MILITARY MEDICINE, 185, S2:28, 2020

Implementation of a Multicomponent Fall Prevention Program:
Contracting With Patients for Fall Safety

CPT Arrah L. Bargmann, BSN, RN* ; Maj Stacey M. Brundrett, MSN, RN, AGCNS-BC*

ABSTRACT
INTRODUCTION
Falls during hospitalizations can increase the length and cost of a hospital stay. Review of patient safety reports on a
26-bed medical-surgical telemetry unit revealed that the number of falls went from 6 in 2015 to 12 in 2016. The reports
identified a knowledge gap in the patient population and nursing staff related to high fall risk interventions. A literature
review suggests that patient-staff safety agreements, in combination with proper implementation of Clinical Practice
Guidelines, can successfully increase education and adherence to fall prevention measures and reduce the number of
inpatient falls.

MATERIALS AND METHODS
The objective of this evidence-based practice project was to determine if the implementation of a patient fall safety
agreement in combination with an existing evidence-based fall prevention bundle reduces the number of falls. Based
on the literature review, the unit developed a multicomponent fall prevention program that emphasizes staff and patient
education. The program consists of (1) assessment of the patient’s fall risk using the Johns Hopkins Fall Assessment Tool,
(2) daily patient education on factors contributing to the patient’s fall risk during the shift assessment, (3) an educational
handout on fall risk factors maintained at the bedside, (4) ensuring compliance with implementation of previously existing
fall prevention measures, and (5) a patient fall safety agreement.

RESULTS
During the first 4 months, the fall rate decreased by 55% and staff compliance with interventions for high fall risk
patients increased to 89%. To achieve added compliance, the unit implemented an incentive program, which resulted in
the increased adherence to the fall risk interventions. The unit experienced 87 and 88 consecutive fall-free days, which
was the longest consecutive days since May 2015. This project has reached sustainment and the unit continues to see a
low fall rate, well below the national average for medical-surgical units.

CONCLUSION
One of the largest obstacles to this project was staff and leadership turnover. However, the project found that patient fall
safety agreements facilitate a dialogue among staff and patients as well as encourage patients to take ownership of their
own care. They improve the safety of patients and create a collaborative environment for nurses to conduct safe, quality
patient care.

INTRODUCTION
Falls during hospitalizations are a safety concern, resulting in
added healthcare costs, increased length of stay, and increased
disability rates to name a few. According to the Agency

*Brooke Army Medical Center, 3551 Roger Brooke Dr, JBSA-Fort Sam
Houston, TX 78234

Poster presentations at Tri-Service Nursing Research Program Evidence
Based Practice and Research Dissemination Course in 2017, the San Antonio
Military Health System and University Research Forum in 2017, and a
podium presentation at National Association of Clinical Nurse Specialists
Annual Meeting in 2018.

The views expressed herein are those of the authors and do not reflect
the official policy or position of Brooke Army Medical Center, the US
Army Medical Department, the US Army Office of the Surgeon General, the
Department of the Air Force, the Department of the Army or the Department
of Defense or the US Government.

doi:10.1093/milmed/usz411
Published by Oxford University Press on behalf of the Association of

Military Surgeons of the United States 2020. This work is written by (a) US
Government employee(s) and is in the public domain in the US.

for Healthcare Research and Quality, falls are one of the
most often reported incidences during hospitalizations.1 Since
2008, hospitals no longer receive reimbursement for traumatic
injuries following falls that occur during a hospital stay.1

Furthermore, Oliver et al. found in their literature review that
falls “are also associated with increased length of stay, higher
rates of discharge to institutional care, and greater amounts of
health resource use.”2 Therefore, falls sustained in the acute
hospital setting remain a priority for any facility.

This project was conducted on a 26-bed medical-surgical
telemetry unit at a 352-bed Level 1 military trauma center
that cares for both civilian traumas and military beneficiaries.
At the facility, policy defines a fall as “a sudden, unintended
uncontrolled downward displacement of a patient’s body to
the ground or other object. This includes situations where a
patient falls while being assisted by another person.”3 Despite
the Clinical Practice Guidelines already in place, retrospective
reviews of the patient safety reporting (PSR) system and
fall response team data within the facility indicated that the

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number of falls on the unit doubled in a year. According to
the facility definition, the number of falls increased from 6
in 2015 (a fall rate of 0.83 per 1,000 patient days) to 12 in
2016 (a fall rate of 1.59 per 1,000 patient days). Although
this rate is less than the national average of 3.92 falls per
1,000 patient days for medical-surgical units,4 the increase in
falls was concerning to both leadership and staff nurses. Of
these falls, approximately 42% (5 of 12) of them resulted in
mild harm. The American Society for Healthcare Risk Man-
agement defines mild harm as “minimal symptoms or loss of
function, or injury limited to additional treatment, monitoring,
and/or increased length of stay.”5 Thus, the fall was associated
with additional cost to the facility and/or caused decline in the
patient’s status.

After further review, the unit practice council (UPC) along
with the unit’s clinical nurse specialist (CNS) discovered
location and circumstances of the falls varied. Four of the
falls occurred in the bathroom and the others occurred during
ambulation or patient changing positions, i.e., reaching for
items or trying to transfer self from bed to chair. Despite
the differences in location and cause of the fall, similarities
among the falls became evident: (1) not all the fall preven-
tion measures were implemented and (2) the patient lacked
understanding of their fall risk and corresponding prevention
measures. It was also noted that at the time, the only edu-
cational guidance provided to patients was in the form of
a brief trifold handout for patients to reference. Therefore,
there were areas for improvement within the fall prevention
program on the unit. This article describes the development,
implementation, outcomes, and challenges of implementing
an enhanced evidence-based fall prevention safety program on
a medical-surgical unit. This project falls under the category
of an evidence-based practice (EBP) project because it inte-
grates clinical expertise with a systematic analysis of current
evidence to guide practice change on the unit to positively
impact patient care.6

METHODS
The Iowa Model7 served as the framework of the EBP project.
Following the Iowa Model’s outline, a review of PSRs, injury
reports, and feedback from nursing staff, floor management,
and the unit’s CNS identified falls as the trigger issue for
the unit. Due to the significant increase in the number of
falls, reducing falls was determined to be a priority for unit
leadership. Then, a team was formed that included the CNS
and members of the UPC. A literature review was conducted
guided by the clinical question: On a medical-surgical unit,
does the implementation of a patient fall safety agreement
in combination with current Clinical Practice Guidelines
for fall prevention reduce the number of falls? The terms
“falls,” “patient education,” “patient safety,” “prevention,”
and “agreement” drove a search in Cumulative Index to
Nursing and Allied Health Literature (CINAHL) and Ovid
MEDLINE databases. The goal was to discover if there

were any additional interventions the unit was not currently
implementing that could affect the unit’s fall rate.

Most of the literature discussed the use of bundled fall
prevention programs suggesting that there is no one inter-
vention that significantly reduces falls in the acute inpatient
setting. For instance, one systematic review, consisting of four
meta-analyses and 19 studies, suggested that multifactorial
fall programs can reduce fall rates in the inpatient population
by up to 30%; however, the optimal bundle of interventions
could not be identified from the systematic review.8 Typical
interventions for fall prevention include fall risk assessment,
yellow wrist bands, nonskid socks, and bed alarms.

In addition to fall prevention interventions, education and
a culture of safety are important for reducing falls. Leone
and Adams9 describe a quality improvement project to pre-
vent falls. Part of their intervention was changing their unit’s
culture of safety, which allowed staff to feel comfortable
reporting falls and unsafe conditions. Staff education is also
important when changing the culture on a unit as well as
implementing anything new; everyone must accomplish the
new process the same way as well as understanding the
purpose for the new process or intervention.

A safety agreement may improve patient education about
falls and adherence with fall interventions. According to one
research study, patient fall safety agreements provided struc-
tured fall education, which may lead to reduction in the degree
of injury following a fall.10 Additionally, Nicolas et al.11 saw
a reduction in their fall rate after implementing a patient fall
safety agreement with their patients and families. Finally, the
Joint Commission Center for Transforming Healthcare: Pre-
venting Falls Targeted Solutions Tool12 (TST) highlights the
importance of a customizable multifactorial approach to fall
prevention that includes the use of safety agreements. The TST
is an evidence-based tool that guides an organization through
a step-by-step process to address patient falls with the goal
of generating customizable solutions to address previously
identified barriers. It utilizes the rapid process improvement
methodology to measure fall rates and identify contributing
factors and implement targeted solutions. This methodology
is a “fact-based, systemic, and data-driven problem-solving
methodology” that includes elements from Lean Six Sigma
and change management methodologies.13 The TST from
the Joint Commission Center for Transforming Healthcare
supports the use of safety agreements to improve call light use,
patient awareness, and patient acknowledgement about their
fall risk during hospitalization. All five of the organizations
that initially participated in the pilot study experienced a 62%
decrease in falls with injury and 35% decrease in their fall
rate.14

Altogether the literature review revealed two common
themes. Regardless of intervention, increased education of
patients and nursing staff and a culture of safety were two
key factors in the reduction of fall rates in hospital settings.
Based on the findings from the literature review and PSR
data, the UPC enhanced the existing fall prevention program

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to emphasize patient education, improved communication,
and a culture of safety.

