Please read directions carefully!!! all components must be entered ( must be familiar with excel )
Before beginning this assignment, read Chapter 12 in Clinical Analytics and Data Management for the DNP. (its attached) start at chp 12
Use the “Data Collection Sheet Template, (its attached)
- Using the “Data Collection Sheet Template,” create a data dictionary for your DPI Project. Refer to the examples within the template.
- Click on the Data Dictionary tab.
- Include all data variables (data points) that will be collected for your DPI Project, ( see attached) including demographics and any surveys, instruments, and tools. (Refer to Chapter 12 in Clinical Analytics and Data Management for the DNP for examples, as needed.)
- Include descriptions for the variable name, variable description, data source, level of measurement, possible values, SPSS coding instructions, and missing values.
- Using the “Data Collection Sheet Template,” create your own template for your DPI Project. Please note that you are not collecting data for your DPI Project for this assignment.
- Click on the Data Collection Sheet tab.
- Edit Row 1 to match the variable names in the data dictionary.
- Edit Row 2 to include example responses for each variable.
I have attached the variable to be included in the table –
I have included the primary article for this DPI project to reference
Please read directions carefully!!! all components must be entered ( must be familiar with excel ) Before beginning this assignment, read Chapter 12 in Clinical Analytics and Data Management for the
Please include these variables- then distinguish among nominal, ordinal, interval, and ratio per example in chapter 12 age, gender, race Hispanic Non-Hispanic African American Caucasian Other Date admitted to LTACH HOU LOS (number) Hospital LOS (number) Avg daily cost of hospitalization Primary dx: sepsis, resp, cardiovascular, GI, Renal , other restraints (y,n) pain medication ordered, (Y,N) sedative ordered (y,N) Therapy services: PT (Y/N) OT (y/N) ST (y/N) JH-HLM score (number) Safe Patient Handling Equipment 1-hoyer 2- person assist 3-sliding board Days on Mechanical Ventilation (DOMV) Days on Trache collar (number) Bedside checklist completed (y.n) Family Present (y,n) Staff Pre bundle assessment completed Post bundle assessment completed Number of passing score Staff demographic Surveys completed( number) Gender Age Degree type: RN BSN MSN CNA RT Years of RN experience (. ) Years of LPN experience (. ) Years of CNA experience (. ) Years of RT experience (. ) Any experience working the A2F bundle How comfortable are you performing the daily functions of your job (using Likert scale)
Please read directions carefully!!! all components must be entered ( must be familiar with excel ) Before beginning this assignment, read Chapter 12 in Clinical Analytics and Data Management for the
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All Rights Reserved. Feature Articles Critical Care Medicine www.ccmjournal.org 885 Objectives: To measure the impact of staged implementation of full versus partial ABCDE bundle on mechanical ventilation dura- tion, ICU and hospital lengths of stay, and cost. Design: Prospective cohort study. Setting: Two medical ICUs within Montefiore Healthcare Center (Bronx, NY). Patients: One thousand eight hundred fifty-five mechanically ventilated patients admitted to ICUs between July 2011 and July 2014. Interventions: At baseline, spontaneous (B)reathing trials (B) were ongoing in both ICUs; in period 1, (A)wakening and (D)elir- ium (AD) were implemented in both full and partial bundle ICUs; in period 2, (E)arly mobilization and structured bundle (C)oordina- tion (EC) were implemented in the full bundle (B-AD-EC) but not the partial bundle ICU (B-AD). Measurements and Main Results: In the full bundle ICU, 95% patient days were spent in bed before EC (period 1). After EC was implemented (period 2), 65% of patients stood, 54% walked at least once during their ICU stay, and