and Iranian medical ethics with the
predominant secular discourse of medical ethics.
• Uncontrolled and unmannered use of the social networks by students.
• Giving the power to enhance commercial, technological, and industrial aspects of medical professions.
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Table 3- The main goals of the national strategic plan for medical ethics in Iran.
Goal 1
To attain the basic Islamic-Iranian framework based on the heritage of medical
ethics regarding the related contemporary knowledge.
Goal 2
To assemble a national collection of documents stating the approved standards of
medical ethics.
Goal 3
To achieve and implement policies, structures, and specific resources in the field of
medical ethics.
Goal 4 To obtain the support and involvement of the key stakeholders of medical ethics.
Goal 5 Development of research in the field of medical ethics.
Goal 6 Development of education in medical ethics.
Goal 7
Developing effective national and international communications in the field of
medical ethics.
Goal 8 Establishment of a comprehensive system of action plans in the field of medical ethics
The first goal emphasizes shifting the
medical professionals’ attention towards the
great heritage of Islamic-Iranian knowledge.
Four objectives were defined in this regard,
as follows:
• Assembling, translating, classifying, and
publishing the Islamic texts related to
medical ethics.
• Collecting, translating, and critical
evaluation of the contemporary knowledge
of medical ethics.
• Strengthening the conceptualization and
interdisciplinary dialogue in the field of
medical ethics.
• Compiling the textbooks related to medical
ethics.
To pursue the goal and its related objectives,
the 19 defined activities included compiling
comprehensive textbooks for the students of
different fields of study (general medicine,
nursing, dentistry, pharmacy, etc.) and at
various education levels. Development of
the “Islamic Medical Ethics Encyclopedia”
and other reference books are also among
these activities.
The second goal aims to provide necessary
national documents, codes, guidelines, and
regulations related to medical ethics as
indicated in table 3. This is to be fulfilled
through the following objectives:
• Development of an appropriate mechanism
for the required assessment of ethical
standards (laws, regulations, and guidelines
related to medical ethics).
• Supporting the development of ethical
standards (laws, regulations, and guidelines
related to medical ethics).
• Design and implementation of appropriate
mechanisms for the approval and
legitimization of ethical standards (laws,
regulations, and guidelines related to
medical ethics).
To achieve these objectives, 35 activities
were designed in a detailed and complete
way. These activities included the
“Establishment of a committee to identify
the gaps in legislation and required ethical
guidelines in healthcare and drafting the
suggested regulations and ethical
guidelines”. Compiling ethical codes and
guidelines for the dentistry, pharmacy,
reproductive health, assisted technologies,
organ transplantation, end of life care,
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emergency medicine, the care of vulnerable
groups, the care of patients with mental
illness, healthcare in disasters, the use of
biobanks, collected health data, the
transmission of biologic samples to foreign
countries, etc.
Goal 3 focuses on achieving and
implementing policies, organizational
structures, and resources in the field of
medical ethics through the following five
objectives:
• Creating the necessary organizational and
administrative structures for healthcare
institutions.
• Providing required financial and human
resources for the healthcare institutions.
• Considering ethical enclosures in all
policies, laws, and regulations related to
healthcare.
• Ethical surveillance and monitoring of all
the healthcare-related policies and
regulations.
• Revising the health system regulations and
laws based on ethical approaches and
concepts.
The establishment of the national committee
for clinical ethics and related secretariat
office in the MOHME are among 18
activities set to achieve this goal and its
associated objectives. Forming the
departments of medical ethics in the major
organizations such as the “Iranian Medical
Council” and the “Nursing Organization of
the Islamic Republic of Iran” and providing
the checklists and regulations for ethical
appraisal of the pharmacies, the drug
companies, medical professionals, faculties,
fellows, residents, and students in the field
of healthcare are among these activities.
Likewise, the allocation of specific funds to
support the educational, research, and
executive affairs of medical ethics by the
MOHME is one of the activities related to
the third goal.
Involvement of the main stakeholders in the
field of medical ethics and attracting their
support and contribution have been
following through the objectives of the
fourth goal as outlined below:
• Developing appropriate strategies for
disseminating information to the key
stakeholders including the general public
and patients.
• Creating appropriate mechanisms for
surveillance and obtaining feedback from
key stakeholders including the public and
patients.
• Providing a supportive environment for the
stakeholders’ engagement and their support.
• To support founding non-governmental
organizations (NGOs) in the field of medical
ethics and encourage the existing health-
related NGOs to focus on the issues of
medical ethics and patient rights.
Activities defined for materializing the goal
include teaching general concepts of
bioethics, patients’ rights in high schools
and compiling age-appropriate books for the
children and adolescents to familiarize them
with the ethics-related issues.
Six objectives are defined for the fifth goal
that targets expanding research in the field
of medical ethics. The objectives include:
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• Development of necessary strategies for
the needs assessment and priority-setting for
research in the field of medical ethics.
• Supporting research in the field of medical
ethics in all related healthcare sciences.
• Backing the production of evidence-based
science in the field of medical ethics.
• Supporting the publication of the scientific
literature and improving the quality of the
existing journals.
• Provision of the infrastructure needed by
medical ethics researchers to access
international resources.
• Providing required funds for essential
research projects and national initiatives in
the field of medical ethics.
Moreover, the foundation of the medical
ethics research centers in the leading
universities of the country, integrating
medical ethics departments within the
structure of specialized medical research
centers, creating and supporting related
journals, holding medical ethics conferences,
post-doctorate, sabbatical courses, and
providing comprehensive databases of
medical ethics studies and researchers are
among 11 activities defined for fulfilling the
fifth goal.
Goal 6 focuses on education emphasizing
the following objectives:
• Qualitative and quantitative improvement
in the relevant academic courses on medical
ethics as well as expanding the
interdisciplinary postgraduate programs.
• Forging regional, and international,
scientific, and educational collaborations
with prominent universities by supporting
the student and faculty exchange programs.
• Improving the quality of medical ethics
education provided to the learners in
different disciplines at various levels.
• Integration of medical ethics education into
the curriculum of all medical and health-
related disciplines.
• Providing and offering medical ethics and
professional ethics education in the form of
in-service programs and continuing medical
education (CME) courses for the healthcare
system personnel.
The change of the pedagogical methods in
medical ethics from the traditional lectures
to the interactive methods such as small
group discussion, workshops, case reports,
launching dual degree doctorates
(MD/Ph.D.), MD/MPH programs,
fellowships, and short-term courses in
clinical ethics and research ethics are among
13 activities listed under the sixth goal.
The seventh goal aims to promote
collaborative activities in the country or
around the globe and consists of four
objectives, as follows:
• to establish a national medical ethics
network with the participation of all main
stakeholders.
• To support organizing national, regional,
and international conferences on medical
ethics.
• To provide Iranian researchers with the
opportunity to participate in regional and
international conferences.
• To develop international collaborations and
partnerships with the universities and
institutions scientifically active in the field
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of medical ethics.
To achieve these objectives, twelve activities
including the establishment of a regional
medical ethics forum in the Eastern
Mediterranean Region, founding the Islamic
Medical Ethics Forum within the Islamic
countries, facilitating membership in
regional and international organizations
related to medical ethics, and signing
agreements for scientific cooperation with
national and international universities have
been considered.
Four objectives shed more light on the
operational planning of medical ethics as the
8th goal:
• Establishing future studies and a
surveillance system for medical ethics in the
fields of education, research, and service
delivery.
• Establishing a system for monitoring,
evaluation, and providing feedback for
medical ethics in the fields of education,
research, and service delivery.
• Integrating the descriptive and analytical
data and findings in the field of medical
ethics.
• Establishing a rating, accreditation system,
and encouraging ethical features in the
healthcare system.
The main related activities are consisted of
developing a framework for the national
reports in the field of medical ethics,
compiling annual reports of “medical ethics
strategic planning program”, “ethics in
medical sciences research”, “monitoring of
medical ethics education”, “observing
patients’ rights and the status of the medical
professionals’ rights”, “evaluating justice in
health care”, “analysis of complaints
received by the MOHME, the Iranian Legal
Medicine Organization (LMO), and the
Medical Council of the Islamic Republic of
Iran”
Discussion
The historical documents confirm the
Iranian physicians’ interests in ethical
conduct in their practice for centuries (9,
10), under the influence of the rich culture
and the religious principles of
Zoroastrianism and Islam (11). Despite
facing various difficulties in the recent
decades (12), substantial scientific progress
has been made in the field of medical ethics
in the country (13).
After the compilation of the first national
strategic plan of medical ethics in 2002 (4),
policymakers, related organizations,
faculties, and researchers were responsible
for its implementation. Key stakeholders
approved the vision and mission of the plan
and were committed to achieving its goals. It
is worth mentioning that in the current
strategic plan, the specified stakeholders
consisted of seven groups as follows:
1. International stakeholders (such as UN
agencies, regional scientific organizations,
associations, universities, and research
centers, especially in the Islamic world).
2. Decision-making and policy-making
bodies including the Parliament, High
Council of the Cultural Revolution, the
Guardian Council, and the MOHME.
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3. Governing and executive bodies including
the MOHME, several related ministries,
Iranian Legal Medicine Organization, Red
Crescent Society, regulatory authorities, and
medical universities.
4. Clients (Patients, their relatives, and the
whole community).
5. Unions and Professional Organizations
(the Medical Council and the Nursing
Council of the Islamic Republic of Iran).
6. Service providers (including Hospitals,
clinics, health care providers, insurance
companies, and pharmaceutical or medical
equipment companies).
7. Professional stakeholders (educational
departments and instructors in the field of
medical ethics at the universities and the
religious seminaries, research centers related
to the field of medical ethics, postgraduate
students, and faculties).