At all military facilities, policy outlines guidance related
to fall prevention, and it focuses on three components:
assessment using the Johns Hopkins Fall Assessment Tool
(JHFAT),15 nurse-initiated orders, and education of the patient
and family. The UPC reviewed the existing fall prevention
bundle, and updated it based on the above literature review.
The pre-project fall prevention bundle included five main
components: (1) assessment utilizing the JHFAT; (2) nurse-
initiated order sets; (3) patient and family education; (4) visual
cues such as falling star, falls wheel, and yellow socks; and
(5) other safety measures such as nonskid socks, gait belts,
and bed alarms. Nurse-initiated orders are a group of orders
in the electronic health record that serve as reminders and a
way to document interventions taken such as bed alarm on,
offering toileting, and remaining with the patient at all times
when they are out of bed for high fall risk patients.

The new fall bundle included the previously existing fall
prevention measures plus (1) daily patient education on factors
contributing to the patient’s fall risk during the shift assess-
ment; (2) a patient educational handout on fall risk factors at
the bedside, which included a modified JHFAT and key fall
safety education points; and (3) a patient fall safety agreement.
Modifications to the JHFAT included removing age and com-
bining all the mobility and cognitive items into one box to
simplify the form, thus easing communication of risk factors
for patients. The modification to the tool was agreed upon
by the UPC members under the guidance of the CNS; it was
simplified for patient understanding. The goal of the abridged
tool was to involve patients in the fall risk assessment. In each
shift, the patient was reassessed and received reinforcement
education of all the fall prevention measures associated with
the patient’s specified fall risk.

The adherence of this EBP bundle was measured by
determining the level of the patient’s fall risk understanding
and associated fall prevention interventions pre- and post-
patient fall safety agreement implementation. Additionally,
staff adherence with pre-existing fall prevention interventions
outlined in accordance with hospital policy pre- and post-
implementation was monitored via audits. In preparation for
the implementation of the bundle, the UPC collected baseline
fall data from the PSR system and created an in-service for
staff members, the patient fall safety agreement, an education
handout, an abbreviated JHFAT sheet, and ambulation status
for the white boards. The fall safety agreement included items
such as the patient has been educated on fall risk prevention
strategies and that they acknowledge falling can cause serious
injuries. Therefore, they agree to ask for help in order to
prevent falling.

Implementation of the bundle began in early February
2017 once 90% of the staff received face-to-face in-services,
which outlined the new bundle. The in-service addressed
baseline fall data collected from the PSR system and post-fall
response team reports, the purpose of the project, as well as

explanations and examples of the new forms. The forms
included the patient fall safety agreement, modified JHFAT,
fall prevention information handout, and new signs for the
patient rooms. Copies of the patient education handout, the
modified JHFAT, and fall prevention signs were laminated on
yellow paper and placed on the bedside table or on the white
board at the foot of every patient’s bed, within their line of
sight. Upon completion of the in-service, staff members were
encouraged to sign a pledge to promote a culture of safety and
utilize the tools of the fall prevention bundle.

During the in-services, which occurred during shift change
safety huddles, the staff were instructed to ensure all patients
received the fall prevention education and had a documented
JHFAT and a signed patient fall safety agreement upon admis-
sion or transfer to the unit. Staff members were allowed up to
24 hours to have the bundle implemented if patients arrived
to the unit sleepy postoperatively or with altered mental sta-
tus. Nursing staff were also encouraged to educate family
members especially if the patient was not able to receive
the education upon arrival. Once patients received the fall
risk and prevention education, they were encouraged to sign
the agreement with the nursing staff. Then, the signed safety
agreement was placed in a separate binder that contained
all the patient fall safety agreements for the unit. Then, the
nursing team placed a star by the patient’s name on the charge
nurse census board to serve as a visual cue to the auditors,
nursing staff, and unit leaders that the patient received the
education and signed the agreement. The modified JHFAT was
to be updated by the nurse in the presence of the patient each
shift, hung in the room, and utilized as a communication tool
for nursing staff to see which risk factors contributed to the
patient’s fall risk.

RESULTS
UPC members and unit management conducted audits on
dayshift and nightshift at least three to five times per week to
observe adherence with the unit fall prevention bundle before,
during, and after the project. Pre-implementation auditors
checked to ensure all interventions were in place that corre-
sponded to the patient’s documented fall risk. After project
implementation, auditors were instructed to check the desig-
nated binder for a signed fall agreement as well as review
the patient’s charted fall risk as determined by the bedside
nurse using the JHFAT prior to beginning each audit. The
auditors would then ask the patient if they knew what their
fall risk was: low, moderate, or high. If the patient’s response
did not match the assessment, reeducation was immediately
given using the patient education handout on the patient’s
bedside table or whiteboard. Finally, the auditors would then
visually check rooms to ensure all interventions were in place
based on the patient’s identified fall risk. Inter-rater relia-
bility was not measured. However, for each intervention the
observation was either adherence or not. For instance, the bed
alarm was either on or off for a high-risk patient. Auditors

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received education on each item to examine prior to starting
the audit process. Unit Practice Council members collected
post-implementation surveys that patients received prior to
discharge and compared them to the visual and verbal audits
during the hospital stay. All data from the audits were recorded
on a spreadsheet and then compared to baseline data retro-
spectively from the PSR system and post-fall response team
reports.

The initial audit revealed only 5 (approximately 30%)
of 17 patients identified as high fall risk patients had bed
alarms on and there were 2 recent falls on the unit. Within
the first 2 weeks of implementing the fall bundle, the bed
alarm adherence increased to 71%. Hoping to achieve a bench-
mark of 90%, the UPC instituted an incentivized performance
improvement project known as “Catch ‘em Doing Good.” The
incentive was “Sunshine Fund” dollars, which staff could use
to purchase snacks from the unit’s snack bar. In each shift
the staff were audited on their adherence with all the fall
bundle interventions. Staff earned a star when 100% of the
nursing interventions were in place for all the patients on
their team, the fall safety agreement was signed, and all their
patients demonstrated understanding of their fall risk. With the
addition of the incentive program, adherence with bed alarms
and fall safety agreement rose to 89% after 3 months.

The incorporation of the fall bundle with the patient fall
safety agreement notably increased the percentage of patients
that correctly stated their fall risk and verbalized understand-
ing of what prevention measures correlated with their fall risk.
Implementation of the staff incentive program improved the
culture of safety on the unit and resulted in a profound increase
to 95% of patients correctly stating their fall risk suggesting a
positive correlation with understanding interventions and the
bundle, while seeing a negative correlation with falls. Since
the implementation of the project, the unit’s fall rate decreased
from 1.59 per 1,000 patient bed days for 2016 to 1.38 per
1,000 patient days for 2018 (see Fig. 1). The lowest fall rate
was seen during the second quarter of 2017, which was right
after implementation of the bundle; the fall rate was 0.54 per
1,000 bed days. Additionally, the unit has experienced two of
the longest stretches of fall-free days since May 2015, 87 and
88 days.

As a result of this project, the fall rate and the number
of falls with mild harm have remained low. The unit only
experienced no harm or mild harm events; none of the fall
events were classified as moderate or severe harm or death.
If the patient experiences a slight change in status or requires
limited additional treatment, then the event classifies as mild
harm. If the event resulted in an injury that impacts daily
functioning or quality of life to some degree, then it would
receive a classification of moderate or severe harm.5 Since
the implementation of the project, only three (approximately
37.5%) of the eight falls in 2017 resulted in mild harm (see
Fig. 2). In 2018, 5 (50%) of the 10 falls resulted in mild harm.
However, all five of these were due to a medical event, two
resulted in a code blue and two in a rapid response team

activation; the staff followed all the applicable fall interven-
tions for each of these events. While there was an upward trend
in the number of fall events in 2018, all except one in the third
and fourth quarters of 2018 had the appropriate fall prevention
interventions in place prior to the event. And, overall the
unit has consistently gone longer between fall events. From
mid-February through December 2018, the average number
of days between falls was 35.96 days. Prior to the intervention
(January 2016 to early February 2017), the average number of
days between falls was 27.8.

Age did not seem to play a factor in the falls. In 2016 prior
to the project implementation, patients age 18–49 accounted
for eight (approx. 67%) of the falls. The following year the
ages were more evenly distributed, with each decade account-
ing for one or two falls. In 2018 six (60%) of the falls were
patients between the ages of 50 and 64. However, the medical-
surgical unit that conducted the project admits mostly civilian
traumas and surgical patients.

DISCUSSION
The implementation of a multifactorial fall prevention bundle,
including a patient fall safety agreement and staff incentive
program, served as a pivotal instrument for the fall rate on
the unit and has several implications for nursing. The safety
agreements and patient education handouts provided nurses
with a standardized set of tools to ensure structured education
is provided to each patient on a consistent basis. The signed
patient safety agreements and staff safety pledges also pro-
moted a culture of safety making both patients and nursing
staff responsible for interventions related to fall prevention.
To encourage adherence, the UPC implemented a staff incen-
tive/recognition program known as “Catch ‘em Doing Good”
to increase staff motivation and adherence with fall prevention
policies despite the frequent changes on the unit. Initially,
the incentive program revitalized the project, served as an
effective means of reinforcing components of the bundle,
and increased staff adherence with components of the fall
prevention program. Unfortunately, the audits required to
sustain the incentive program proved to be too much of a
burden to continue in the long term. The benefit of these audits
was to increase the number of personnel asking the patients
about their fall risk status. Therefore, the patients received
reinforcement of their education, which likely contributed to
the early success of the project.