ICU-acquired pressure ulcers and physical restraint use decreased (period 1 vs 2: 39% vs 23% of patients; 30% vs 26% patient days, respectively; p < 0.001 for both). After adjustment for patient-level covariates, im- plementation of the full (B-AD-EC) versus partial (B-AD) bundle was associated with reduced mechanical ventilation duration (–22.3%; 95% CI, –22.5% to –22.0%; p < 0.001), ICU length of *See also p. 997.1Division of Pulmonary, Critical Care, and Sleep Medicine, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY. 2Division of Pulmonary Diseases, Critical Care, and Environmental Medi-cine, Department of Medicine, Tulane University School of Medicine, New Orleans, LA. 3Division of Pulmonary, Allergy, Critical Care, and Sleep Medicine, Depart- ment of Medicine, University of Miami, Miller School of Medicine, Miami, FL. 4Division of Critical Care Medicine, Department of Medicine, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY. 5Division of Pulmonary Diseases and Critical Care, Department of Med-icine, University of Texas Health Sciences Center at San Antonio, San Antonio, TX. 6Department of Nursing, Montefiore Healthcare Center, Bronx, NY.7Department of Physical Medicine and Rehabilitation, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY. 8Occupational Therapy Assistant Program, Health Sciences Depart-ment, LaGuardia Community College, Long Island City, NY. 9Division of Pulmonary Medicine, Department of Medicine, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY. 10Network Performance Group, Montefiore Medical Center, Yonkers, NY.11Department of Epidemiology and Population Health, Albert Einstein Col- lege of Medicine, Bronx, NY. Drs. Hsieh and Gong conceptualized and designed the study. Drs. Hsieh, Otusanya, Gershengorn, Hope, Dayton, Prince, Mills, Fein, Colman, and Gong acquired, analyzed, and interpreted the data. Drs. Hsieh, Otusanya, Gershengorn, Hope, and Gong drafted the article for important intellec- tual content. Supplemental digital content is available for this article. Direct URL cita- tions appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s website (http://journals.l ww.com/ ccmjournal). Supported, in part, by 8KL2TR0000088-05 from the Albert Einstein Col- lege of Medicine - Montefiore Medical Center Institute for Clinical an d Translational Research (to Dr. Hsieh), R03AG050927 (to Dr. Hope), Na- tional Heart, Lung, and Blood Institute HL084060 and HL086667 (to Dr. Gong); 1 UL1 TR001073-01, 1 TL1 TR001072-01, 1 KL2 TR001071-01 (Einstein-Montefiore Clinical and Translational Science Awards). Drs. Hsieh, Hope, and Gong received support for article research from the National Institutes of Health (NIH). Dr. Hsieh’s institution received funding from Einstein-Montefiore Institute for Clinical and Translational Research DOI: 10.1097/CCM.0000000000003765 Staged Implementation of Awakening and Breathing, Coordination, Delirium Monitoring and Management, and Early Mobilization Bundle Improves Patient Outcomes and Reduces Hospital Costs* S. Jean Hsieh, MD, MS 1; Olufisayo Otusanya, MD 2; Hayley B. Gershengorn, MD 3; Aluko A. Hope, MD, MScE 4; Christopher Dayton, MD 5; Daniela Levi, MD 4; Melba Garcia, BSN 6; David Prince, MD 7; Michele Mills, MA, OTR 8; Dan Fein, MD 9; Silvie Colman, PhD 10; Michelle Ng Gong, MD, MS 4,11 and La Jolla Pharmaceutical. Dr. Gong’s institution received funding from NIH grants and Philips Healthcare. The remaining authors have disclosed that they do not have any potential conflicts of interest. This work was performed at Montefiore Healthcare Center. Address requests for reprints to: Michelle Ng Gong, MD, MS, Division of Critical Care Medicine, Department of Medicine, Montefiore Medical Center, 111 East 210th Street, Bronx, NY 10467. E-mail: [email protected] tefiore.org Copyright © 2019 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved. Copyright © 2019 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved. Hsieh et al 886 www.ccmjournal.org July 2019 • Volume 47 • Number 