The process of design and development of
the current strategic plan was led by the
AMS, a high-level independent scientific
authority in the country. This is considered
as an advantage and opportunity to generate
the plan through the consensus of several
stakeholders and reinforce their
responsibilities for achieving future goals. It
is so important that the AMS set timelines
and monitor the progress of the plan towards
the goals. Moreover, reviewing the plan
would be carried out regularly.
All the key stakeholders are expected to be
fully engaged in the implementation of the
plan, commit time and efforts to venture out
and accomplish the objectives. Despite the
consensus on the defined goals and
activities, there may be controversies on the
priority rankings of the action plan and
surveillance strategies.
The World Medical Association (WMA)
adopted a 5-year (2020-2025) strategic plan3
in 2019, the main purpose of which was to
promote international standards in medical
ethics. “Medical Ethics”, “Universal Health
Coverage”, “Human Rights and Health”,
and “Organizational Capacity” are four
main strategic priorities. Promoting the
international code of medical ethics along
with global discussion to provide a new
revision of the international code of ethics in
2022, governance development, member
integration, and staff development are
among the priorities and deliverables.
The Emory Center for Ethics (Atlanta,
Georgia, US) has been a leader in several
fields of ethics since 1990, creating the first
5-year strategic plan in 2011. The “Vision”
of the second strategic plan (2016-2021) is
“to inspire and advance scholarship and
education in ethics, to ignite the moral
imagination of leaders in all walks of life,
and to foster lives of moral meaning and
ethical engagement”.4 Key strategic priority
areas of the Center consist of:
– Ethical engagement through scholarship
– Ethical engagement in health and science
– Ethical engagement through corporate
partnerships
– Ethical engagement through citizenship and
the public good
– Ethical engagement in education
3. www.wma.net/wp-content/uploads/2020/02/2020-
2025-Strategic-plan-1.pdf
4.http://ethics.emory.edu/about_the_center/CFE%20Strat
egic%20Plan%202016%202021%20FINAL.pdf
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– Ethical engagement in Arts
– Ethical engagement through financial
stability
For each strategic priority, some initiatives
and their metrics are determined. For
example, academic books and peer-reviewed
journal articles are two initiatives of “Ethical
Engagement through Scholarship”. As for
“Ethical Engagement in Education”, some
initiatives such as developing ethics
curriculum and courses (undergraduate,
graduate, doctoral) and non-degree
educational offerings are defined. Defining
metrics for each initiative plays an
encouraging role in engaging the faculties
and the members in related studies.
Kirigia et al have reviewed and discussed
the current status as the way forward to the
establishment of the national health research
systems in 47 countries of the World Health
Organization (WHO) African Region (14).
Although “Research for Health” was the
subject of their study, their strategies and
recommendations are used in other fields as
well as for strengthening medical ethics
discourse. Several key contributing factors
emphasized by Kirigia et al include (14):
– An official national health policy and
strategic plan
– Related legislation components
– Appropriate coordination mechanisms
– Regulation mechanisms for scientific and
ethical review committees at national and
institutional levels and in hospitals and
clinics
– Developed collaborative agreements
– Creating and sustaining resources
– Financing and health budgetary planning
– Securing funding by the private sector and
local and international NGOs
– Promotion and implementation of research
– Facilitating the production of human
resources and strengthening their
competencies through design and
implementation of master and Ph.D. courses,
bursaries, and training grants
– Building or reinforcing necessary
infrastructures, such as well-equipped
offices and laboratories
All identified factors that enable national
health research systems are critical for the
establishment and reinforcement of the
national medical ethics plans. Fortunately, it
seems that the eight goals of our strategic
plan cover all emphasized factors stated by
Kirigia et al (14).
The national strategic plan working group
has approved 60 activities including
compiling books and educational resources,
ethical guidelines, related codes, and
regulations. It has also endorsed 60
recommendations to MOHME to provide the
required infrastructure and empower the
healthcare professionals. Table 4
summarizes the key activities carried out in
recent years, before and after compiling the
second strategic plan.
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Table 4- Summary of some key activities in recent years
Title/type Timeline
In accordance
with
Responsible
Organization(s)
General guideline for Professional
Codes of Ethics
2017 Goal 2
The Medical Council of
Islamic Republic of Iran
Revising National Guidelines for
Publication Ethics
2017 Goal 2,4,5 MOHME
Compiling a textbook as an
educational resource for medical
residents
2015-2020 /
in press
Goals 1,6
MEHRC, the Medical Ethics
Group of EMRI of TUMS
Evolution and Innovations packages in
Medical Education: 6th package:
Promotion of Professional Ethics
2015-2016 Goal 6 MOHME
Herbal Medicine Research Protocol 2015 Goal 2 MOHME
Hidden curriculums as longitudinal
themes for “medical ethics and law”
and “professionalism”
ongoing Goal 6
TUMS, and a few other
designated universities
The Charter of Rights for clients in
Medical diagnostics Laboratories
2012 Goal 2
High Council of Medical
Ethics of MOHME
The code of Ethics for National
Pharmaceutical System
2012 Goal 2
MEHRC, High Council of
Medical Ethics of MOHME
The National Code of Ethics for
Nurses
2009-2011 Goal 2
The Medical Ethics Group
of EMRI of TUMS, MEHRC,
MOHME
Enhancing specific publications such
as journals in the field of medical
ethics; including the Journal of
Medical Ethics and History of
Medicine
ongoing Goal 1
MOHME, Ethics research
centers and universities of
medical sciences
Annual Medical ethics Congress/
And Training workshops and courses
2013- up to
now /
ongoing
Goals 3,4,6,7
MOHME, MEHRC, AMS,
TUMS and other
Universities of Medical
Sciences, etc.
Defining an educational package to
promote medical ethics and
professionalism
2016-
now/ongoing
Goal 6 MOHME
Evaluating teaching medical ethics in
all medical universities
2018-2019 Goal 6 MOHME
To plan and execute the proposed activities
to achieve the goals, several tasks are in
progress. As an example, the development of
the Iranian Code of Medical Ethics (ICOM)
to determine the ethical codes of mutual
behaviors in the provision of medical
services are being pursued by the MEHRC
at the Tehran University of Medical Sciences
in collaboration with the AMS. The ICOM
has been on the agenda with approximately
150 headings; 24 topics of which have
already been completed in the public
consultation phase. After summarizing and
incorporating the feedback from the
workshop participants, the codes were
published in Farsi (Persian Language) to
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seek the input of the healthcare academics
and practitioners. The final results are
reported in a recent report of AMS.5
Moreover, the promotion of ethical
standards and the development of related
guidelines have been high on the agenda
during recent years. For example, specific
national guidelines for palliative care in
terminal patients have been compiled by the
medical ethics department of the
“Endocrinology and Metabolism Research
Center of Endocrinology and Metabolism
Institute (EMRI)” of Tehran University of
Medical Sciences (TUMS) in 2017 due to
the ever-increasing attention to palliative
care in the country. This was supported by a
grant from the WHO office in the MOHME.
The results of the project6 were submitted to
the High Council of Medical Ethics of
MOHME and after approval (February
2019) was conveyed to the medical sciences
universities for being implemented in
clinical practice.
Education is an integral part of the current
strategic plan and has been the focus of
accrediting bodies. Although working in the
field of medical ethics requires lifelong
learning, the educational mission of ethics is
never accomplished. This is based on the
Henk ten Have stating (15) that the
empowerment of medical ethics education
has always been one of the main initiatives
around the globe. Accordingly, more than
5.http://www.ams.ac.ir/sites/default/files/book%20Akhl
agh%201400–02-18-021.pdf
6. Available (in Farsi) at:
http://nursing.fums.ac.ir/images/Palliative_Care_guidelin
es-Final_compressed.pdf
twenty projects including the development
of textbooks for different graduate and
undergraduate programs, ethical guidelines
for medical education, and ethical checklists
for health professionals have been proposed.
To achieve the educational goal of the new
strategic plan, we designed a national
descriptive survey to evaluate the medical
ethics education in medical sciences, which
is an ongoing project. Providing higher
academic education in the field of medical
ethics is also considered an educational
achievement in our country (5). The
bioethics graduates are now helping to
empower medical ethics discourse in the
research centers, clinics, and hospitals, to
provide specific education, ethics
consultations, and to lead ethics ground
rounds, and even to contribute to health
policymaking.
Conclusion
Academic knowledge and practice of
medical and research ethics have developed
enormously in recent decades. Compared
with the first strategic plan (4), we have
made great progress in strengthening and
flourishing medical ethics throughout the
country. However, considering the ethical
challenges ahead, it is evident that there is
no room for complacency.
The development of the medical ethics
strategic plan was an attempt to improve the
capacity of the health system to be more
proactive in client advocacy. Today, the
main challenges facing our healthcare
system include increasing moral sensitivity,
enhancing adherence to ethical principles
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amongst medical professionals and
promoting a positive ethical climate in the
system. It is also known that an acceptable
level of accountability of health
professionals is necessary to provide decent
standards of care in an ethical atmosphere.
We hope that achieving the goals and
objectives of the recent strategic plan would
play an essential role in the promotion of
professionalism among healthcare
practitioners in Iran. The strategic plan
presented in this article can also be adapted
for other contexts and environments, taking
into account the national priorities,
challenges, and shortcomings.
Acknowledgements
We would like to convey our sincere thanks
to workshop participants (in alphabetical
order): Dr. Forozan Akrami, Dr. Khalil
Alizadeh, Dr. Masoud Asadi, Dr. Omid
Asemani, Dr. Amin Asgharian, Dr. Morteza
Ashrafi, Dr. Hamidreza Ayatolahi, Dr. Sajad
Azmand, Dr. FattanehSadat Bathaie, Dr.