While only one medical-surgical unit in the facility
implemented this bundle, other units and their leadership took
note of its success. After presenting this project in numerous
forums to the Facility Nurse Practice Council and local and
national conferences, parts of this bundle were incorporated
into the facility policy. Staff members educated other units
about the lessons learned throughout this project as other units
began to adopt parts of it prior to the facility officially updating
the fall policy. Leadership agreed that the most effective
component of the project was the fall safety agreement since it

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FIGURE 1. Quarterly Falls Rate.

FIGURE 2. Falls by Definition.

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encouraged a dialogue between the staff and the patient. Plus,
it enabled the patient to be an active participant in their care.

Like most projects the implementation of the bundle was
not without its challenges. For the first 4 months, the unit
showed a positive trend in the fall rate. However, with staff
turnovers and complacency, the rate began to increase at the
beginning of 2018. Leadership did a push, re-engaging with
the staff at shift change huddles to re-energize the program
(annotated by an ∗ in Fig. 1). At that time, there was also
a decrease in the adjusted fall rate, which does not include
assisted falls. Assisted falls occur when the staff is in the room
with the patient and all the appropriate interventions are in
place. The staff are with the patient when they begin to fall
and assist them to a seated position on the floor. The facility’s
definition of a fall still includes these events as a fall. However,
in these instances the staff probably prevented mild or even
moderate harm since they were with the patient and eased
them to the floor; they implemented all the appropriate fall
interventions.

Military facilities are unique in that floor management
and staff change frequently. For instance, during the first
11 months of the project, the head nurse changed twice, 9
staff members (approx. 32% of the military staff) received rou-
tine military reassignments, and 15 (approx. 28%) additional
nursing staff were oriented to the unit. This created a need for
continuous reinforcement of the bundle components to ensure
all staff members were aware of the unit’s fall prevention
program and safety agreement. Additionally, medical-surgical
units are staffed with nurses with less experience. Using
Benner’s Model,16 the majority (approximately 65%) of the
staff would be considered advanced beginners. Therefore, the
experience level on the unit is low. On a shift there are a mix
of between 7 and 10 registered nurses and licensed vocational
nurses, including the charge nurse. Of those, at least four or
five have less than 2 years of nursing experience. Military
charge nurses typically have about 2 years of experience,
while civilian charge nurses could have anywhere from 3 to
over 10 years.

More studies and research are needed to further evaluate
the sustainability and efficacy of multifactorial fall prevention
programs with safety agreements in both military and civilian
healthcare facilities. Additionally, the optimal bundle of fall
prevention interventions has yet to be identified. It would
be helpful for future studies to determine the interventions
best suited to prevent falls in the medical-surgical setting, the
essential elements of a patient education program, and specific
factors appropriate to increase a culture of patient safety for
fall prevention.

CONCLUSION
Despite the limitations and challenges previously discussed,
since implementation the unit has seen (1) decreased
frequency of falls; (2) less total falls per given time; (3)
maintained low fall rate per 1,000 patient days, and (4) a

maintained low number of falls with mild harm. While falls are
concerning, the unit started with a rate well below the national
average. Therefore, any improvement is difficult to achieve.
The unit also experienced 87 and 88 consecutive fall-free days
which were the longest consecutive number of days since May
2015. Effective education and adherence with fall prevention
measures in both nursing staff and patient populations were
a vital component of fall prevention and increased patient
safety. Safety agreements and bundled prevention approaches
facilitate a dialogue among staff and patients. It improves the
safety of patients, and it creates a collaborative environment
for nurses to conduct safe, quality patient care.

ACKNOWLEDGMENTS
The authors acknowledge the effort of the staff and unit leadership who
helped during the implementation of the project. Special thanks to Tri-Service
Nursing Research Program for their assistance in the publication process. The
authors also declare that the evidence-based project was not funded by any
agency or organization.

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Age and Ageing 2019; 48: 337–346
doi: 10.1093/ageing/afy219
Published electronically 5 February 2019

© The Author(s) 2019. Published by Oxford University Press on behalf of the British Geriatrics Society.
All rights reserved. For permissions, please email: [email protected]

Quality improvement strategies to prevent falls
in older adults: a systematic review and network
meta-analysis

ANDREA C. TRICCO1,2, SONIA M. THOMAS1, ARETI ANGELIKI VERONIKI1, JEMILA S. HAMID1, ELISE COGO1,
LISA STRIFLER1,3, PAUL A. KHAN1, KATHRYN M. SIBLEY4,5, REID ROBSON1, HEATHER MACDONALD1, JOHN
J. RIVA6,7, KEDNAPA THAVORN1,8, CHARLOTTE WILSON1, JAYNA HOLROYD-LEDUC9, GILLIAN D. KERR1,
FABIO FELDMAN10, SUMIT R. MAJUMDAR11✠, SUSAN B. JAGLAL12, WING HUI1, SHARON E. STRAUS1,13

1Knowledge Translation Program, Li Ka Shing Knowledge Institute, St. Michael’s Hospital, 209 Victoria Street, East Building,
Toronto, ON Canada M5B 1T8
2Epidemiology Division, Dalla Lana School of Public Health, University of Toronto, 155 College Street, 6th floor, Toronto, ON,
Canada M5T 3M7
3Institute of Health Policy, Management and Evaluation, University of Toronto, 155 College Street, Toronto, ON, Canada M5T
3M6
4Toronto Rehabilitation Institute, University Health Network, 550 University Avenue, 11th floor, Toronto, ON, Canada M5G
2A2
5Department of Community Health Sciences, University of Manitoba, 379–753 McDermot Ave, Winnipeg, MB, Canada R3E
0W3
6Department of Family Medicine, McMaster University, David Braley Health Sciences Centre, 100 Main Street West, 6th Floor,
Hamilton, ON, Canada L8P 1H6
7Department of Health Research Methods, Evidence and Impact, McMaster University, 1280 Main Street West, Hamilton, ON,
Canada L8S 4K1
8Clinical Epidemiology Program, The Ottawa Hospital Research Institute, 501 Smyth Road, PO Box 201B, Ottawa, ON, Canada
K1H 8L6
9Departments of Medicine and Community Health Sciences, University of Calgary, 1403 29th Street NW, Calgary, AB, Canada
T2N 2T9
10Patient Safety & Injury Prevention, Fraser Health, 13450—102nd Avenue, Surrey, BC, Canada V3T 0H1
11Department of Medicine, University of Alberta, 5-134 Clinical Sciences Building, 11350—83rd Avenue, Edmonton, AB, Canada
T6G 2G3
12Department of Physical Therapy, University of Toronto, 160-500 University Ave, Toronto, ON, Canada M5G 1V7
13Department of Geriatric Medicine, University of Toronto, 27 King’s College Circle, Toronto, ON, Canada M5S 1A1

Address correspondence to: Andrea C. Tricco, Scientist, Knowledge Translation Program, Li Ka Shing Knowledge Institute, St.
Michael’s Hospital 209 Victoria Street, East Building, Toronto, Ontario, M5B 1W8, Canada. Tel: 416-864-6060; Fax: 416-864-
5805. Email: [email protected]
✠Deceased 19 January 2018.

Abstract

Background: Falls are a common occurrence and the most effective quality improvement (QI) strategies remain unclear.
Methods: We conducted a systematic review and network meta-analysis (NMA) to elucidate effective quality improvement
(QI) strategies for falls prevention. Multiple databases were searched (inception−April 2017). We included randomised con-
trolled trials (RCTs) of falls prevention QI strategies for participants aged ≥65 years. Two investigators screened titles and
abstracts, full-text articles, conducted data abstraction and appraised risk of bias independently.
Results: A total of 126 RCTs including 84,307 participants were included after screening 10,650 titles and abstracts and
1210 full-text articles. NMA including 29 RCTs and 26,326 patients found that team changes was statistically superior in

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reducing the risk of injurious falls relative to usual care (odds ratio [OR] 0.57 [0.33 to 0.99]; absolute risk difference [ARD]
−0.11 [95% CI, −0.18 to −0.002]). NMA for the outcome of number of fallers including 61 RCTs and 40 128 patients
found that combined case management, patient reminders and staff education (OR 0.18 [0.07 to 0.47]; ARD −0.27 [95%
CI, −0.33 to −0.15]) and combined case management and patient reminders (OR, 0.36 [0.13 to 0.97]; ARD −0.19 [95%
CI, −0.30 to −0.01]) were both statistically superior compared to usual care.
Conclusions: Team changes may reduce risk of injurious falls and a combination of case management, patient reminders,
and staff education, as well as case management and patient reminders may reduce risk of falls. Our results can be tailored
to decision-maker preferences and availability of resources.
Systematic review registration: PROSPERO (CRD42013004151)

Keywords

falls, falling, quality improvement, older people, fall prevention, systematic review

Key points

• Numerous randomised controlled trials (RCTs) and systematic reviews have examined falls prevention quality improve-
ment (QI) strategies, but the key effective elements remain unclear.

• Network meta-analysis (NMA) allows the ranking of all available falls prevention and combinations of falls prevention QI
strategies for each outcome.

• Our systematic review and NMA of all available falls prevention QI strategies for older people encompassing 126 RCTs
and 84,307 participants, is the first to identify effective QI strategies for preventing falls using NMA.