7 stay (–10.3%; 95% CI, –15.6% to –4.7%; p = 0.028), and hos- pital length of stay (–7.8%; 95% CI, –8.7% to –6.9%; p = 0.006). Total ICU and hospital cost were also reduced by 24.2% (95% CI, –41.4% to –2.0%; p = 0.03) and 30.2% (95% CI, –46.1% to –9.5%; p = 0.007), respectively. Conclusions: In a clinical practice setting, the addition of (E)arly mobilization and structured (C)oordination of ABCDE bundle components to a spontaneous (B)reathing, (A)wakening, and (D) elirium management background led to substantial reductions in the duration of mechanical ventilation, length of stay, and cost. (Crit Care Med 2019; 47:885–893) Key Words: critical care; delirium; early mobilization; implementation; mechanical ventilation I CU-acquired delirium and weakness can lead to dev- astating cognitive and physical impairments and psy- chiatric symptoms in ICU survivors, also known as “post-intensive care syndrome” (1–6). The (A)wakening and (B)reathing, (C)oordination, (D)elirium monitoring and management, and (E)arly mobilization (ABCDE) bundle (7, 8) is an interdisciplinary patient-centered evidence-based strategy endorsed by critical care societies and national quality improvement agencies to prevent and reduce ICU delirium and weakness, and operationalize the Society of Critical Care Medicine’s Pain, Agitation, and Delirium clin- ical practice guidelines (9–13). Individual components of the ABCDE bundle are asso- ciated with substantial benefits in research settings (14–20). Although studies in clinical practice settings suggest that im- plementation of the full ABCDE bundle is associated with clinical benefits, its uptake has been limited and implemen- tation often-incomplete (21–28). Sequential implementa- tion of bundle components may improve overall execution by allowing providers to: 1) maximize efficacy of imple- mentation by focusing on individual components, 2) assess process improvement by performing stepwise evaluation of components, and 3) make practice adjustments before mov- ing to the next component. In addition, studies suggest that the efficacy of early mobilization can be maximized if pro- grams to reduce unnecessary sedation and delirium are al- ready in place (25, 29). Accordingly, we sought to determine the impact of add- ing EC to B-AD in the context of staged implementation of the ABCDE bundle in mechanically ventilated (MV) patients. We hypothesized that implementation of early mobilization on a foundation of targeted sedation practices and routine de- lirium monitoring would improve clinical outcomes and re- duce hospital cost. Preliminary results have been presented in abstract form (30, 31). MATERIALS AND METHODS See Supplemental Appendix (Supplemental Digital Content 1, http://links.lww.com/CCM/E506) for a more detailed descrip- tion of study procedures. Study Design and Setting This prospective study took place in two academic medical ICUs at Montefiore Medical Center (Bronx, NY). ICUs had the same size (14 beds) and staffing (two patients per nurse, 24 hr onsite intensivist coverage), except the full bundle ICU was staffed by medical residents and the partial bundle ICU by physician assistants. The Institutional Review Board (IRB) approved a waiver of informed consent (IRB number 2014–3466). Cohort Our primary cohort consisted of all MV adults (≥ 18 yr) admit- ted to the ICUs for greater than or equal to 24 hours between July 1, 2011, and June 30, 2014 (Fig. 1). This cohort was used for analyses of clinical outcomes; alternative cohorts were used for process of care and cost outcomes (Fig. S1 and text in Sup- plemental Appendix, Supplemental Digital Content 1, http:// links.lww.com/CCM/E506). Implementation Stages Interdisciplinary teams of critical care nursing, physician, phar - macy, respiratory therapy, and rehabilitation leadership and champions developed and implemented bundle components. (A)wakening and (D)elirium Monitoring/Management (AD) (Both ICUs). At baseline, both ICUs used MV order sets that included daily