Shabnam Bazmi, Dr. Hasan Behboodi, Dr.
Saeed Beiroodian, Dr. Kourosh Delpasand,
Dr. Zeynnab Derakhshan, Dr. Sedighe
Ebrahimi, Dr. SeyedAli Enjoo, Dr. Mohsen
Fadavi, Prof. Dariyoosh Farhhod, Dr. Mina
Foroozandeh, Dr. Nazafarin Ghasemzadeh,
Dr. Sadat Hosseini, Dr. Nikzad Isazadeh, Dr
Maliheh Kadivar, Dr. Ali Khaji, Dr.
Mehrzad Kiani, Dr. Mansoureh Madani, Dr.
Alireza Milanifar, Dr Mina Mobasher, Dr.
SeyedHasan Moghadamnia, Dr. Maryam
Montazeri, Dr. FatemehSadat Nayeri, Dr.
Nasrin Nejadsarvari, Dr. Davood Nezam-
Eslami, Dr. Mahshad Nouroozi, Prof.
Mohammad Pajoohi, Dr. Mojtaba Parsa, Dr.
Roya Rashidpouraie, Dr. MohamadReza
Razaghi, Dr. Mohsen Rezaie-Adriani, Dr.
Mahbobeh Saber, Dr. Mehran Seyf, Dr.
Behzad Shams, Dr. MohammadNader
Sharifi, Prof. SeyedMahmood Tabatabaie,
Dr. Ladannaz Zahedi.. The special thanks go
to Dr. Pooneh Salari, Dr. Amir
Keshavarzian, and Dr. Leila Afshar for their
valuable input and contribution in compiling
this national plan. The authors also would
like to thank Dr. Reza Baradar Jalili and Dr.
Ali Tooti for the English editing of the
paper’s first draft. We have furthermore to
thank Ms. Firoozeh Hajipour for her sincere
cooperation.
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Copyright of Journal of Medical Ethics & History of Medicine is the property of Tehran
University of Medical Sciences and its content may not be copied or emailed to multiple sites
or posted to a listserv without the copyright holder’s express written permission. However,
users may print, download, or email articles for individual use.
Copyright of Journal of Medical Ethics & History of Medicine is the property of Tehran
University of Medical Sciences and its content may not be copied or emailed to multiple sites
or posted to a listserv without the copyright holder’s express written permission. However,
users may print, download, or email articles for individual use.
Cuschieri et al. Health Res Policy Sys (2021) 19:43
https://doi.org/10.1186/s12961-020-00665-y
R E S E A R C H
Mapping the burden of diabetes in five small
countries in Europe and setting the agenda
for health policy and strategic action
Sarah Cuschieri1, Elena Pallari2* , Natasa Terzic3, Ala’a Alkerwi4 and Árún Kristín Sigurðardóttir5,6
Abstract
Background: Diabetes is a global epidemic affecting every country. Small countries, however, face distinctive chal-
lenges related to their health system governance and their ability to implement effective health systems’ reforms.
The aim of this research was to perform a comparative assessment of existing diabetes management practices at the
population level and explore governmental-related policy for Cyprus, Iceland, Luxembourg, Malta and Montenegro.
This is the first time that such an evidence-based review study has been performed in the field of diabetes. The overall
purpose was to set the agenda for health policy and inform strategic actions for small countries that can benefit from
dealing with the diabetes epidemic at a country level.
Methods: We collected data and synthesized the evidence on dealing with diabetes for each of the five small Euro-
pean countries according to the (1) epidemiology of diabetes and other related metabolic abnormalities, (2) burden
of diabetes status and (3) diabetes registers and national plans. We collected data by contacting Ministry representa-
tives and other bodies in each state, and by searching through publicly available information from the respective
Ministry of Health website on strategies and policies.
Results: Diabetes rates were highest in Cyprus and Malta. National diabetes registers are present in Cyprus and Mon-
tenegro, while national diabetes plans and diabetes-specific strategies have been established in Cyprus, Malta and
Montenegro. These three countries also offer a free holistic healthcare service to their diabetes population.
Conclusions: Multistakeholder, national diabetes plans and public health strategies are important means to provide
direction on diabetes management and health service provision at the population level. However, political support
is not always present, as seen for Iceland. The absence of evidence-based strategies, lack of funding for conducting
regular health examination surveys, omission of monitoring practices and capacity scarcity are among the greatest
challenges faced by small countries to effectively measure health outcomes. Nevertheless, we identified means of
how these can be overcome. For example, the creation of public interdisciplinary repositories enables easily accessi-
ble data that can be used for health policy and strategic planning. Health policy-makers, funders and practitioners can
consider the use of regular health examination surveys and other tools to effectively manage diabetes at the popula-
tion level.
Keywords: Type 2 diabetes, Noncommunicable diseases, Healthcare systems, Health policy, Healthcare delivery,
Global burden of diseases, Small countries
© The Author(s) 2021. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which
permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the
original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or
other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line
to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory
regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this
licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/. The Creative Commons Public Domain Dedication waiver (http:// creat iveco
mmons. org/ publi cdoma in/ zero/1. 0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
Open Access
*Correspondence: [email protected]
2 MRC Clinical Trials and Methodology Unit, University College London,
London, UK
Full list of author information is available at the end of the article
Page 2 of 10Cuschieri et al. Health Res Policy Sys (2021) 19:43
Key messages
• Most small member states have national diabetes
plans, national registers and strategies.
• Diabetes plans exist in Cyprus, Malta and Monte-
negro, countries that have relatively higher diabetes
prevalence rates and burden of disease compared to
the much lower diabetes burdens in Luxembourg and
Iceland.
• Regular health examination surveys are currently
missing and, as part of monitoring and evaluation,
this is something that should be considered.
Introduction
Noncommunicable diseases (NCDs) are global epidemics
that contribute to a substantial burden related to morbid-
ity, disability and premature death. Diabetes falls within
the top five predominating NCDs across the world,
including Europe [1]. In 2019, the International Diabe-
tes Federation (IDF) reported an estimated 463 million
adults (aged 20–79 years) suffering from diabetes world-
wide, with 59 million residing in Europe [2]. By 2045, a
15% rise in the diabetes population is expected to occur
within Europe [2].
With the global spread of the coronavirus disease 2019
(Covid-19) pandemic in 2020, several mitigation legis-
lations have been implemented by almost all countries
across the globe to safeguard the health and safety of
their populations. A number of these legislations have
an effect on the healthcare systems and previously estab-
lished services, including diabetes screening, prevention
and management [3]. Although it is too early to assess
the exact impact of this pandemic on the diabetes situa-
tion across Europe, it can be predicted that the relation-
ship between diabetes and the healthcare services can
only be negative in the near future, especially in light of
the observed relationship between diabetes and Covid-19
[3].
Small countries are known to face distinct challenges
related to their health system governance and their health
service delivery due to lack of capacity, limited resources,
small market size and their constrained ability to imple-
ment effective health system reforms [4]. However, this
is not always the case. Indeed, recently in the face of the
Covid-19 pandemic, the small country of Malta proved
to be a prototype for small and large European countries
alike in the response to the first wave of the pandemic
through health system preparedness and timely measures
[5].
Recently, a common path was agreed among the 11
Member States in the Small Countries Initiative of the
WHO European Region [6] to foster a collaborative
framework, to promote health and reduce health inequi-
ties. These goals were based on the alignment of priori-
ties on health policies within the European health policy
Health 2020 framework, the development of capacity-
building infrastructure to promote health and reduce
health inequities, the set-up of supportive and engag-
ing environments for the implementation of the goals
and the development of a platform to share learning and
experiences.
Considering the extend of the global diabetes epi-
demic, it was considered paramount to also explore
this epidemic from a small-country perspective, while
investigating how the associated population-level stra-
tegic planning can be improved. The World Bank and
the Commonwealth define small countries or states as
those with populations under 1.5 million. This defini-
tion together with data on the countries participating
in the COST Action CA18218–European Burden of
Disease Network (burden-eu) [7] allowed us to include
Cyprus, Iceland, Luxembourg, Malta and Montenegro
in this study. The objective of the study was to perform
a comparative assessment of the existing diabetes situa-
tion at the population level while assessing the particu-
lar country’s governmental-related policy among these
five small countries in Europe. The overall aim was to set
up an agenda for health policy and strategic action for
small countries in dealing with the diabetes epidemic at
a country level. More broadly, the goal is to contribute to
the overall continuous battle against the diabetes crisis by
identifying potential solutions for small countries.
Methods
Methodology rationale
The authors are members of the CA18218–European
Burden of Disease Network (burden-eu) CA18218 that
focusses on mapping the burden of disease at the Euro-
pean level. Our study was based on a simple model of
analysing the existing state of diabetes by synthesizing
the evidence to make relevant suggestions on disease
management and health policy for these countries. The
methodology is split into three parts.
The first part is concerned with the context of analys-
ing the five small European countries of Cyprus, Ice-
land, Luxembourg, Malta and Montenegro. The rationale
behind this selection is threefold. Firstly, there is a lack
of studies conducted at a national level in these countries
and, hence, this provides an appropriate opportunity to
study these. Secondly, when compared to other European
countries, these small countries have a high prevalence
of diabetes and, as such, it was considered appropriate to
focus on these countries to shed light on the problem at
hand and how it can be tackled. Thirdly, when comparing
Page 3 of 10Cuschieri et al. Health Res Policy Sys (2021) 19:43
small states, lessons can be learnt not only to help small
countries but also to inform actions and decisions in
geographically larger countries, with a more decentral-
ized decision-making system in place, or at a regional
level, having the same population size as that of an entire
small-country state.