• We found that effective falls prevention QI strategies are multi-faceted, and including components targeting patients (such
as education and reminders), as well as components targeting clinicians (such as team changes, case management and staff
education) will increase likelihood of effectiveness.

• Depending on the outcome desired, our results can be tailored according to decision-maker preferences and availability of
resources.

Introduction

Despite high-quality evidence of effective interventions for
prevention [1–5], falls remain a common occurrence among
those aged 65 years and older, representing an enormous
burden to patients, their caregivers and the health care sys-
tem [6, 7]. This represents a quality of care gap because high-
quality evidence is not being implemented to prevent falls
and injuries. In order to reduce this gap, quality improvement
(QI) strategies can be considered.

QI strategies can help with the implementation of
evidence-based clinical interventions, such as falls prevention
programmes. QI strategies can target patients (e.g. patient
education), health care providers (e.g. clinician education),
and/or the health care system (e.g. financial incentives). As
the population continues to age [8], QI interventions will
have the potential to prevent numerous falls in the future. In
a previous study of falls prevention interventions, QI strat-
egies were effective at reducing injurious falls [9], but specific
types of QI strategies and their combinations were not
explored. The effectiveness of specific QI strategies alone or
in combination for preventing falls amongst older people
was explored through a systematic review and network
meta-analysis (NMA).

Methods

Protocol

A protocol was prepared using the Preferred Reporting
Items for Systematic Review and Meta-analysis (PRISMA)
Protocols Statement [10], registered with PROSPERO
(CRD42013004151), and published [11]. An integrated
knowledge translation approach was used, whereby the sys-
tematic review team included knowledge users who posed
the research question, and were invited to participate in all
steps of the review. The PRISMA-NMA extension [12] was
followed for the reporting of results (see Appendix P in the
supplementary data, available at Age and Ageing online), which
are related to another paper examining all clinical interven-
tions for falls prevention in addition to QI strategies [9].

Eligibility criteria

Eligible studies were randomised controlled trials (RCTs).
Quasi-randomised trials were excluded. The RCTs had to
include patients aged 65 years or older and any type of set-
ting (e.g. living independently in the community, long-term
care) was eligible for inclusion. The RCT had to examine
one of 13 QI strategies that were adapted from the US

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Agency for Healthcare Research and Quality, which are out-
lined in Box 1 [13, 14]. The comparators examined in the
RCTs were usual care or other falls prevention QI strategies.

The knowledge users identified primary (number of
injurious falls and number of fall-related hospitalisations)
[15] and secondary (number of fallers, fall-related emer-
gency department visits, fall-related physician visits, frac-
tures, intervention-related harms, and quality of life and
health utility [measured by 36-Item or 12-item Short Form

Survey (SF-36 or SF-12), SF-36 physical and mental sum-
mary component measures and health utility measured by
EuroQol-5D (EQ-5D)] outcomes of interest [16, 17].

Data sources

A search strategy was developed and peer-reviewed using
PRESS [18] by experienced librarians, and published [11].
Subsequently, the following databases were searched from

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Box 1. Falls prevention quality improvement strategies

Strategy Description Examples

QI strategies targeting health care providers (clinic or care team)
1) Case management Any system for coordinating diagnosis, treatment, or routine

management of patients (e.g. arrangement for referrals, follow-up
of test results) by a person or multidisciplinary team in
collaboration with, or supplementary to, the primary-care clinician.
If the study called the intervention ‘case management’ we classified
it as such

Nurse functioning as case management role, which
included assessment of patient status, planning,
evaluation of adherence to dietary/medication
recommendation, advocacy, home visits, and care
coordination

2) Team changes Changes to the structure or organisation of the primary health care
team (adding team member, multidisciplinary teams, expansion or
revision of professional roles)

Modifying a geriatric outpatient clinic to include
assessment by a nurse and physiotherapist, in addition
to a geriatrician

3) Facilitated relay of

info to clinicians

Clinical information collected from patients and transmitted to
clinicians by means other than the existing medical record
(excluding conventional means of correspondence between
clinicians.)

Communicating a patient’s medication information to care
providers in the long-term care facilities including the
family physician, nursing staff, and community
physician

4) Continuous QI Interventions explicitly identified as involving the techniques of
continuous QI, total quality management, or plan-do-study-act, or
any iterative process for assessing quality problems, developing
solutions to those problems, testing their effects, and then
reassessing the need for further action

Weekly continuous quality improvement meetings to
discuss progress of individual participants and to help
maximise their success in the intervention

5) Audit & feedback Summary of clinical performance of health care delivered by an
individual clinician or clinic over a specified period, which was then
transmitted back to the clinician. This strategy was strictly based on
clinical data and excluded clinical skills

Providing data on the number of patients with missing
tests to the clinician

6) Staff education Interventions for staff designed to promote increased understanding
of principles guiding clinical care or awareness of specific
recommendations for a target disorder or population of patients

Includes conferences or workshops, distribution of
educational materials (written, video or other), and
educational outreach visits

7) Clinician reminders Paper-based or electronic systems intended to prompt a health
professional to recall patient-specific information (e.g. most recent
HbA1c value) or to do a specific task (e.g. foot examination)

Development of a Fall Prevention Tool Kit software
(decision support system) to prompt physicians when
evaluating a patient

QI strategies targeting health system
8) Financial incentives Interventions with positive or negative financial incentives directed at

providers (e.g. linked to adherence to some process of care or
achievement of some target outcome). This strategy also includes
positive or negative financial incentives directed at patients or
system-wide changes in reimbursement

Examples are gym memberships, drug assistance
programs, free medications.

Rides to the intervention or parking are not included

QI strategies targeting patients
9) Promotion of self-

management

Provision of equipment or access to resources to promote self-
management. If the study called the intervention promotion of
self-management, personalised goal-setting, or action-planning, we
included it here. (We generally thought this a more active strategy
than education of patients)

Problem-solving skills, tracking number of steps, fit bit,
self-help groups, working with patient to develop
strategies to reduce risk of falling

10) Patient Reminders Any effort to remind patients about upcoming appointments or
important aspects of self-care. If the intervention included case
management, reminders to patients needed to be explicit

Reminders via postcards or telephone calls

11) Patient education-

written materials,

videos, lectures, other

Patient education related to health
Note: a pamphlet/leaflet that only explains exercises does not count
as patient education

Pamphlets, booklets, brochures on fall prevention, videos,
classes, lectures, workshops, unspecified instructions/
advice to prevent falls

12) Motivational

interviewing

‘a directive and client-centred counselling style that relies upon
identifying and mobilising the client’s intrinsic values and goals to
stimulate behaviour change (Miller & Rollnick, 2002), thus
encouraging client and family involvement in all aspects of care.’

Restructuring misconceptions to promote a view of falls
risk and fear of falling as controllable, setting realistic
goals for increasing activity in a safe manner (taking
personal capabilities into account)

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inception until April 2017: MEDLINE, EMBASE, Cochrane
Central Register of Controlled Trials and Ageline. In addition,
trial registries, conference abstracts, reference lists of included
RCTs, and references of related systematic reviews were
searched. Authors of relevant RCTs were emailed to obtain
additional or unpublished data.

Study selection

The eligibility criteria and screening explanation document
were calibrated on a random sample of 50 citations. After
75% agreement was achieved, pairs of reviewers screened
all citations and potentially relevant full-text articles inde-
pendently. Conflicts were resolved by a third reviewer.

Data abstraction

A data abstraction form was developed in Excel with an
accompanying guidance document, and calibrated using a
5% random sample of included studies. After calibration,
all data were independently abstracted by pairs of reviewers.
To increase consistency, all discrepancies were resolved by a
third reviewer. As falls prevention QI strategies are complex
interventions, which are difficult to classify [19], all studies
were coded independently by a knowledge user and a meth-
odologist, using the pre-established coding guide for QI
strategies.

Risk-of-bias appraisal

The Cochrane Effective Practice and Organisation of Care
(EPOC) Group’s risk-of-bias tool was used to appraise the
internal validity of included RCTs [20]. The tool was cali-
brated using a random sample of five included studies.
Subsequently, each included RCT was appraised by inde-
pendent pairs of reviewers. Conflicts were resolved by a
third reviewer.

Data synthesis and analysis

All analyses were conducted by an experienced statistician
who used the metafor and netmeta packages [21–23] in R stat-
istical version 3.3.3 [24] software and the netfunnel command
in STATA 13.0 [25–28]. Pooled odds ratios (ORs) for
dichotomous data, which were converted to the absolute
risk differences (ARDs) using standard formulae [29] and
mean differences (MD) for continuous data were estimated
using pairwise random-effects meta-analysis. RCTs report-
ing dichotomous outcomes with zero events across all arms
were excluded from the analysis. RCTs reporting continu-
ous outcomes with missing measures of variance (e.g.
standard deviation) were included in the analysis, with
standard errors imputed using established methods, if feas-
ible [30,31]. Cluster-RCTs were adjusted using an effective
sample size and intracluster correlation coefficient (ICC) for
each cluster-RCT [13, 14]. The between-study variance in
both meta-analysis and NMA was estimated using the
DerSimonian and Laird method [32,33]. In each meta-

analysis, heterogeneity was quantified using the I2- measure
[34]. The mean control event rate across included studies
was calculated for each outcome when possible.