sedation vacations and spontaneous (B) reathing trials (B) (Fig. 1); however, no guidance was given on performance or coordination of these bundles. Beginning in January 2012, the (A)wakening from sedation and (D)elirium monitoring/management (AD) bundles were implemented in both ICUs; this included physician-directed targeted sedation using the Richmond Agitation and Sedation Scale (32, 33), twice daily delirium assessments using the Confusion Assess- ment Method-ICU by nurses (32, 34), and suggestions for nonpharmacologic delirium reduction methods. To account for time to adopt these changes, AD bundles were considered fully implemented by July 1, 2012. (E)arly Mobilization and (C)oordination of Components (EC): (Full Bundle ICU Only). (E)arly mobilization (E) con- sisted of evaluation by physical therapy (PT) and occupational therapy (OT) at ICU admission, and daily rehabilitation by PT and/or OT according to a staged protocol in which patients ad- vanced from passive range of motion to independent ambula- tion with respiratory therapy and nursing assistance as needed (17, 35) (Fig. S3, Supplemental Digital Content 1, http://links. lww.com/CCM/E506). As part of this bundle, daily structured interdisciplinary rounds were established for ICU nurses, res- piratory therapists, and rehabilitation staff to (C)oordinate bundle components (C), diagnostic tests and procedures. On July 1, 2013, EC were implemented in the full bundle ICU only because of resource and staffing limitations. Data Collection Clinical data were extracted from electronic medical records using healthcare surveillance software (Clinical Looking Glass; Emerging Health Information Technology, Yonkers, Copyright © 2019 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.Feature Articles Critical Care Medicine www.ccmjournal.org 8 87 NY ). To determine if practices changed after ICU-wide implementation of bundle components, we also examined process of care data (Fig. 1; and Fig. S1 and text in Supple- mental Appendix, Supplemental Digital Content 1, http:// links.lww.com/CCM/E506). Outcomes Clinical Outcomes. The primary outcome of interest was the hospital length of stay (LOS) after the index ICU admission (i.e., ICU LOS + post-ICU LOS). Secondary outcomes included ICU LOS, duration of MV, hospital mortality, and discharge location. Cost Outcomes. Total hospital and ICU cost and average daily ICU cost (i.e., total cost divided by ICU LOS) were de- termined using cost-to-charge ratios at Montefiore Medical Center. Because cost-to-charge ratios differ by calendar year, the cohort in the cost analyses was limited to patients with hospitalizations that ended between January 1, 2012, and De- cember 31, 2013. Costs were calculated as the sum of daily direct variable costs from cost centers related to inpatient, nonoperative care (e.g., respiratory support, room and board, laboratory, medications) as previously described (37). Clinical Quality Outcomes. Clinical quality metrics that may be affected by implementation of the ABCDE bundle (e.g., ICU restraint use, prevalence of ICU-acquired pressure ulcers) were obtained from aggregate hospital-reported data for Cen- ters for Medicare and Medicaid Services quality indicators in both full and partial bundle ICUs. Data were only available for periods 1 and 2. Statistical Analysis Patient characteristics and unadjusted clinical outcomes were compared across ICUs and time periods using standard de- scriptive statistics. Nonparametric tests were used for skewed continuous measures. To evaluate the impact of EC on clinical and cost out- comes, we compared trends in these outcomes in the full versus partial bundle ICUs before and after EC implemen- tation using a multivariable difference-in-differences (DiD) approach (38, 39). This methodology uses a multivariable regression model that includes an interaction term for “time period” (e.g., period 1 vs 2) and “ICU” (full vs par - tial bundle) that measures the magnitude of the effect of EC Figure 