The second part of this work involves the documenta-
tion of the health-policy status for each of the five small
European countries according to the (1) epidemiology of
diabetes and other related metabolic abnormalities, (2)
burden of diabetes status and (3) diabetes register and
national plans. Our proposed study aims to contribute
to the aforementioned effort within Health 2020 by iden-
tifying gaps, differences and similarities between these
countries towards evidence-based health-policy planning
and strategic action.
The third part of the study is focussed on the synthesis
of the findings of an evidence-based proposal on diabetes
management in the following three dimensions: (1) mon-
itoring and evaluation, which covers health examination
surveys and their implementation in the five countries;
(2) prevention, to draw on existing practices for public
health diagnostic and screening practices; and (3) health
system performance, to contextualize the impact of care
delivery on the disease burden for each population.
A summary of the methodology protocol can be seen
in Fig. 1.
Data sources
We collected data by contacting Ministry representa-
tives and other governmental bodies in each state, and
searched for publicly available information from web-
sites on strategies and policies as available at the respec-
tive Ministry of Health, some health sector divisions
and appropriate bodies, such as statistical organiza-
tions. We identified published articles originating from
national surveys and datasets conducted in each of the
five countries: Cyprus, Iceland, Luxembourg, Malta and
Montenegro. When data were not available online, we
contacted the corresponding person who would in turn
send us the available nonconfidential data. We searched
for documents on national strategies, action plans and/or
policies on NCDs and diabetes at a country level.
Data analysis
The burden of diabetes at a population level was evalu-
ated in terms of the “disability-adjusted life years”
(DALYs) metrics as reported by the Institute for Health
Metrics and Evaluation (IHME) in their Global Burden of
Disease (GBD) study [8]. The same resource was used to
evaluate each country’s profile characteristics [8]. Com-
parisons between the DALYs, years lived with disability
(YLDs) and years of life lost (YLLs) data were performed
for the five small countries, using the GBD Compare tool
[9]. DALYs is an overall measure of the disease burden
that takes into account the YLDs and the YLLs due to a
disease, which in this case is diabetes. The importance
of DALYs is that it provides a consistent, geographic and
time-bound metric of population health on both mor-
bidity (YLDs) and mortality (YLLs) measures in units of
years. The use of DALYs can assist in relative compari-
sons between countries for a specific condition to iden-
tify gaps in performance, research, health delivery or
policy to prevent illness, disability or premature death.
It can also be used to guide health system planning and
public health interventions within a country for different
Fig. 1 The research methodology
Page 4 of 10Cuschieri et al. Health Res Policy Sys (2021) 19:43
diseases or by tracking changes for a specific disease over
time. Epidemiological data were obtained from the lit-
erature in each of the five states for both incidence and
prevalence per 100,000 people.
The scientific literature was reviewed by the authors
and common frameworks were identified. The data
were categorized according to diabetes: prevalence
data, diabetes register, governmental strategy and pol-
icy and diabetes health care. Subsequently, the pub-
lished literature, strategies, policies and burden of
disease data were reviewed, and an agenda for policy
and strategy action based on the small countries expe-
rience was formulated.
Results
Table 1 shows the population characteristics of the five
small countries in Europe that were included in the
study according to the GBD study for 2017. Although
all five countries have comparable life expectancy,
intercountry variations are still observed. Cyprus
ranked the highest in terms of diabetes mortality at the
population level, followed by Montenegro and Malta.
Epidemiology of diabetes and other related metabolic
abnormalities
Diabetes prevalence rates varied across the five small
countries, with the highest rates being reported in Malta
and Cyprus followed by Montenegro (Table 2) [10–13].
However, it is worth noting that the data obtained from
surveys were conducted in different time frames as well
as following different study protocols. For example, Mon-
tenegro’s diabetes estimate was based on a combina-
tion of data obtained from a national register under the
patronage of the Institute of Public Health and the pri-
mary healthcare information system. A similar picture is
observed for the prevalence of obesity, where the high-
est obesity rates among the five small countries were
reported by Malta (Table 2) [12, 14–17]. Yet, data on
impaired glucose regulation (impaired glucose tolerance
or impaired fasting glucose) and the metabolic syndrome
Table 1 Distribution of the population characteristics among the five small countries in Europe, 2017 [6]
GDP Gross domestic product
Population characteristics Cyprus Iceland Luxembourg Malta Montenegro
Population 875.9 K 337.5 K 590.5 K 434.5 K 626.3 K
GDP per capital (in $US) 31,531 47,062 97,887 36,920 15,716
Life expectancy at birth (in years) 81.85 82.85 81.65 80.95 76.5
Diabetes death ranking at a population level 5th > 10th > 10th 8th 6th
Table 2 Comparisons between prevalence of the different metabolic abnormalities across the five small countries in Europe
BMI Body mass index
Prevalence Cyprus Iceland Luxembourg Malta Montenegro
Type 2 diabetes 10.4% (2005) 6.72% (2005–2011) 9.8% (2016–2018) 10.4% (2014–2016) 10.2% (2014)
Obesity (BMI > 30 kg/m2) 25.5% (2008) 26.6% (2017) 19.2% (2016–2018) 34.1% (2014–2016) 25% (2016)
Impaired glucose tolerance – – 25.6% (2013–2015) – –
Impaired fasting glucose – – – 24.3% (2014–2016) –
Metabolic syndrome – – 28.0% (2008–2009) 26.3% (2014–2016) –
Fig. 2 Comparative summary of the diabetes epidemiology and official diabetes registers and plans across the five small countries in Europe
Page 5 of 10Cuschieri et al. Health Res Policy Sys (2021) 19:43
was available only for Luxembourg and Malta (Table 2)
[18–23].
Diabetes register and national plans
Official national diabetes registers are only present in
Cyprus and Montenegro. Malta’s national diabetes reg-
ister is still in the pipeline. However, the Endocrinol-
ogy Department of Malta’s state hospital has an online
database that physicians can voluntarily input diabetes
patients’ data. This database can act as the foundation
for the construction of a national diabetes register [24].
National diabetes plans have only been established in
Cyprus, Malta and Montenegro [25, 26]. A compara-
tive summary of the official diabetes registers and plans
across the five small countries can be observed in Fig. 2.
Cyprus
In Cyprus, diabetes is high on the health policy agenda
due to its impact on the economy and productivity [25].
A national diabetes strategy (2016–2024) is in place and
it is based on five pillars: (1) prevention, (2) early detec-
tion and care, (3) rehabilitation, (4) diabetes registry and
(5) research. An interdisciplinary body, the National Dia-
betes Committee, has been appointed by the Ministerial
Board in order to execute the policy of this diabetes stra-
tegic plan. There are 12 institutions carrying out research
on diabetes on the island; the University of Nicosia, Nico-
sia General Hospital and the University of Cyprus are
among the top three. Although the island has are no clin-
ical practice guidelines, the specialists follow European
guidance or that of the UK. Cyprus has a high diabetes
prevalence, but the amount of research done in the field
is not appropriate to the needs of the population [27].
In Cyprus, individuals suffering from diabetes are enti-
tled to a holistic healthcare service that includes free
medication and consultations.
Iceland
In Iceland, the position of diabetes within the politi-
cal agenda is a delicate one. Existing national policies
target diabetes-related diseases and risk factors, includ-
ing obesity, overweight, physical inactivity, smoking
and unhealthy eating, but not prevention of diabetes. In
fact, there is no national plan for diabetes [25]. However,
individuals diagnosed with diabetes are eligible for free
medication with a minimal fee for check-up visits to dia-
betologists, diabetes nurses, ophthalmologists and podia-
trists. The diabetes care in Iceland follows the American
Diabetes Association guidelines [28]. An interdiscipli-
nary working group appointed by the Minister of Health
has recently suggested a national diabetes register for Ice-
land [29].
Luxembourg
In Luxembourg there is no diabetes-specific national
plan but rather a general national prevention policy that
targets the different chronic NCD risk factors, including
diabetes, obesity and overweight, dietary habits, smok-
ing, physical inactivity and the harmful use of alcohol [25,
30]. The “Eat Healthy and Move More 2018–2025 Action
Plan” is an interministerial prevention strategy developed
by the Education, Family, Sports and Health Ministries,
with the aim of promoting a healthy diet and physical
activity. Diabetic patients are eligible for free medica-
tion. However, there are no systematic yearly check-ups
organized with endocrinologists or other allied health
professionals. The patients need to organize follow-up
consultations on their own initiative. Those opting to
have check-up consultations will get a percentage reim-
bursement by the government for the incurred fee. In
addition, a national plan for 2019–2023 to fight cardi-
oneurovascular diseases is being implemented, with a
specific focus on diabetes risk.
Malta
In Malta, a national diabetes plan was set up entitled
“Diabetes: A National Public Health Priority: 2015–2020”
[31]. This plan complemented the already existing “Dia-
betes Shared Care Programme” [32]. This programme
follows a multidisciplinary team effort to provide a free
holistic care plan to the diabetes population and includes:
regular follow-ups with a diabetes nurse, diabetologist,
general practitioner with a special interest in diabetes,
dietician, ophthalmologist, ophthalmic nurse and podia-
trist. Furthermore, all individuals diagnosed with diabe-
tes are entitled to free medication as well as to a limited
amount of blood glucose monitoring strips every month.
Additionally, there are a number of preventive strategies
and action plans that target the different risk factors for
diabetes including the “Healthy Weight for Life Strategy”,
the “Noncommunicable Disease Control Strategy for
Malta” and the “Food and Nutrition Policy and Action
Plan for Malta”.