For outcomes forming a connected network of falls pre-
vention interventions, random-effects NMA was conducted
using a common within-network between-study variance (τ2)
across treatment comparisons. To surmount small-study
effects [35], RCTs with 100 or fewer patients across all treat-
ment arms were excluded from analysis. A comparison-
adjusted funnel plot was drawn for each outcome with at least
10 studies to examine small-study effects [27] by estimating
the overall treatment effect for each comparison under the
fixed-effect meta-analysis model and ordering all interven-
tions based on the potential for effectiveness and target.

In order to predict the interval within which a new RCT
treatment effect would lie, a 95% predictive interval was cal-
culated [36]. The NMA assumptions were tested a priori, first
by assessing transitivity and comparing all potential effect
modifiers across treatment comparisons, and then evaluating
consistency between different sources of evidence in the net-
work using the design-by-treatment model [37]. Several
effect modifiers were considered (see Appendix A in the
supplementary data, available at Age and Ageing online). If
results suggested global inconsistency, then local inconsist-
ency was examined within each loop in a network separately
using the loop-specific method [38,39]. If results suggested
local inconsistency or important heterogeneity, or over 10
RCTs were available, and the number of RCTs was larger
than the number of the included interventions, a subgroup
NMA was conducted considering the aforementioned effect
modifiers. Sensitivity analyses were conducted on the risk of
bias results for the primary outcomes. All interventions were
ranked using P-scores measuring the mean extent of certainty
that a treatment is better when compared to the remaining
treatments in the network [40]. P-scores were depicted across
all outcomes in a rank-heat plot (http://rh.ktss.ca/) [41].
Both meta-analysis and NMA treatment effect estimates were
presented along with 95% confidence intervals (CI).

Results

Study selection

A total of 10,650 citations and 1,210 full-text articles were
screened (Figure 1). Of these, 126 RCTs (84,307 partici-
pants) involved a relevant QI strategy with a relevant com-
parator were included (Figure 1, see Appendix B in the
supplementary data, available at Age and Ageing online).
None of the included studies were written in languages other
than English; one paper was a dissertation [42].

Study and participant characteristics

The mean of ages of participants across studies ranged
between 65 and 88 years across the 126 included RCTs
(Table 1, see Appendix C in the supplementary data, available
at Age and Ageing online). Most RCTs included a high propor-
tion (over 50%) of female participants (89%) (Table 1, see

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Appendix C in the supplementary data, available at Age and
Ageing online), and included a mixture of participants with
and without a previous history of falling (66%). The number
of medications used by participants was not reported in
most RCTs (59%).

The majority of the RCTs were published in 2004 or
later (77%), and conducted mainly in Europe (39%) and
Australia/New Zealand (33%) (Table 1, see Appendix D in
the supplementary data, available at Age and Ageing online).
The studies were most frequently conducted in a home set-
ting (57%), clinic (28%), or community (27%), with a lower
proportion occurring in a hospital (15%), chronic care
(16%), or retirement home (8%) setting. The number of
included participants ranged from 22 to 5,310 for patient
RCTs, and 80 to 10,558 for cluster-RCTs (3–842 clusters).

Risk of bias

The majority of the included RCTs were assessed as having a
low risk of bias for random sequence generation (69% low;

30% unclear; 1% high), allocation concealment (58% low; 40%
unclear; 2% high), similar baseline outcome measures (82% low;
13% unclear; 6% high), similar baseline characteristics (80% low;
10% unclear; 10% high), incomplete outcome data (77% low;
8% unclear; 15% high), blinding (93% low; 3% unclear; 4%
high), and other bias (69% low; 22% unclear; 9% high) (see
Appendices E and F in the supplementary data, available at Age
and Ageing online). However, the majority of the RCTs were
assessed as having an unclear risk of bias for contamination
(58% unclear; 40% low; 2% high) and selective outcome report-
ing (56% unclear; 41% low; 2% high) (see Appendices E and F
in the supplementary data, available at Age and Ageing online).
The comparison-adjusted funnel plots suggested no evidence of
publication bias or small-study effects (see Appendix G in the
supplementary data, available at Age and Ageing online).

Outcome results

Twenty-two studies included less than 100 patients and
were excluded from the analysis [43–64]. All pairwise

Figure 1. Study flow.

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meta-analysis results can be found in Appendix H in the
supplementary data, available at Age and Ageing online.
Across all NMAs, no evidence of significant inconsistency
was indicated (see Appendix I in the supplementary data,
available at Age and Ageing online). The overall NMA results
for each outcome, with a focus on the QI strategy effects
relative to usual care are presented below. The results from
all significant treatment comparisons can be found in
Appendix I in the supplementary data, available at Age and
Ageing online. Subgroup and sensitivity analyses are sum-
marised in Table 2, and all the P-scores from the overall
NMAs, subgroup, and sensitivity analyses can be found in
Appendices J and K in the supplementary data, available at
Age and Ageing online. The rank-heat plot is presented in
Appendix L in the supplementary data, available at Age and
Ageing online.

Injurious falls

NMA for number of injurious falls included 29 RCTs
(26,326 patients), with a total of 18 QI strategies examined
(see Appendix M Panel A in the supplementary data, avail-
able at Age and Ageing online). The average event rate for the
usual care group was 31.79%. Across all 171 comparisons,
3 (1.75%) were statistically significant (see Appendix I in the
supplementary data, available at Age and Ageing online). The
QI intervention of team changes was statistically superior in
reducing the risk of injurious falls relative to usual care (OR,
0.57 [95% CI, 0.33–0.99]; ARD −0.11 [95% CI, −0.18 to
−0.002]). All studies of team changes were in mixed settings.
An additional 12 single or multifactorial interventions were
also superior to usual care, but the differences did not reach
statistical significance. While five interventions were inferior
(i.e. associated with increased falls) to usual care, none of
these differences were statistically significant (see Appendix
I in the supplementary data, available at Age and Ageing
online). Subgroup and sensitivity analyses can be found in
Appendices A and J in the supplementary data, available at
Age and Ageing online.

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Table 1. Summary of patient and study characteristics

Patient characteristics

Number of RCTs % of RCTs
(n = 126)

Age (mean)
65–74.99 years 30 23.8
75–84.99 years 73 57.9
≥85 years 9 7.1
NR 14 11.1

Female (%)
0–49.99% 9 7.1
50–69.99% 42 33.3
70–89.99% 54 42.9
90–100% 16 12.7
NR 5 4.0

History of falls
All have history of falls 30 23.8
Mixed history of falls 83 65.9
NR 13 10.3

Medications takena

0–4 medications 25 19.8
≥5 medications 27 21.4
NR 74 58.7

Study characteristics

Year of publication
1992–96 4 3.2
1997–2001 9 7.1
2002–6 23 18.3
2007–11 43 34.1
2012–17 47 37.3

Continent
Europe 49 38.9
Australia/New Zealand 41 32.5
North America 19 15.1
Asia 16 12.7
Multi 1 0.8

Study design
Parallel RCT 103 81.7
Cluster RCT 23 18.3

Site
Multi-centre 83 65.9
Single centre 43 34.1

Settingsb

Home 72 57.1
Clinic 35 27.8
Community 34 27.0
Hospital 19 15.1
Chronic care 20 15.9
Retirement home 10 7.9
NR 2 1.6

Sample Size
Patient RCTs
22–99 20 19.4
100–199 25 24.3
200–299 15 14.6
300–999 37 35.9
1,000–5,310 6 5.8

Cluster RCTs
80–499 8 34.8
500–999 7 30.4
1,000–3,999 5 21.7
4,000–10,558 3 13.0

Continued

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Table 1. Continued

Patient characteristics

Number of RCTs % of RCTs
(n = 126)

Study duration
<1–24 weeks 53 42.1
25–50 weeks 22 17.5
51–75 weeks 31 24.6
76–208 weeks 9 7.1
NR 11 8.7

NR, not reported; RCT, randomised controlled trial.
aMean or median.
bTotal numbers are >110 and >100% due to studies reporting multiple
settings.

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Fall-related hospitalisations

For falls-related hospitalisations, eight RCTs (4,887 patients)
with 10 treatments were included. NMA was not possible
because of network disconnectivity. No pairwise meta-analysis
was possible across all pairwise comparisons (see Appendix H
in the supplementary data, available at Age and Ageing online).

Number of fallers

NMA for the number of fallers included 61 RCTs (40 128
patients), examining 35 QI interventions (see Appendix M
Panel B in the supplementary data, available at Age and
Ageing online). The total event rate for the usual care group
was 39.50%. Across all 595 comparisons, 27 (4.5%) were
statistically significant (see Appendix I in the supplementary
data, available at Age and Ageing online). Combined case
management, patient reminders and staff education were
statistically superior in reducing the number of fallers rela-
tive to usual care (OR, 0.18 [95% CI, 0.07–0.47]; ARD

−0.29 [95% CI, −0.35 to −0.16]). Combined case manage-
ment and patient reminders were also statistically superior
to usual care in reducing the number of fallers (OR, 0.36
[95% CI, 0.13–0.97]; ARD −0.20 [95% CI, −0.32 to
−0.007]). An additional 28 single or multifactorial interven-
tions were superior to usual care, but the differences were
not statistically significant. While four interventions were
inferior to usual care, none were statistically significant.
Subgroup and sensitivity analyses are summarised in Table 2
and Appendices A and J in the supplementary data, avail-
able at Age and Ageing online.