1. Timeline of staged implementation of ABCDE in partial (B-AD only) versus full (B-AD-EC) bundle ICUs and data measurement periods. A, Periods of component implementation in the full and partial bundle ICUs. At baseline, spontaneous (B)reathing trials were ongoing in both full and partial bundle ICUs; on July 1, 2012, (A)wakening and (D)elirium monitoring/managemen t were implemented in both ICUs; on July 1, 2013, (E)arly mo- bilization and structured bundle (C)oordination were implemented in only the full bundle ICU. B, Periods in which process of care, clinical outcomes, and cost data were collected relative to bundle implementation. aProcess of care measurements (sedative use, delirium prevalence, maximum level of mobility) were compared across time in the full bundle ICU (B-AD-EC) only. bICU quality indicators, clinical outcomes, and cost were compared across t ime in both the full (B-AD-EC) and partial (B-AD) bundle ICUs. cCost periods were truncated because cost data are calculated based on a cost-to-charge ratio which varies between calendar years. The following periods were compared for the cost analysis: 1) baseline v ersus period 1 (i vs ii) and 2) period 1 versus pe - riod 2 (iii vs iv). A = awakening from sedation, B = spontaneous breat hing trial, C = structured coordination of bundle components, D = deliri um monitor - ing and management, E = early mobilization. Copyright © 2019 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved. Hsieh et al 888 www.ccmjournal.org July 2019 • Volume 47 • Number 7 (Fig. 1). In contrast to standard before-after studies, DiD controls for temporal trends in patient characteristics (e.g., increasing severity of illness) that might impact outcomes. DiD analyses are based on four assumptions to ensure va- lidity of the model, the most important of which is the parallel trend assumption (i.e., prior to interventions, tem- poral changes in outcomes for both ICUs are similar) (38). To test this assumption, separate regression models were constructed for each outcome in the baseline period (for B vs B-AD analysis) and period 1 (for B-AD vs B-AD-EC analysis); models included interaction terms for ICU admis- sion date and ICU. We also performed sensitivity analyses to determine if including patients with hospital LOS greater than 90 would alter our estimates. Although AD was imple- mented in both units, we used DiD (baseline vs period 1) to evaluate for differential impact of AD implementation on clinical outcomes between ICUs. All models were adjusted for patient-level characteristics that differed between ICUs (univariable p ≤ 0.2). Because Acute Physiology and Chronic Health Evaluation (APACHE) IV scores were missing in 10% of patients, we used dummy variable adjustment (40). All tests were two-tailed and p value of less than 0.05 de- fined statistical significance. Analyses were performed with STATA/MP 13 (Statacorp, College Station, TX). TABLE 1. Patient Characteristics in Partial (B-AD) Versus Full Bundle (B-AD-EC) ICUs Across Implementation Periods Patient Characteristic Baseline Period 1 Period 2 B Ongoing in Both ICUs B-AD in Both ICUs B-AD in Partial Bundle ICU; B-AD-EC in Full Bundle ICU Partial Bundle ICU, n = 267 Full Bundle ICU, n = 356 Partial Bundle ICU, n = 271 Full Bundle ICU, n = 314 Partial Bundle ICU, n = 281 Full Bundle ICU, n = 366 Age a, mean ( sd) 64 (5 74) 64 (5 75)66 (5 77) 64 (5 75)67 (5 78) c 61 (5 73) c Male, % 49464846 4551 Race, % c cc c White 221833213317 Black 3735273330 35 Multiracial 303230 342837 Other 111510111011 Hispanic ethnicity, % 33 c 42 c 373929 c 42 c Resided at home, % 79 c 70c 82 c 74c 8076 Admit from Ed, % a 66 6779 c 68 c 78c 69 c Charlson Comorbidity Index, median (IQR) 0 ( 1) 0 ( 2) 0 ( 2)0 ( 2)0 ( 1) c 0 ( 2) c Acute Physiology and Chronic Health Evalu- ation IV, median (IQR) b,d 59 (4 76) 59 (4 77) 61 (4 77)62 (4 77)66 (5 86) 72 (5 90) Primary admitting diagnosis, % sepsis 5248 5449 5549 Respiratory 181917221517 Cardiovascular 444345 Gastrointestinal 