Montenegro
In Montenegro, a governmental “Strategy on Health-
care of People who Live with Diabetes 2016–2020” with
Action Plan 2017–2020 is under completion [26]. The
main objectives of this strategy are to improve the health
of these people through effective measures, including
early detection, control, treatment and prevention of
associated complications. A multisectoral approach is
in place to safeguard the adherence and maintenance of
this strategy. A national strategy for the prevention and
control of NCDs (2008–2020) is also set in place, includ-
ing the “Master Plan for Health System Development
Page 6 of 10Cuschieri et al. Health Res Policy Sys (2021) 19:43
(2015–2020)” focussing, among other things, on pri-
orities for diabetes. Montenegro has other strategies,
including the “National Strategy for Sustainable Devel-
opment—NSSD 2016–2030” and the “Strategy for
Healthcare Quality Improvement and Patient Safety
2019–2023”, with both strategies targeting NCDs. Indi-
viduals with diabetes are eligible for free medication and
healthcare services under the Compulsory Health Insur-
ance Act.
Burden of diabetes
On assessing the DALYs metric for the diabetes situation
across the five small countries in Europe, we draw on dif-
ferences and similarities, as shown in Table 3. Montene-
gro had the highest diabetes DALYs and YLDs for 2017
compared to the other small countries; however, Cyprus
had the highest YLLs for the same year.
Discussion
Diabetes is a growing epidemic that gives rise to several
different challenges and imposes a substantial burden
on healthcare services. This has led to a number of col-
laborative reports and joint actions between countries
and states that are members of the EU with the aim of
addressing this epidemic [33]. Across Europe, many
countries have introduced national diabetes plans or
NCD strategies as part of a national effort to contain this
epidemic. We identified a wealth of information related
to the strategies and action plans that are related to (1)
monitoring and evaluation aspects, (2) prevention and
(3) health system performance.
A multistakeholder approach is key when develop-
ing such strategies, in addition to a sustainable political
leadership [1, 34]. However, political support for a spe-
cific framework allocated only to diabetes is not always
in place, as seen Iceland, which has the highest gross
domestic product (GDP) of the five small states studied.
On the other hand, national diabetes plans are already
established in Cyprus, Malta and Montenegro. These lat-
ter three small countries have relatively higher diabetes
prevalence rates and burden of disease compared to a
much lower diabetes burden in Luxembourg and Iceland.
Nevertheless, all five small countries have an established
preventive strategy targeting the various diabetes risk
factors and NCDs.
Monitoring and evaluation
The key to successful NCD strategies is the continuous
monitoring and evaluation of the situation at a popula-
tion level [1]. This is maintained by undertaking regular
health surveys, ideally through health examination sur-
veys. Without regular updated evidence-based data,
there will be sparse evidence on whether the strate-
gies are working efficiently and whether there is a need
for more rigorous interventions. Conducting regular
health examination surveys is one of the many challenges
faced by most small countries due to the lack of human
resources and research budget allocation. In fact, over
the past 15 years, a national representative health exami-
nation survey covering diabetes was conducted only once
in Cyprus and Malta, never in Iceland and Montenegro,
while in Luxembourg health examination surveys were
performed on a regular basis (2007–2008, 2013–2015
and 2016–2017) [13, 35–37]. The European Health Inter-
view Survey consists of a number of health modules,
including a self-reported medical history of diabetes,
and is conducted every 5 years among the EU countries,
including Iceland [38]. This type of survey depends on
self-reporting; hence, it is prone to incorrect recall infor-
mation biases. However, it still constitutes a good source
of information on health indicators at the population
level, with reasonable resources.
Prevention: management plans and execution
An integrated approach is required when targeting
chronic diseases, including diabetes [39]. Prevention is
one of the key priorities in terms of reducing the burden
of diabetes within the population [1]. In fact, prevention
is one of the key pillars of the national diabetes plans
set up by Cyprus, Malta and Montenegro [31]. Regard-
less of this focus on prevention, it is of utmost impor-
tance that such strategies are adhered to and maintained.
Establishing multidisciplinary diabetes care protocols in
each country may be the way forward to ensure adher-
ence to such strategies. Nonetheless, it is paramount that
adequate human resources, infrastructure and financial
budget allocation are present to enhance the healthcare
services. In Montenegro, a multisectoral approach has
been established to ensure that the strategies are adhered
to. However, the implementation of these strategies still
Table 3 Distribution of the burden of disease metrics for
diabetes across the five small countries in Europe for 2017 [7]
DALYs Disability-adjusted life years, GBD GlobalBburden of Disease, YLDs years
lived with disability, YLLs years of life lost
GBD
burden
of disease
study
(2017)
Cyprus Iceland Luxembourg Malta Montenegro
DALYs per
100,000
1098 526.98 786.65 1172.67 1254.47
YLDs per
100,000
600.66 429.75 639.76 776.97 847.71
YLLs per
100,000
497.34 97.23 146.89 395.7 406.76
Page 7 of 10Cuschieri et al. Health Res Policy Sys (2021) 19:43
presents a major challenge. The small island of Malta
together with Cyprus have the highest DALYs burden of
the other small countries; they both have one of the high-
est prevalence rates for both diabetes and obesity [10,
14]. Although Malta has had a National Diabetes Plan
in place since 2014, an official diabetes screening frame-
work is not yet present even if various recommendations
have been suggested [10, 31, 40]. For Cyprus, the burden
of disease data show that YLDs are very similar, about
1.5-fold higher, to data on mortality from diabetes, which
possible illustrates that a better diagnosis and regular
blood glucose management of the disease can prevent
premature deaths. For example, in Malta, it is at the dis-
cretion of the family physician or of the individual to seek
out regular blood glucose testing and screening for dia-
betes. A similar picture is seen for Luxembourg.
Health system performance
A slight discrepancy is observed between the diabetes
holistic management approach offered by the health-
care systems of these five small countries. The diabetes
populations residing in Cyprus, Malta and Montenegro
benefit from a free medication scheme as well as system-
atic check-up routines. This holistic approach is justified
considering the high prevalence of diabetes among each
country’s adult population. Regular follow-up enables
early detection of complications and a reduction in the
healthcare burden. Similarly, the diabetes population in
Iceland has the same opportunities, but individuals incur
a minimal fee for the check-up consultations. As Iceland
has the highest GDP per capita of the five small coun-
tries studied here, this health regulation may be justi-
fied, especially as Iceland has not only the lowest overall
disease burden but also the lowest burden from prema-
ture deaths attributed to diabetes, compared to the other
small states studied. Of all the small countries in this
study, Iceland enjoys the lowest overall diabetes’ burden
even though it was noted that it lacks regular evidence-
based data to allow adequate monitoring of population
health. This is in contrast to Luxembourg, which benefits
from access to such data but still has a higher diabetes
burden among its population. Therefore, the plan for a
more organized diabetes management strategy in combi-
nation with better diagnostic and surveillance databases
can complement the monitoring and control within the
provided framework of service delivery to those small
countries who suffer the most from diabetes.
Implications and recommendations
Small states, irrelevant of their GDP (except for Luxem-
bourg) and their health status, appear to have low pri-
orities for regular and ongoing surveys and population
research. The potential reasons for this are multifactorial
and include: the lack of human resources, minimal allo-
cation of grants and funding for research, different gov-
ernance priorities, among others. These issues hinder
the mapping of the burden of diabetes and the associated
evidence-based policy and strategic action plans. Con-
ducting regular health examination surveys with a low
budget and minimal human resources can be achieved
within small countries. Malta’s Health Examination Sur-
vey conducted by the University of Malta suggests that
an epidemiological health examination survey target-
ing diabetes can be successfully conducted with mini-
mal resources [36]. A “toolkit for the development and
implementation of epidemiological surveys in small
populations” has been compiled by the University of
Malta in collaboration with the World Health Organiza-
tion for Health Systems and Policies in Small States [41]
to illustrate how small countries can use their minimal
resources to conduct epidemiological population-based
research. A public interdisciplinary repository may also
be created where researchers can share their research
and data. It is not uncommon that scholars conduct valu-
able studies as part of an academic endeavour, but the
outcomes are not publicly shared with stakeholders. In
small countries, such studies are more likely to be popu-
lation-based and, if easily accessed, the data can be used
effectively for health policy and strategic planning. How-
ever, the mechanisms for the translation of this evidence
into action are unclear. The collection of accurate health-
related data from healthcare facilities can be more feasi-
ble in small countries than in larger ones due to the small
population size. On the other hand, small countries lack
the capacity to conduct local burden of diseases stud-
ies. Therefore, the estimated DALYs obtained from the
GBD study is a useful metric that helps policy-makers to
identify the impact of a disease, such as diabetes, on their
country. Additionally, policy-makers can make use of
such administrative data collection systems when imple-
menting plans to assist with their decisions. It is, there-
fore, important that such resource metrics are brought to
the attention of policy-makers while setting agendas for
health policies and strategic action plans.
Another key challenge that small countries face is the
inability to monitor and evaluate community diabe-
tes public awareness while building up the capacity to
measure the health outcomes following interventions
[33]. Provided that the right tools and data are estab-
lished, small countries are in a better position to imple-
ment interventions and monitor their outcomes due to
their small population size. Awareness of diabetes and
its associated risk factors is not an adequate stand-alone
strategy; rather, it needs to be incorporated into multi-
sectorial interventions that also consider the environ-
ment, social status and cultural setting of the population
Page 8 of 10Cuschieri et al. Health Res Policy Sys (2021) 19:43
[42]. Therefore, it is of immense importance that policy-
makers work with various stakeholders, including local
researchers, to collectively map the country-specific bur-
den of diabetes and set the agenda for population-specific
action plans.
Study limitations
The focus was on diabetes management among small
countries as associated with health policy and strategic
action. This article is based on research literature freely
available in online databases as well as on Ministry of
Health and other releavent websites and data provided
from the appropriate bodies in each of the countries.