Emergency department visits

For number of emergency department visits, four RCTs
(1,280 patients) with five treatments were included. Pairwise
meta-analysis was not possible across any comparisons (see
Appendix H in the supplementary data, available at Age and
Ageing online).

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Table 2. Statistically significant additional analysis results for the outcome of number of fallers

Intervention (versus usual care) OR (95% CI) Direction of result

Subgroup: follow-up <12 months (24 studies, 14,135 patients)
Staff education 2.33 (1.06–5.26) Increased risk

Subgroup: follow-up >12 months (36 studies, 22,692 patients)
Patient education 0.73 (0.54–0.98) Reduced risk
Patient education + self-management 0.50 (0.26–0.99) Reduced risk
Patient education + staff education 0.59 (0.40–0.88) Reduced risk
Patient education + team changes 0.59 (0.40–0.86) Reduced risk
Case management + patient reminders + staff education 0.18 (0.07–0.45) Reduced risk
Case management + motivational interviewing + patient education + team changes 0.33 (0.12–0.88) Reduced risk

Subgroup: age <80 years (40 studies, 26,785 patients)
Staff education 3.23 (1.03–10.00) Increased risk

Subgroup: age ≥80 years (19 studies, 9,368 patients)
Patient education + self-management 0.57 (0.33–0.96) Reduced risk
Patient education + staff education 0.61 (0.38–0.99) Reduced risk
Patient education + team changes 0.48 (0.24–0.96) Reduced risk
Patient education + self-management + staff education 0.44 (0.21–0.95) Reduced risk
Case management + patient reminders + staff education 0.18 (0.07–0.44) Reduced risk

Subgroup: female <75% (37 studies, 24,658 patients)
Case management + patient reminders 0.36 (0.14–0.92) Reduced risk

Subgroup: female >75% (21 studies, 11,375 patients)
Patient education + team changes 0.24 (0.07–0.87) Reduced risk
Case management + patient reminders + staff education 0.18 (0.06–0.56) Reduced risk

Subgroup: Medication use ≥5 (15 studies, 8,634 patients)
Patient education 0.18 (0.05–0.69) Reduced risk
Patient education + team changes 0.24 (0.07–0.81) Reduced risk

Subgroup: medication use <5 (15 studies, 7,950 patients)
Patient education 2.00 (1.03–4.00) Increased risk
Case management + patient reminders + staff education 0.18 (0.07–0.48) Reduced risk

Subgroup: history of falling − all fallers (12 studies, 3,709 patients)
No significant comparisons – –

Subgroup: mixed history of falling (40 studies, 33,959 patients)
Case management + patient reminders + staff education 0.18 (0.07–0.43) Reduced risk

Subgroup: home setting (24 studies, 15,418 patients)
Case management + patient reminders + staff education 0.18 (0.08–0.43) Reduced risk

Sensitivity analysis: low risk of contamination (29 studies, 24,967 patients)
Case management + patient reminders + staff education 0.18 (0.06–0.53) Reduced risk
Case management + motivational interviewing + patient education + team changes 0.28 (0.08–0.97) Reduced risk

Sensitivity analysis: low risk of selective outcome reporting (24 studies, 14,564 patients)
Case management + patient reminders 0.36 (0.14–0.91) Reduced risk

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Outpatient physician visits

For outpatient physician visits, nine RCTs (6,856 patients)
with 11 treatments were included. NMA was not possible
due to network disconnectivity. Only one pairwise meta-
analysis was possible (see Appendix H in the supplementary
data, available at Age and Ageing online). There was no statis-
tically significant difference between combined patient edu-
cation and team changes compared to patient education
alone (OR, 1.14 [95% CI, 0.82–1.59]).

Fractures

NMA for the number of fractures included 23 RCTs (38
497 patients), which examined 17 different QI strategies
(see Appendix M Panel C in the supplementary data, avail-
able at Age and Ageing online). The total event rate for the
usual care group was 6.84%. Across all 153 comparisons,
one was statistically significant (see Appendix I in the sup-
plementary data, available at Age and Ageing online). Patient
education was statistically superior compared to usual care
in reducing the number of fractures (OR, 0.81 [95% CI,
0.68–0.97]; ARD −0.012 [95% CI, −0.021 to −0.0019]).
Eleven interventions appeared superior to usual care and
five were inferior to usual care, but these differences were
not statistically significant.

Hip fractures

Eleven RCTs (15 883 participants) with 11 treatments were
included for the outcome of hip fractures. Across all com-
parisons, pairwise meta-analyses were not possible (see
Appendix H in the supplementary data, available at Age and
Ageing online).

Harms

Twenty of the included RCTs reported no intervention-
related harmful events in all study arms, and 13 RCTs
reported at least one harm event (see Appendix N in the
supplementary data, available at Age and Ageing online).
Pairwise meta-analysis was not possible across any compari-
son (see Appendix H in the supplementary data, available at
Age and Ageing online).

Quality of life

Ten RCTs reported on quality of life using the SF-12 or SF-
36 physical and mental summary component measures or
EuroQol-5D. One pairwise meta-analysis was possible
across all comparisons (see Appendix H in the supplemen-
tary data, available at Age and Ageing online). There was no
statistically significant difference between team changes com-
pared to usual care (OR, −4.12 [95% CI, −8.87 to 0.63]).

Discussion

Team changes, which refers to modifying the structure of
the primary health care team (see Box 1), may reduce risk of

injurious falls, and patient education, which includes provi-
sion of health-related educational materials to patients, may
reduce risk of fractures. Furthermore, a combination of case
management (any system for coordinating diagnosis, treat-
ment, or routine management of patients by a person or
multidisciplinary team in collaboration with, or supplemen-
tary to, the primary-care clinician), patient reminders, and
staff education, as well as a combination of case manage-
ment and patient reminders may reduce falls. These results
can be used to tailor treatment to decision-maker prefer-
ences for outcome and availability of resources. For example,
if a clinic has many patients over 80 years of age and avail-
able resources, clinicians can consider the following inter-
ventions for reducing falls: combined patient education and
self-management, combined patient education and staff edu-
cation, combined patient education and team changes, com-
bined patient education, self-management, staff education,
and combined case management, patient reminders, and
staff education (Table 2). The longest term studies (i.e.
follow-up ≥12 months) suggested that patient education,
combined patient education and self-management, com-
bined patient education and staff education, combined
patient education and team changes, combined case manage-
ment, patient reminders, staff education, as well as combined
case management and motivational interviewing and patient
education and team changes are likely effective for reducing
the risk of falling. While staff education appeared to increase
the number of falls in patients below the age of 80 years, and
those with shorter follow-up (<12 months), this finding is
not unexpected (Table 2). Educational interventions about
fall prevention targeted at staff typically result in greater
awareness, and can subsequently lead to increased reporting
of fall-related events. Overall, QI interventions should target
patients and the team (rather than clinicians alone) to have
impact on falls, injurious falls, and fractures, and simple
interventions are unlikely to be effective.

There are numerous strengths to this systematic review.
The methods conform to the Cochrane Handbook for
Systematic Reviews [65] and the International Society for
Pharmacoeconomics and Outcomes Research (ISPOR)
guidance on NMA validity [66]. In addition, studies written
in languages other than English were sought (although
none were identified), as well as unpublished studies. The
use of RCTs to evaluate the effectiveness of QI interven-
tions produces generalisable knowledge which can be
applied to a variety of settings, rather than the localised
knowledge produced by a PDSA cycle. However, there are
limitations. The results are only as valid as the included
RCTs, and although most contained a low risk of bias, con-
tamination and outcome reporting bias were frequently
unclear. In addition, several outcomes of interest lacked suf-
ficient data to conduct analysis. Furthermore, an interven-
tion coding scheme adapted from the Agency for
Healthcare Research and Quality was used, however other
taxonomies [67,68] may have led to different results.
Coding the QI strategies was complex, and definitions of
these varied across studies. For example, case management

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may include different personnel with varying levels of skills
across studies, contributing to heterogeneity. As well, some
analyses (subgroup and sensitivity) were not possible due to
limited data. Some additional analyses for the number of
fallers found that the QI strategies may increase falls.
Further exploration of the effects of combinations of falls
prevention interventions and different QI interventions
should be explored to identify optimal combinations of
these complex interventions. This issue highlights a chal-
lenge in clinical practice whereby patients require multiple
interventions and little is known about how these interven-
tions interact.

Future RCTs can be designed to examine outcomes, such
as outpatient physician visits, harms and quality of life. In
addition, the results can be extended to a cost-effectiveness
analysis, which is currently being planned by members of the
team, and will provide important information to decision-
makers considering implementation of these approaches.
Finally, a different model can be used to explore our results
further, such as the additive model [69], which is currently
being conducted by the coauthors.

Conclusions

Team changes may reduce risk of injurious falls, patient educa-
tion may reduce the risk of fractures, and a combination of
case management, patient reminders, and staff education, as
well as case management and patient reminders combined
may reduce risk of falls. These results can be tailored accord-
ing to decision-maker preferences and availability of resources.

Supplementary data mentioned in the text are available to
subscribers in Age and Ageing online.

Declaration of Conflicts of Interests: RR owns stock in
GlaxoSmithKline and provides consulting services to a con-
tract research organisation that provides services to various
pharmaceutical companies, which are not funding this pro-
ject. The methodology used in this study, such as screening,
selection and abstraction conducted independently by two
separate reviewers, was designed to manage any potential
conflict of interest.