355877 Endocrine/renal 341344 Other 211918161518 A = awakening from sedation, B = spontaneous breathing trial, C = coordination of bundle components, D = delir ium monitoring and management, E = early mobilization, IQR = interquartile range. a Partial bundle ICU between three periods, p ≤ 0.04.b Full bundle ICU between three periods, p < 0.001.c Partial vs full bundle ICU within period, p < 0.01.d Test for trend across three periods within partial and full bundle ICU, p ≤ 0.001. Multiple comparisons are being made in this table. Interpretive example: 1) patients were younger in full bundle ICU vs partial bundle ICU and 2) severity of illness increased over time in both partial and full bundle ICUs. Copyright © 2019 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.Feature Articles Critical Care Medicine www.ccmjournal.org 889 RESULTS Patient Characteristics Between July 1, 2011, and June 30, 2014, 1,855 MV patients were admitted to the full (1,036, 56%) and partial bundle (819, 44%) ICUs. The full bundle ICU had younger patients and more minorities (Table 1). Patients in the full bundle ICU also had more comorbidities, higher severity of illness, and fewer lived at home prior to hospitalization. Severity of illness (APACHE IV) increased across periods in both ICUs (p ≤ 0.001). Process of Care Evaluation (Full Bundle ICU Only) Sedative Use and Delirium Prevalence (Fig. S2, Supple- mental Digital Content 1, http:// links.lww.com/CCM/E506). In the rull bundle ICU, the pro- portion of patients receiving continuous sedation decreased across all three periods (p < 0.001 for midazolam and fen- tanyl; p = 0.06 for propofol) (Fig. S3A , Supplemental Digital Con- tent 1, http://links.lww.com/ CCM/E506). The proportion of patients with ICU delirium and/ or coma also decreased across all three periods (p ≤ 0.02) and similar to sedative use, the larg- est decrease occurred after AD was implemented (Fig. S3B , Supplemental Digital Content 1, http://links.lww.com/CCM/ E506). ICU Mobility. After EC was implemented in the full bundle ICU (period 1 vs 2), the pro- portion of patients evaluated by the rehabilitation team (i.e., either PT and/or OT) increased from 19% to 90% and the pro- portion of patient days spent passively lying or sitting in bed decreased from 95% to 37%. Patients received rehabilitation therapy within 1 day of ICU ad- mission (median ICU day 1; in- terquartile range [IQR], 0–1) for a median of 60% of all ICU days (IQR, 50–80%); 77% of patients dangled at the bed’s edge, 65% stood, and 54% walked at least once during their ICU stay. No serious complications occurred during the 1,345 rehabilitation treatments. The main reasons why patients did not receive reha- bilitation therapy were lack of staff and clinical instability (61% and 29% of patient days with no rehabilitation, respectively). Outcomes Clinical Quality Outcomes. The proportion of patients with ICU-acquired pressure ulcers decreased (39% to 23%; p < 0.001) and the proportion of ICU patient days in restraints Figure 2. Clinical quality outcomes in full and partial bundle ICUs (periods 1 vs 2). Quality metrics from ag- gregate hospital-reported data Centers for Medicare and Medicaid Service s quality indicators were compared between periods 1 versus 2 in both full and partial bundle ICUs. A, In the full bundle ICU (B-AD vs B-AD-EC), pressure ulcer incidence and physical restraint use decreased (p < 0.001 for both). B, In the partial bundle ICU (B-AD vs B-AD), pressure ulcer incidence and physical restraint use in creased ( p = 0.04; p = 0.001, respec- tively). A = awakening from sedation, B = spontaneous breathing trial, C = structured coordination of bundle components, D = delirium monitoring and management, E = early mobilizati on. Copyright © 2019 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved. Hsieh et al 890 www.ccmjournal.org July 2019 • Volume 47 • Number 7 decreased (30% to 26%; < 0.001) after implementation of EC in the full bundle ICU (period 1 vs 2; Fig. 