Ongoing or unpublished studies have, therefore, not
been included. As such, the value of this work is limited
in these countries (n = 5) and on their characteristics of
setting health policies and implementing management
practices on diabetes. This limitation may prevent the
translation of the relevance or value of the current find-
ings on strategic planning and health policy on health
promotion and disease prevention for diabetes to the
remainder of the excluded countries (n = 6) from the
European countries of the WHO Small Countries Initia-
tive (n = 11). Additionally, further research on address-
ing these differences could, therefore, bring more clarity
on the importance of the context, with emphasis on fac-
tors and performance indicators of small countries in the
European region.
We acknowledge that the article is based on the five
small countries in Europe and that the generalizability of
the findings to other smaller European or other countries
may not be appropriate. Further research is merited to
examine the transfer of knowledge across different small
countries. Although the article is based solely on these
five small European countries, we cannot draw any con-
clusions on differences in the country healthcare system
and structure. A potentially useful model in future stud-
ies might be the Pandemic Risk Exposure Measurement
(PREM) to identify factors that are associated with demo-
graphic characteristics, measures of a country’s activities
and economic and social susceptibilities [43]. For exam-
ple, we can identify such complex variables to map the
impact of diabetes management against the response,
policies and strategies that a country can apply during a
pandemic situation, such as Covid-19.
Study strengths
To our knowledge, this is the first study that has focussed
on mapping the health policy and strategy on diabe-
tes management in five small countries in Europe. The
importance of this work is that it lays the foundation
for a future comparative study between smaller and
medium-sized or larger European states, and for setting
an agenda relevant to them. By collecting and analysing
epidemiological, burden of disease and strategy plans we
have provided a comprehensive analysis of the health pol-
icy landscape related to diabetes. Our results point out
the similarities and differences between these countries
and subsequently set up an evidence-based agenda for a
health-policy framework. Additionally, this study brings
together evidence from multiple national sources, high-
lighting gaps in the process of health policy and strategic
action. These can, in turn, be used by policy-makers in
each of the countries to inform their existing processes
and current practices on diabetes management.
Conclusions
The diabetes epidemic affects every nation including
small countries in Europe. We identified policy docu-
ments, strategies and action plans as well as mapped the
diabetes situation and the resources for Cyprus, Iceland,
Luxembourg, Malta and Montenegro. Despite their small
geographical size, we observed distinct challenges faced
by these small countries as related to their diabetes epi-
demiology, burden of disease and diabetes registers and
national plans. Iceland and Luxembourg have the lowest
prevalence among the five member states, and the low-
est burden from premature deaths, despite being the
only two member states that have no official national
register and no national plan for diabetes. While Malta,
Montenegro and Cyprus provide a free holistic care plan
to patients diagnosed with diabetes, they also have the
highest disease burden from premature mortality. These
findings may also (a) justify the need to perform health
examination surveys for better monitoring and evalua-
tion, (b) acknowledge gaps in the prevention aspects and
set-up of appropriate health population priorities and (c)
identify lack of coherent management approaches within
the health system to support the population they serve.
The key to mapping the burden of diabetes depends on
up-to-date evidence-based data, appropriate infrastruc-
ture and healthcare frameworks supported by the gov-
ernance and multisectoral stakeholders. Such an agenda
can enable the implementation of targeted health policies
and strategic action plans to reduce the burden of diabe-
tes at the population level.
Abbreviations
DALYs: Disability-adjusted life years; GBD: Global Burden of Disease; IDF: Inter-
national Diabetes Federation; IHME: Institute for Health Metrics and Evaluation;
NCDs: Noncommunicable diseases; WHO: World Health Organization; YLDs:
Years lived with disability; YLLs: Years of life lost.
Acknowledgements
The authors would like to thank Dr. Olga Kalakouta, First Health Officer at the
Ministry of Health and Dr. Myrto Azina Chronides, Senior Medical Officer at the
Page 9 of 10Cuschieri et al. Health Res Policy Sys (2021) 19:43
Ministry of Health and President of the National Diabetes Committee for the
provision of data for Cyprus.
Authors’ contributions
SC designed the study protocol. SC and EP have shaped the manuscript. The
other authors provided information and references to their specific countries’
data on diabetes. All authors have approved of the manuscript prior to
submission.
Funding
No funding was required.
Availability of data and materials
All data used are provided within the manuscript.
Ethics approval and consent to participate
Not applicable.
Concept for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Author details
1 Department of Anatomy, Faculty of Medicine and Surgery, University
of Malta, Msida, Malta. 2 MRC Clinical Trials and Methodology Unit, Univer-
sity College London, London, UK. 3 Center for Health System Development,
Institute of Public Health of Montenegro, Podgorica, Montenegro. 4 Service
épidémiologie et statistique, Direction de la Santé, Luxembourg, Luxembourg.
5 School of Health Science, University of Akureyri, Sólborg, Iceland. 6 Akureyri
Hospital, Akureyri, Iceland.
Received: 13 October 2020 Accepted: 23 November 2020
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- Mapping the burden of diabetes in five small countries in Europe and setting the agenda for health policy and strategic action
- Abstract
- Background:
- Methods:
- Results:
- Conclusions:
- Key messages
- Introduction
- Methods
- Methodology rationale
- Data sources
- Data analysis
- Results
- Epidemiology of diabetes and other related metabolic abnormalities
- Diabetes register and national plans
- Cyprus
- Iceland
- Luxembourg
- Malta
- Montenegro
- Burden of diabetes
- Discussion
- Monitoring and evaluation
- Prevention: management plans and execution
- Health system performance
- Implications and recommendations
- Study limitations
- Study strengths
- Conclusions
- Acknowledgements
- References
RESEARCH Open Access
Application of machine learning models in
predicting length of stay among healthcare
workers in underserved communities in
South Africa
Sangiwe Moyo1,3* , Tuan Nguyen Doan1,2, Jessica Ann Yun3 and Ndumiso Tshuma3
Abstract
Background: Human resource planning in healthcare can employ machine learning to effectively predict length of
stay of recruited health workers who are stationed in rural areas. While prior studies have identified a number of
demographic factors related to general health practitioners’ decision to stay in public health practice, recruitment
agencies have no validated methods to predict how long these health workers will commit to their placement.
We aim to use machine learning methods to predict health professional’s length of practice in the rural public
healthcare sector based on their demographic information.
Methods: Recruitment and retention data from Africa Health Placements was used to develop machine-learning
models to predict health workers’ length of practice. A cross-validation technique was used to validate the models, and
to evaluate which model performs better, based on their respective aggregated error rates of prediction. Length
of stay was categorized into four groups for classification (less than 1 year, less than 2 years, less than 3 years, and
more than 3 years). R, a statistical computing language, was used to train three machine learning models and
apply 10-fold cross validation techniques in order to attain evaluative statistics.
Results: The three models attain almost identical results, with negligible difference in accuracy. The “best”-
performing model (Multinomial logistic classifier) achieved a 47.34% [SD 1.63] classification accuracy while the
decision tree model achieved an almost comparable 45.82% [SD 1.69]. The three models achieved an average
AUC of approximately 0.66 suggesting sufficient predictive signal at the four categorical variables selected.
Conclusions: Machine-learning models give us a demonstrably effective tool to predict the recruited health
workers’ length of practice. These models can be adapted in future studies to incorporate other information
beside demographic details such as information about placement location and income. Beyond the scope of
predicting length of practice, this modelling technique will also allow strategic planning and optimization of
public healthcare recruitment.
Keywords: Machine learning, Artificial intelligence, Health workers, Modeling, Staff retention
* Correspondence: [email protected]
1Africa Health Placements, Rosebank, Johannesburg, South Africa
3The Best Health Solutions, 107 Louis Botha Avenue, Orange Grove,
Norwood, P.O. Box 92666, Johannesburg, South Africa
Full list of author information is available at the end of the article
© The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and
reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver
(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Moyo et al. Human Resources for Health (2018) 16:68
https://doi.org/10.1186/s12960-018-0329-1
Introduction
The lack of health workforce is a global crisis which
numerous countries have proposed and implemented
intervention plans [1, 2]. However, there is limited data
regarding the impact of these interventions and their
sustainability over a long period of time. Research shows
that the loss of healthcare workers in African countries
(such as South Africa and Ghana) cripples the pre-exist-
ing delicate health system [3, 4]. Hence, the retention of
health workers is essential for the healthcare system per-
formance. These studies also point out that the recruit-
ment of health workers should not only focus on nurses
and physicians, but also on community health workers
(CHWs) to help the primary healthcare systems boost
the coverage and address the basic health needs of soci-
eties [4].
Specifically, healthcare systems in sub-Saharan Africa
(SSA) face a serious human resource crisis, with recent
estimates pointing to a shortfall of more than half a
million nurses and midwives needed to meet the
Millennium Development Goals of improving the
health and wellbeing of the SSA population by 2015 [5].
One of the reasons for this phenomenon is due to
human capital flight (“brain drain”) in the health
profession, especially in the public sector [1, 6]. Migra-
tion of health workers from low- and middle-income
countries (LMICs) to high-income countries is a con-
troversial aspect of globalization, having attracted con-
siderable attention in health policy discourse at both
the technical and political levels [1, 7–9]. The migra-
tion of skilled healthcare workforce translates into a
direct loss of considerable resources to the public
sector of LMICs, as direct benefits only accrue to coun-
tries, which have not invested in educating young
professionals. To make matters worse, in many sub-Sa-
haran countries such as Sierra Leone and South Africa,
there are limited alternatives for the population to seek
healthcare services from the private sector or next
health facility due to inaccessible distance or cost factor
[10].
To maintain a functional health system, most coun-
tries have altered their retirement age in order to
extend the working life of their staffs. Furthermore,
Botswana and South Africa have recruited from other
countries within and outside the continent [7]. Despite
various local and international frameworks, the effect-
iveness of these interventions is yet to be seen [7, 8].