Declaration of Sources of Funding: The research is
funded by a Canadian Institutes of Health research and
Knowledge Synthesis Grant (KRS289648).

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Copyright © 2019 British Geriatric Society. Copyright of Age & Ageing is the property of
British Geriatric Society 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.

408 | wileyonlinelibrary.com/journal/ajr Aust. J. Rural Health. 2020;28:408–413.© 2020 National Rural Health Alliance Ltd.

1 | BAC KG R O U N D
It is known that falls are a leading cause of mortality and
morbidity, especially in the elderly.1 In 2017-2018, there
were 64 385 falls that resulted in the need for hospitalisation
in NSW, associated with an upward trend over the past dec-
ade.2 Australian hospital statistics reported more than 40 000

inpatient falls during 2017-2018 in Australian hospitals that
resulted in harm.3 Morello et al4 examined the incidence of
inpatient falls across multiple sites in Australia from 2011 to
2013 and identified that 3.6% of hospital admissions involved
at least one fall and 1.2% of admissions had at least one fall
resulting in injury. One study involving two general rehabilita-
tion inpatient wards in the Sydney area had a falls rate of 14%,

Received: 30 November 2019 | Revised: 25 April 2020 | Accepted: 18 May 2020
DOI: 10.1111/ajr.12646

Q U A L I T Y I M P R O V E M E N T R E P O R T

Reducing falls through the implementation of a multicomponent
intervention on a rural mixed rehabilitation ward

Colleen Lok Kum Ma MBBS | Rebecca Ann Morrissey FAFRM

Department of Rehabilitation & Aged
Care, Tamworth Rural Referral Hospital,
Tamworth, NSW, Australia

Correspondence
Colleen Lok Kum Ma, Rehabilitation Unit,
Tamworth Rural Referral Hospital, 31 Dean
Street, Tamworth, NSW 2340, Australia.
Email: [email protected]

Abstract
Problem: There is an absence of literature to guide staff in how falls can be reduced
in a diverse patient population on a mixed acute/subacute rehabilitation unit, espe-
cially one with daily fluctuations in acuity that occurs due to frequent changes in its
acute/rehabilitation patient ratio.
Design: Pre-intervention and post-intervention audits.
Setting: The Rehabilitation Unit at Tamworth Rural Referral Hospital in Tamworth,
NSW.
Key measures for improvement: Improvement in the number of falls and repeat
fallers.
Strategies for change: A multicomponent intervention involving: (a) in-service
education sessions for nursing staff about falls risk-increasing drugs, (b) patient
and family education regarding falls risks and prevention strategies, (c) improving
documentation of incident reports by using a set template, (d) ensuring that the cor-
rect patient mobility status information is handed over between nursing shifts and
physiotherapists providing timely and regular updates, (e) the introduction of the
‘traffic light mobility system’ and (f) enhancing the use of existing falls prevention
strategies.
Effects of change: The total falls reduced in number from 36 falls to 19 with a de-
crease in the number of repeat fallers from 8 to 4. There was also increased compli-
ance with existing falls risk tools and improved documentation of each falls incident
which provided insight into activities and times with higher falls risk.
Lessons learnt: A multicomponent approach remained effective even when applied
to a mixed acute/subacute rehabilitation ward setting.

K E Y W O R D S

falls reduction, heterogeneous patient population, multicomponent intervention, rural

| 409MA And MORRISSEY
with 4% having two or more falls.5 In the rehabilitation setting,
the rate of falls varies with respect to the inpatient population
characteristics particularly in the areas of continence and toi-
leting, cognition, communication, balance and mobility.5,6

In 2017, statistics provided by the Peel Sector Falls
Injury and Prevention Committee found that the Tamworth
Rural Referral Hospital (TRRH) Rehabilitation Unit had
the highest rate of falls when compared to the other in-
patient wards. This was based on the number of falls per
patient bed days across the entire hospital. The rehabilita-
tion unit is a 22-bed onsite ward with acute medical and
surgical patients and subacute rehabilitation patients being
cared for in the same ward. This ratio of acute vs rehabil-
itation patients can vary on a daily basis; thus, the range
of functional abilities and conditions on the rehabilitation
ward varies considerably.

There is an absence of literature to guide the staff in the
care of acute patients alongside rehabilitation patients in re-
ducing falls in this unique situation. Previous research has
generally focused on either intervention implemented in a
purely acute setting4 or in a rehabilitation setting,5,6 but not to-
gether, presumably in part due to the large variation in patient
characteristics.

What is already known on this subject:
• Falls remain common in patient populations with

cognitive impairment requiring assistance with
mobility and personal care and in those with a di-
agnosis of stroke

• Currently, the majority of literature is targeted to-
wards falls reduction in a relatively homogenous
patient population with existing falls risk strate-
gies. There is limited research into preventing
falls on a mixed acute/subacute rehabilitation unit

What this study adds:
• A tailored multicomponent approach to falls re-

duction remains effective in a mixed of acute/sub-
acute rehabilitation unit with daily fluctuations in
patient acuity

• Existing falls reduction tools are only effective if
used correctly

• The traffic light mobility system can help prevent
falls and contribute to patient goal setting, an im-
portant component of the rehabilitation process

T A B L E 1 Summary of gaps and interventions

Gaps in existing falls reduction plan Proposed interventions

Education

Insufficient patient and staff education regarding identification of risk
factors

Example: Education regarding management of cognitively impaired
patients: equipment such as bed alarms and pressure sensors should
be used for patients with cognitive impairment as they might not
realise they have to buzz for assistance when mobilising

(i) Nursing staff required to redo online falls modules and review
policy regarding falls prevention

(ii) Medical team provided in-service presentations on common falls
risk-inducing drugs and their associated side effects

(iii) Promote active patient and family involvement during the
Falls Risk Screen (FRS)/Falls Risk Assessment Management Plan
(FRAMP) assessment to identify personalised strategies for falls
reduction

Documentation

Inconsistent completion and utilisation of the FRS/FRAMP
assessment tools (missing or incomplete)

(i) Improve completion rates of the existing FRS/FRAMP tools

Highly variable accuracy and quantity of information provided in
IIMS reports regarding the circumstances of each fall

Example: Some reports did not provide any detail of the
circumstances leading up to the fall, only that the patient was found
on the ground.

(i) Use a set template developed by the hospital inpatient falls
committee with the essential data to be included in each report

Mobility status identification

Whiteboards at the bedside not updated with current mobility status
(outdated or missing)

Mismatch in patient mobility status handed over by the
physiotherapist and nursing handover (both verbal and written)

(i) Daily updates of the white bedside care boards by a nominated
nursing staff

(ii) Improving consistency through regular checks each day for any
disparity in mobility status by an assigned nursing staff member

Difficulty with identifying patient’s mobility status in an efficient
manner when patient away from bedside

(i) Introduction of the traffic light mobility system: patients requiring
assistance had a red tag attached to their mobility aid with an elastic
band. Patients requiring standby assistance or supervision had a
yellow tag and patients that were cleared to mobilise independently
had a green tag

410 | MA And MORRISSEY

2 | M E T H O D S
An audit tool was developed following a review of the
existing literature.5,6 This tool was used in both the pre-
intervention and postintervention audits to investigate the
circumstances and characteristics surrounding each fall and
to assess the unit’s compliance with risk assessment tools
and documentation. The information was gathered using
the existing Incident Information Management System
(IIMS) tool (which captured information regarding pa-
tient characteristics, risk factors and the fall incident itself)
along with a file review to ensure accuracy and completion

of the IIMS data and to collect the remaining data of inter-
est such as medications and mobility status. The total num-
ber of inpatient admissions during the study period was
collected using the search function in the hospital patient
management system.

This quality improvement initiative consisted of three
parts: the pre-intervention audit (November 2017-April
2018), assessment and intervention phase (with interventions
implemented from July 2018 onwards) and the postinterven-
tion audit (October 2018-March 2019).

The pre-intervention audit was conducted to eval-
uate patient characteristics and the circumstances

Patient characteristics
Preliminary audit
(n = 27) Reaudit (n = 14)

P
value

Gender

Male 17 (63.0%) 10 (71.4%) .734

Female 10 (37.0%) 4 (28.6%)

Age

65 and below 5 (18.5%) 6 (42.9%) .140

Over 65 22 (81.5%) 8 (57.1%)

Care status

Acute 9 (33.3%) 2 (14.3%) .275

Rehabilitation 18 (66.7%) 12 (85.7%)

Condition type

Amputee 1 (3.7%) 3 (21.4%) .326

Deconditioning 7 (25.3%) 3 (21.4%)

Orthopaedics 2 (7.4%) 0 (0.0%)

Other 4 (14.8%) 3 (21.4%)

Stroke 13 (48.1%) 5 (35.7%)

Cognitive impairment

Yes 21 (77.8%) 11 (78.6%) 1.000

No 6 (22.2%) 3 (21.4%)

Mobility status

Assistance 11 (40.7%) 8 (57.1%) .818

Supervision 10 (37.0%) 1 (7.1%)

Independent 6 (22.2%) 5 (35.7%)

Mobility aid

Wheelchair 5 (18.5%) 5 (35.7%) .449

Frame 2 (7.4%) 2 (14.3%)

4WW 10 (37.0%) 5 (35.7%)

Walking Stick 7 (25.9%) 2 (14.3%)

Nil aid 3 (8.1%) 0 (0.0%)

Activities of daily living status

Assistance 18 (66.7%) 11 (78.6%) .490

Supervision 1 (3.7%) 1 (7.1%)

Independent 8 (29.6%) 2 (14.3%)

T A B L E 2 Patient characteristics

| 411MA And MORRISSEY

surrounding each fall in order to identify gaps in falls
prevention. Recommended strategies to address these
(Table 1) were presented by the authors to the ward quality
improvement team, which included issues involving edu-
cation about common falls risk factors, documentation and
identification of the patient’s mobility status. A discussion
surrounding the proposed interventions included input from
each discipline in the rehabilitation team: such was essen-
tial to ensure a unified approach for successful implementa-
tion of the interventions.