2A). In contrast, the prevalence of ICU-acquired pressure ulcers increased (18% to 23% of patients; p = 0.04) and proportion of ICU days in restraints increased (50% to 54%; p = 0.001) in the partial bundle ICU during the same periods of time (Fig. 2B). Clinical Outcomes. Duration of MV and ICU LOS signifi- cantly changed in the full bundle ICU but not in the partial bundle ICU across three periods (Table 2). The duration of MV was sig- nificantly shorter in period 2 in the full versus partial bundle ICU, and ICU LOS was significantly shorter across all three periods in the full versus partial bundle ICU (p < 0.001). Hospital LOS and hospital mortality did not differ across all periods in both ICUs. In our DiD analyses, implementation of AD in both full bundle and partial bundle ICUs was associated with no signifi- cant changes in clinical outcomes, except for increased hospital LOS in the full versus partial bundle ICU (5.9%; 95% CI, 4.6– 7.2%; p = 0.011) (Table 3). Implementation of EC in the full bundle ICU after AD was associated with a 22.3% decrease in duration of MV (95% CI, –22.5% to –22.0%; p < 0.001), a 10.3% decrease in ICU LOS (95% CI, –15.6% to –4.7%; p = 0.028), and a 7.8% decrease in hospital LOS (95% CI, –8.7% to –6.9%; p = 0.006) compared with the partial bundle ICU (Table 3). The parallel trend assumption was met for all outcomes except for hospital LOS in period 1, where hospital LOS increased more in the full versus partial bundle ICU (0.17% change per calendar day; 95% CI, 0.10–0.24%; p = 0.022) (Table S2, Supplemental Digital Content 1, http://links.lww.com/CCM/E506). Sensitivity analyses including patients with hospital LOS greater than or equal to 90 days (n = 28, who had been excluded from our pri- mary cohort) revealed similar results (Table S3, Supplemental Digital Content 1, http://links.lww.com/CCM/E506). Cost Outcomes. In DiD analyses, implementation of AD in both full and partial bundle ICUs was associated with no sig- nificant changes in cost between the two units (Table 3). Im- plementation of EC in only the full bundle ICU was associated with a 24.2% reduction in total ICU cost (95% CI, –41.4% to –2.0%; p = 0.034; Table 3) and a 30.2% reduction in total hos- pital cost (95% CI, –46.1% to –9.5%; p = 0.007) in the full versus partial bundle ICU; there was no reduction in average daily ICU cost (4.4%; 95% CI, –4.5% to 14.1%; p = 0.342). The parallel trend assumption was met for all cost outcomes (Table S2, Supplemental Digital Content 1, http://links.lww. com/CCM/E506). TABLE 2. Clinical Outcomes in Partial (B-AD) Versus Full Bundle (B-AD-EC) ICUs Across Implementation Periods Clinical Outcome Baseline Period 1 Period 2 B Ongoing in Both ICUs B-AD in Both ICUs B-AD in Partial Bundle ICU; B-AD-EC in Full Bundle ICU Partial Bundle ICU, n = 267 Full Bundle ICU, n = 356 Partial Bundle ICU, n = 271 Full Bundle ICU, n = 314 Partial Bundle ICU, n = 281 Full Bundle ICU, n = 366 Duration of mechanical ventilation (d), median (IQR) a 5 (3–11) 4 (3–9)5 (3–10) 5 (3–10)6 (3–11) b 4 (2–7) b ICU LOS (d), median (IQR) a 6.9 (3.4–12.7) b 5.0 (3.0–10.3) b 7.6 (4.7–13.0) b 6.2 (3.9–11.7) b 6.9 (3.8–13.3) b 5.0 (3.0–9.3) b Hospital LOS (d), median (IQR) c 13.2 (6.6–22.9) 12.2 (7.0–21.5)13.4 (8.9–21.9) 13.9 (8.0–24.4)14.0 (7.7–24.2)13.3 (7.1–23.3) Hospital mortality, % 222530 262830 Discharge location, % b b Home 464546 484348 Rehabilitation 634 253 Skilled nursing facility 4246 41 464441 Acute care hospital 134 044 Hospice 114 021 Left against medical advice 3 22 313 A = awakening from sedation, B = spontaneous breathing trial, C = coordination of bundle components, D = delir ium monitoring and management, E = early mobilization, IQR = interquartile range, LOS = length of stay. a Full bundle ICU across three periods, p < 0.001; partial bundle ICU did not significantly differ across three periods.b Partial vs full bundle ICU within period, p ≤ 0.01.c Hospital LOS defined as index ICU LOS + post-ICU LOS. Multiple comparisons are