Another challenge lies in the monitoring and evalu-
ation of these frameworks. Recent cross-sectional
reviews of currently available healthcare workforce
database show that in most cases, the systems are
fragmented, unreliable, and cannot be integrated at
both national and international levels, and that in
order for policy-makers to make data-driven decisions,
better database management systems still need to be
developed [1, 2, 8].
A high turnover rate in the health workforce is another
concern as it is costly and detrimental to organizational
performance and quality of care. Healthcare organizations
with high attrition rate not only face issues with the qual-
ity, consistency and stability of services provided to people
in need, but also issues regarding the working conditions
of the remaining staffs such as increased workloads,
disrupted team cohesion and decreased morale [11, 12].
Some studies have focused on the influence of individ-
ual and organizational factors on an employee’s intention
to leave [13]. A World Health Organization (WHO)
study of four African countries shows that the major
reasons behind health worker migration are better sal-
ary, safer environment, living conditions, lack of facil-
ities, lack of promotion, and heavy workloads [8]. Other
studies conclude that better compensation package with
good work-life balance is the primary reason to migrate
[6, 14, 15]. On the other hand, one of the obstacles to
migration is language barrier, which lies at the basis of
patient care [16, 17]. Patients express their distress by
describing their symptoms and pain and report changes
in health status to professionals. Nurses or doctors need
the current and technical language fluency to communi-
cate under stress and duress with one another, members
of the teams, and patient families [6].
Another healthcare policy concern is the misdistribution
of healthcare workforce between urban and rural areas. It
prevents equitable access to health services, contributes to
increased health-care costs and underutilization of health
professional skills in urban areas, and remains a barrier to
universal health coverage [6].
Overall, the human capital flight of local health pro-
fessionals, the high turnover rate, and the shortage of
workers in the public sector of South Africa thus
demands further investment in attracting and retain-
ing foreign healthcare staffs that stay for an extended
period of time. The WHO has also issued global rec-
ommendations to improve the rural recruitment and
retention of the health workforce [18]. This is pivotal
to the delivery of healthcare in rural and remote areas
of South Africa. A study has shown that 84% of South
African population uses public healthcare, served by
only 30% of the trained and certified doctors [19].
Generally, sub-Saharan Africa faces severe lack of
healthcare workers, with only 3% of the world’s total
medical staff while facing 24% of the global burden of
disease [8]. The arrival of foreign medical workforce
and their placement in the public health sector
reduces the two-front misdistribution of physicians,
alleviates the lack of human resources in public rural
facilities, and improves access to healthcare to people
in rural areas [8].
Moyo et al. Human Resources for Health (2018) 16:68 Page 2 of 9
To date, greater efforts have focused on recruitment,
with significantly less attention to workforce retention.
As aforementioned, a challenge to improve health access
in rural areas is to maintain high retention rate of the
medical workforce. Currently, there are few empirical
studies regarding the factors that influence the length of
practice [14, 17]. Previous attempts to identify these fac-
tors mainly focus on worker satisfaction at medical facil-
ities and retention strategy of staffing agencies [17].
There are some recent research into the correlation be-
tween employee demographic information and the suc-
cess of retention effort in public health facilities [14].
This paper aims to develop a predicting tool for the
length of practice of foreign healthcare workers, given
their demographic information. Machine learning
methods are well-suited for this challenge. Rather than
traditionally considering the effect of demographic vari-
ables on the length of practice one after another, machine
learning method examines all potential predictors simul-
taneously in an unbiased manner, and identifies pattern of
information that are useful to make prediction.
Methods
Study design
A quantitative retrospective cohort study was conducted
using secondary data, collected from the Africa Health
Placements (AHP).
Study setting
South Africa Health, healthcare worker population in
underserved communities and distribution and retention
levels. AHP recruits foreign and locally qualified health
professionals to be placed in underserved communities
in South Africa. Underserved areas like rural areas often
face challenges in recruiting and retaining health
workers, government has responded with programmes
like compulsory community service and rural allowance
to address this challenge.
Data acquisition
Longitudinal individual health worker records are main-
tained at AHP. These health workers included profes-
sionals from South Africa and the rest of the world
seeking employment in underserved facilities in South
Africa. Data was collected using two methods (i) cus-
tomized online portal completed by healthcare workers
(HCW) and (ii) interviews by recruitment officers
through email, Skype, and telephonic conversations.
Data were captured onto a database and customer man-
agement system called Docwize. The online portal is
available at the AHP website as a contact form. Once
registered, the HCW receives login details to complete
their application on Docwize. This system allows them
to input personal and professional information, upload
certificates, which would then be verified with the re-
spective regulatory authorities, and be informed about
the next steps until they secured a job offer. The HCW
have an option of completing the application online or
supplying the details to the recruitment officers who
then update the system. It takes an average of 18 months
to complete the recruitment process, 75% of the HCW
were discouraged by the regulatory delays resulting in
incomplete data. The length of stay was continuously
monitored during their employment contract. Emails
and telephonic contact are used to establish their last
date of employment at a particular facility.
Statistical analysis
Dataset description and manipulation
We took a complete cases approach, using only data
from successfully recruited health workers without
missing observations. The Africa Health Placements
dataset contains 62 variables and 13 698 entries, in
which there were 2079 successfully recruited practi-
tioners. Among these 2079 professionals, some chose
not to provide personal information such as marital sta-
tus or gender. After data cleaning, there were 1838
entries with completed fields to meet the requirements
of this study.
The variables that are used to develop our machine
learning models are chosen based on their availability in
the AHP data system. They are nationality, profession,
relationship, and gender. Since there are a lot of missing
values in our age variable dataset, a complete case ap-
proach with age could have further reduced the dataset
to merely 914 entries and undermine the ability of the
model to learn from existing data. Hence, we excluded it
from the final analysis. Notably, all of our four predictors
are categorical variables. A challenge with having cat-
egorical variables in machine learning is that to fully rep-
resent each variable, we have to use a large number of
dummy variables to represent each level within the vari-
able. For example, since our data had records from 145
countries, we needed 144 dummy variables to represent
all existing countries. This method would result in a very
sparse dataset and usually not useful in predictive mod-
elling. Hence, we transcribed each variable as follows:
Nationality: categorical data of 145 different countries.
Instead of recording nationality as it is, the nationality
variable is transcribed based on World Bank’s classification
of countries into 4 categories: low income, lower middle
income, upper middle income, and high income.
Professions: categorical data of 22 different registered
professions, recorded into 3 different categories: doctor,
nurse, and other
Gender: categorical data of 2 levels: male and female
Moyo et al. Human Resources for Health (2018) 16:68 Page 3 of 9
Relationship status: categorical data of 3 levels: married,
single, or other.
Machine learning model development
With a large recruitment and retention dataset from
AHP, we built three machine learning predictive models
using relevant demographic data. We evaluated the
models’ performance by doing 10-fold cross-validation.
The aim was to choose a model that performs signifi-
cantly better in predicting length of practice.
As shown on Table 1, three different machine learning
classification models (multinomial logistic regression,
decision tree, and Naive Bayes Classification) were used
to train the dataset. The issue was approached as a
classification, rather than a regression problem, as we
aimed to classify a successful recruit into one of the four
mutually exclusive groups (less than 1 year, less than 2
years, less than 3 years, and more than 3 years). The use
of a regression method is not optimal in this case, due
to (i) the lack of quantitative numerical variables in our
demographic information, (ii) the wide range of value of
the dependent variables (length of practice measured in
days), and (iii) the non-continuous nature of the
dependent variables. A regression method would require
a much larger dataset to arrive at a model of relatively
acceptable fit. With our current available dataset, the
experimental fit is approximately 18% with high internal
sum of squares. Moreover, in strategic workforce plan-
ning, a precise prediction of the length of practice in
days (or months) is generally not expected. A prediction
of whether a specific healthcare worker will stay for 1
year, 2 years, or longer is usually acceptable for most
intents and purposes.
Cross-validation
To decide which of the three models perform best, we
have to see their ability to generalize and predict new,
unseen data. A challenge to our research was the lack of
test data which we could have used for model evalu-
ation. Conventionally splitting our existing data into a
80/20 ratio—80% of the data for training and 20% for
testing—was an option, but not optimal as we wanted to
use all data available for training.
We examined our three models with a technique
called 10-fold cross-validation. Ten-fold cross-validation
works as follows: we randomly partition the original
dataset into 10 disjoint subsets, use nine of those subsets
in the training process, make predictions about the
remaining subset, and record the misclassification error.
To avoid opportune data splits, we average misclassifica-
tion error across the 10 folds. A comparison between
the average misclassification errors of the three machine
learning models allowed us to decide which model per-
forms best on unseen data.
Results
Three machine learning models were trained, and a
10-fold cross validation technique was used to attain
evaluative statistics. The three models attain almost identi-
cal results, with negligible difference in accuracy. The
“best”-performing model (multinomial logistic classifier)
achieves a 47.34% [SD 1.63] while the decision tree model
achieves an almost comparable 45.82% [SD 1.69]
(Table 1).
Multiclass area under the curve (AUC) was computed
by building multiple receiver operating characteristic
(ROC) curves (one class versus another) and taking the
average, as defined by Hand and Till [20]. The three
models achieve an average AUC of 0.66 (multinomial lo-
gistic at 0.6652, decision tree 0.6635, Naive Bayes
0.6602), suggesting sufficient predictive signal at the four
selected categorical variables.