We strived to optimise current resources and clinical prac-
tices first, as these were not being used to their full potential.
This included ensuring completion of the Falls Risk Screen
(FRS) and Falls Risk Assessment and Management Plan
(FRAMP) in a timely manner. The only new addition was the
traffic light mobility system (TLMS).

The specific interventions, as outlined in Table  1, were
implemented in July 2018 and subsequently became incor-
porated into clinical practice thereafter, as per the Plan-
Do-Study-Act cycle recommended by the NSW Clinical
Excellence Commission.7

The post-intervention audit was completed following the
implementation of the interventions.

2.1 | Statistical analysis
The statistical significance of the pre- and post-intervention
groups was analysed using the Chi-square test for categorical
variables with Fisher’s exact test used for expected values of
<5. The Mann-Whitney U test was used for ordinal data such
as mobility and activities of daily living (ADL) status. The
accepted significance level was set at P < .05. The software
used was Statistical Package for the Social Sciences version
19 (SPSS, 115 Chicago, IL, USA).

2.2 | Ethics approval
An application was submitted to the Hunter New England
Human Research Ethics committee for ethics approval—
the decision from the committee was that this project in its
current forms as a quality improvement project did not re-
quire HREC approval to proceed (authorisation number:
AU201809-12).

3 | R E S U LT S
Patient and fall characteristics are listed below in Tables  2
and 3, respectively, with falls risk tools compliance rates
listed in Table 4. Male patients contributed to the majority of
falls in both audits.

Data collected from the pre-intervention audit identified
259 inpatient admissions to the rehabilitation ward with a
total of 36 falls. There were 27/259 (10.4%) patients having at
least one fall, and of these fallers, 8/27 had more than one fall.

The post-intervention audit included 257 inpatient admis-
sions to the rehabilitation ward with a total of 19 falls. The
number of fallers overall decreased in the post-intervention
audit with 14/257 (5.4%) patients that had at least one fall,
and of these fallers, 4/14 had more than one fall.

As shown in Table  2, many falls in the pre- and
post-intervention audits involved patients recovering from
a stroke and individuals with cognitive impairment, those
requiring hands-on assistance and/or requiring a four-wheel
walker for mobility and those requiring assistance with their
ADLs. Most falls were sustained during transfers and when
mobilising. All repeat fallers in both audits met the criteria for
having at least two of these aforementioned characteristics.

T A B L E 3 Falls characteristics

Fall characteristics

Preliminary
audit Reaudit

P
value(n = 36) (n = 19)

Activity type

Mobilising 12 (33.3%) 5 (26.3%) .178

Transfers 17 (47.2%) 6 (31.6%)

Leaning 3 (8.3%) 4 (21.0%)

Rolled out of bed 2 (5.6%) 4 (21.0%)

Unwitnessed 2 (5.6%) 0 (0.0%)

Location

Bedside 22 (61.1%) 9 (47.4%) .232

Hallway 2 (5.6%) 0 (0.0%)

Lounge room 0 (0.0%) 3 (15.8%)

Physiotherapy Gym 2 (5.6%) 2 (10.5%)

Shower 3 (5.6%) 3 (15.8%)

Toilet 7 (19.4%) 2 (10.5%)

Fall risk assessment tools
completion

Preliminary audit
(n = 27) Reaudit (n = 14)

P
value

FRS (on admission) 27/27 (100%) 13/14 (92.9%) .000

FRAMP (on admission) 24/27 (88.9%) 13/14 (92.9%)

FRAMP (postfall) 17/36 (47.2%) 18/19 (94.7%)

T A B L E 4 Falls risk assessment tools
completion

412 | MA And MORRISSEY
Falls risk assessment tools used at Tamworth Hospital

include the FRS and FRAMP. There was a significant im-
provement in compliance with FRAMP updates in the
post-intervention audit as seen in Table 4.

4 | D I S C U S S I O N
The number of falls on the rehabilitation unit was reduced
following the implementation of a multicomponent interven-
tional approach. This resulted in a change in the number of
patients falling from 10.4% to 5.4% of all admissions and a
statistically significant change in the compliance rate for up-
dating the FRAMP following a fall. This might account for
the reduced number of repeat fallers in the post-intervention
audit. This study showed that falls reduction can be achieved
with inexpensive and simple changes in clinical practice
when dealing with diverse states of patient acuity.

Previous studies have shown that a multicomponent ap-
proach is the most effective method of preventing falls in
the hospital setting with a 30%–47% reduction in the over-
all amount of falls postinterventions.8,9 As noted in the sys-
tematic review by Chang et al,10 the difficulty remains in
identifying which component of the multifactorial approach
contributed the most towards falls reduction.

It is known that falls rates are significantly higher among
stroke patients in rehabilitation, with figures ranging from
16.3% to 37% of inpatients having at least one fall,11,12 with
a large majority of falls attributed to deficits in gait and bal-
ance.13 Measured outcomes from the National Stroke Audit
201814 showed that 15% of stroke patients (included in the
audited rehabilitation units) sustained a fall during their ad-
mission. Multiple studies have also shown a link between
declining cognition (in particular, deterioration in executive
function) in the elderly with an increased risk of falling.15,16
A study by Fischer et al17 identified that fallers tend to carry
out ADLs requiring mobility in an unsafe manner. Similar
trends were reflected in both audits completed at TRRH
with stroke patients and those with impaired cognition or
requiring assistance with their ADLs making up a large pro-
portion of fallers. Future quality improvement research on
this ward could focus on providing tailored interventions to-
wards this high-risk population with the adaptability to be
modified when the patient demographics change.

There were fewer falls in patients requiring supervision. It
is hypothesised that this could be attributed to the implemen-
tation of the TLMS. Both staff and visitors have found the
TLMS to be useful in providing an easily identifiable visual
aid, especially for cognitively impaired patients requiring as-
sistance with mobilisation, which is consistent with findings
in a previous study.18 In general, there is a scarce amount of
literature currently available on the use of the TLMS in the
rehabilitation setting.

A surprising outcome of the TLMS was that it also re-
sulted, subjectively, in increased levels of patient motivation
due to its role in contributing to patient goal setting, which in
itself is also an important part of the rehabilitation process.19
Since its implementation, numerous patients have celebrated
‘advancing a level’ in their mobility from red to yellow to
green, with others making the goal to advance to the desired
‘green tag’ level within a certain amount of time.

One limitation was the small sample size secondary to
the constrained time frame. To audit again after a period of
12 months would increase the sample size and highlight any
changes that might arise with the inclusion of data from the
winter months, which is consistently associated with a higher
number of patient admissions to our hospital.

Another limitation is that the data in this study were based
on existing IIMS reports, which varied in quality due to the
staff member making the report and the circumstances of
the fall, some of which were unwitnessed. Subjectively, the
quality of information provided did show improvement in the
post-intervention audit.

5 | C O N C L U S I O N
Due to the association of falls with increased morbidity and
mortality, falls prevention and reduction remain an important
part of a patient’s hospital admission. Patients with the fol-
lowing characteristics had higher rates of falls in both audits:
male, cognitively impaired, age over 65 years, a diagnosis of
stroke and requiring assistance with mobilising and personal
care.

Key interventions included the implementation of a
TLMS to provide visual aids for mobility, increased com-
pliance with existing falls risk tools and the improved docu-
mentation of each falls incident which provided insight into
activities and times with higher falls risk. These results are
promising in that a multicomponent approach was shown to
remain effective even when applied to a mixed acute/reha-
bilitation ward setting. This study demonstrated inexpensive
and simple ways of addressing falls risk when dealing with a
heterogeneous patient population.

AC K N OW L E D G E M E N T S
None.

C O N F L I C T S O F I N T E R E S T
None to declare.

AU T H O R C O N T R I B U T I O N S
Colleen Ma contributed to the design, acquisition, analysis
and interpretation of the data and drafted the work. Rebecca
Morrissey contributed to the design, analysis and interpreta-
tion of the data and made critical revisions of the draft. Both

| 413MA And MORRISSEY
contributors have given final approval of the version to be
published and agree to be accountable for all aspects of the
work.

O RC I D
Colleen Lok Kum Ma  https://orcid.
org/0000-0003-2125-1485
Rebecca Ann Morrissey  https://orcid.
org/0000-0003-2060-1594

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How to cite this article: Ma CLK, Morrissey RA.
Reducing falls through the implementation of a
multicomponent intervention on a rural mixed
rehabilitation ward. Aust J Rural Health.
2020;28:408–413. https://doi.org/10.1111/ajr.12646

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