Overall, the three models had significant accuracy
in classifying the length of stay of healthcare workers
(p value < 2.2e−16) (Table 1). Additionally, Kappa
statistics was also computed, in order to measure
how much better each of the classifiers is performing
over the performance of a classifier that simply
guesses at random according to the frequency of each
class [21]. The Cohen’s Kappa statistics of the multi-
nomial logistics, decision tree, and Naive Bayes are
0.2658, 0.2649, and 0.2521 respectively, suggesting a
Table 1 Machine learning results
Techniques
Multinomial logistic Decision tree Naive Bayes
Accuracy 47.34% [1.63] 45.82% [1.69] 47.01% [1.62]
95% CI (46.22, 50.84) (46.66, 51.28) (45.19, 49.81)
AUC 0.6652 0.6635 0.6602
No information rate [NIR] 0.376 0.376 0.376
P value [Acc > NIR] < 2.2e−16 < 2.2e−16 < 2.2e−16
Cohen’s Kappa 0.2658 0.2649 0.2521
Moyo et al. Human Resources for Health (2018) 16:68 Page 4 of 9
fair (but not substantial) agreement between predic-
tion and response adjusted by the amount of agree-
ment expected by chance.
All three models perform reasonably well at identifying
those who are likely to stay for less than 1 year (Table 2).
The sensitivity of this class was greater than 75% for all
three models, showing that they correctly identify more
than ¾ of those who are likely to stay less than 1 year.
Specificity of this class is not particularly high (all lower
than 65%), so all three models do not do as well in iden-
tifying those who are staying for more than 1 year. How-
ever, with a negative positive rate as high as 84% across
the three techniques, it means that when the model
negatively classifies a person out of those who stay for
less than 1 year, such classification is likely to be correct.
In contrast, all three models perform poorly at identi-
fying those who are staying between 2 and 3 years
(Table 2). With sensitivity at as low as 0% (decision tree)
and specificity up to 100%, the three models must have
learned to negatively assign a majority (all in decision
tree case) out of this class. This is likely the result of
imbalanced data sample with too little sample data of
this class (Fig. 1).
Comprehensive data analysis
In general, more males (997, 54%) than females (861,
46%) were recruited (Table 3). Males stay on average
187.78 days more than females do. South Africa has
supplied the greatest number of health workers (381,
41%), followed by the United Kingdom (361, 39%),
Nigeria (106, 11%), and Netherlands (86, 9%) (Table 3).
Doctors (1538, 83%) were the most recruited health
workers and then nurses (107, 6%) and other profes-
sionals (193, 10%). With regard to relationship status,
single healthcare workers constituted 61% of the
recruited, 31% were married, and 8% were cohabiting
(Table 3, Figs. 1, 2, and 3).
Figure 4 shows two world heat maps that represent (a)
the number of successful recruits from each country and
(b) the average length of practice among those in these
countries. The two maps point to an observation: AHP
as a health placement organization is not very successful
in recruiting from some countries, e.g. Russia, but once
we do, the recruits tend to stay for an extended period
of time. However, the sample size casts some doubts on
this observation. Some countries have very high average
length of stay, simply because we have a very small sam-
ple size of them.
Discussion
This research shows that a majority of foreign qualified
healthcare workers (1497 out of 1838, 81%) stay at their
placement facilities for less than 3 years. While a con-
stant rate of foreign recruitment per year can “fill the
gap” in paper, the low average length of practice signifies
a hidden cost of recruiting, relocating, and training of
new healthcare professionals. Effective workforce plan-
ning from government or non-profit organizations, thus,
requires a tool to predict the length of practice of in-
coming health professionals.
Table 2 Predictions of length of stay across the three models
Less than 1 year Less than 2 years Less than 3 years More than 3 years
Multinomial logistic techniques
Sensitivity 0.7685 0.3248 0.0369 0.5425
Specificity 0.6548 0.8503 0.9766 0.7896
Positive predictive value 0.5728 0.4533 0.2340 0.3700
Negative predictive value 0.8244 0.7673 0.8398 0.8834
Balanced accuracy 0.7166 0.5876 0.5068 0.6661
Decision tree techniques
Sensitivity 0.7858 0.3740 0.000 0.4897
Specificity 0.6469 0.8075 1.000 0.8150
Positive predictive value 0.5728 0.4260 NaN 0.3761
Negative predictive value 0.8337 0.7716 0.8379 0.8751
Balanced accuracy 0.7164 0.5908 0.5000 0.6524
Naive Bayes techniques
Sensitivity 0.7728 0.2658 0.0403 0.5630
Specificity 0.6391 0.8752 0.9760 0.7675
Positive predictive value 0.5633 0.4485 0.2449 0.3556
Negative predictive value 0.8236 0.7573 0.8401 0.8852
Balanced accuracy 0.7059 0.5704 0.5081 0.6653
Moyo et al. Human Resources for Health (2018) 16:68 Page 5 of 9
Fig. 1 Number of subjects categorized by (from left to right, up to down) length of practice, professions, relationships, and countries
Table 3 Length of stay by gender, nationality, profession, and relationship status
Mean length of stay (days) Standard deviation (sd) Sample (n) Percentage (%)
Gender
Female 603.48 499.0 861 46
Male 791.26 630.9 997 54
Total 1 838 100
Nationality (top 4)
South Africa 548.65 388.1 381 41
United Kingdom 475.11 373.3 361 39
Nigeria 1 096.09 719.7 106 11
Netherlands 753.36 532.7 86 9
Registered profession
Doctor 714.58 588.4 1 538 83
Nurse 575.38 498.2 107 6
Other supporting staff 684.31 550.9 193 10
Total 1 838 100
Relationship status
Single 625.22 530.64 1 114 61
Married 868.46 659.26 574 31
Other 651.12 651.12 150 8
Total 1 838 100
Moyo et al. Human Resources for Health (2018) 16:68 Page 6 of 9
The three models attain significantly above chance
results, with the average AUC of approximately 0.66 (multi-
nomial logistic at 0.6652, decision tree at 0.6635, Naive
Bayes at 0.6602), suggesting sufficient predictive signal at
the four categorical variables selected. This is an indication
that applying and retraining machine learning models with
available datasets, Human Resource for Health decision
makers can effectively source healthcare workers who are
most likely to stay the longest in underserved communities.
Machine learning must be applied together with other
qualitative methods like exit interviews so as to give an
in-depth understanding of the healthcare worker per-
ceptions and experiences that relate to their length of
stay. A mixed method would have generated a better
Fig. 2 Length of stay as function of relationship, colour by gender and grid by income group
Fig. 3 Decision tree on income, gender and profession
Moyo et al. Human Resources for Health (2018) 16:68 Page 7 of 9
understanding of why certain gender, countries, age,
and experience tend to stay longer than others.
Limitations of the study
Incomplete fields in the data were another issue as many
candidates were excluded from the study due to missing
information. We could not obtain age as one of the pre-
dictors, although we recognized that it could potentially
influence health worker long-term plan to stay. Our
issue with incomplete data relates directly to the inef-
fective database system issue that is common among the
public sector in South Africa [1, 2, 8]. Although in the
short run, installing and enabling a more effective
database system imposes a cost challenge to healthcare
non-profits and public sector, such system is likely to
make tremendous impacts as the machine learning
models can be further improved by learning from a lar-
ger, high-quality dataset. In the meantime, there is a po-
tential for the public sectors and NGOs to collaborate
and involve in data sharing that could empower the
training process of machine learning algorithms.
Conclusions
Machine learning models give us an effective tool to pre-
dict the recruited health workers’ length of practice. These
models can be adapted beyond the scope of demographic
Fig. 4 Map showing world distribution of a number of candidates sourced from each country and b average length of practice by these
candidates from each respective country
Moyo et al. Human Resources for Health (2018) 16:68 Page 8 of 9
information (i.e. information about placement location, in-
come), allowing strategic planning and optimization of
public healthcare recruitment.
Abbreviations
AUC: Area under the curve; HCW: Healthcare workers; LMIC: Low- and middle-
income countries; NGO: Non-governmental organization; ROC: Receiver operating
characteristic; SSA: Sub-Saharan Africa; WHO: World Health Organization
Acknowledgements
The authors would like to thank the African Health Placement for providing
the dataset used in the study.
Funding
This research received no specific grant from any funding agency in the
public, commercial, or not-for-profit sectors.
Availability of data and materials
The dataset supporting the conclusions of this manuscript is available with
the corresponding author and will be made available in an anonymized
version on reasonable request.
Authors’ contributions
All authors contributed toward conceptualization, data analysis, drafting, and
critically revising the paper and agree to be accountable for all aspects of
the work. All authors also read and approved the final manuscript.
Ethics approval and consent to participate
Permission to conduct the study was obtained from Africa Health Placements.
The researchers followed the highest standards to protect confidentiality and
anonymity of subject data. All identifying information of individual subjects
such as name, address and date of birth were removed from the dataset prior
to the study.
Competing interests
The authors declare that they have no competing interests.
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published
maps and institutional affiliations.
Author details
1Africa Health Placements, Rosebank, Johannesburg, South Africa. 2Yale
University, New Haven, CT, United States of America. 3The Best Health
Solutions, 107 Louis Botha Avenue, Orange Grove, Norwood, P.O. Box 92666,
Johannesburg, South Africa.
Received: 15 December 2017 Accepted: 30 October 2018
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Moyo et al. Human Resources for Health (2018) 16:68 Page 9 of 9
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- Abstract
- Background
- Methods
- Results
- Conclusions
- Introduction
- Methods
- Study design
- Study setting
- Data acquisition
- Statistical analysis
- Dataset description and manipulation
- Machine learning model development
- Cross-validation
- Results
- Comprehensive data analysis
- Discussion
- Limitations of the study
- Conclusions
- Abbreviations
- Acknowledgements
- Funding
- Availability of data and materials
- Authors’ contributions
- Ethics approval and consent to participate
- Competing interests
- Publisher’s Note
- Author details
- References

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