being made in this table. Interpretive example: 1) duration of mechanical ventilation in period 2 was shorter in the full vs partial bundl e ICU and 2) duration of mechanical ventilation significantly differed across three periods in the full bundle ICU. Copyright © 2019 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved.Feature Articles Critical Care Medicine www.ccmjournal.org 891 DISCUSSION This is the first large-scale prospective quality improvement study demonstrating the value of staged implementation of a bundle of evidence-based interventions aimed at reducing ICU associated weakness and delirium. We showed that the addition of (E)arly mobilization and structured interdiscipli- nary (C)oordination of bundle components to a spontaneous (B)reathing trial, (A)wakening from sedation, and (D)elirium monitoring/management program (B-AD + EC), is feasible, associated with improvements in quality of care, and is inde- pendently associated with substantial reductions in MV dura- tion, ICU LOS, hospital LOS, and cost savings after adjusting for secular trends and patient-level confounders. Our findings complement the growing literature demonstrat- ing the clinical benefit of ABCDE bundle (25, 41). Simultaneous implementation of ABCDE/F bundle components has been associated with increased hospital survival and delirium and coma-free days, and reduced duration of MV (21–23). Studies suggest that ABCDE, and early mobilization in par - ticular, can be challenging to implement in routine practice (24–26, 42). Over 100 unique barriers have been identified in recent literature reviews (43). Dubb et al (44) classified these barriers into four categories: patient-related (e.g., deep seda- tion, delirium, new immobility/weakness), structural (e.g., lack of mobility protocol, limited staff and equipment, inadequate training), process related (e.g., lack of coordination), and cul- tural (e.g., lack of ICU mobility culture, staff buy-in, expertise). The positive outcomes in our study may be explained by our use of strategies specifically targeting these barriers, including: 1) reducing sedative use and delirium (B-AD, period 1) “be- fore” implementation of EC (period 2) so patients were more awake and could actively engage in mobilization; 2) mobiliza- tion of patients within 1 day of ICU admission to prevent the development of new immobility/weakness; 3) developing an interdisciplinary mobility protocol with prespecified roles and responsibilities before EC implementation; 4) obtaining admin- istrative buy-in to finance dedicated rehabilitation staff and re- habilitation equipment; 5) interdisciplinary simulation training of mobilization scenarios to enhance skills, improve interdisci- plinary communication, and increase buy-in; 6) daily interdis- ciplinary coordination of staff and bundle components; and 7) including local nursing, respiratory, rehabilitation champions in protocol development, training, and dissemination. Our large effect size may also be explained by our use of DiD analysis which mitigates against secular trends that can con- found pre-post study designs (21, 23). In addition, prior studies implemented bundle components all at once, which may reduce overall bundle compliance and offset clinical benefit if com- ponents are not fully adopted (25, 45). Barnes-Daly et al (22) showed that for every 10% increase in ABCDEF bundle com- pliance, odds for hospital survival increased by 7%. Finally, our study excluded non-MV patients from analysis since only a frac- tion of the bundle (i.e., D, E) applies to them. Their inclusion in prior studies may have diminished any effect seen (21, 23). TABLE 3. Difference-in-Differences Estimates of Change in Clinical and Cost Outc omes After AD Implementation (Baseline vs Period 1) and EC Implementation (Period 1 vs Period 2) in Mechanically Ventilated Patients a Outcome Measure Full Bundle ICU Minus Partial Bundle ICU Baseline vs Period 1 % Change (95% CI) (B minus B-AD) pPeriod 1 vs Period 2 % Change (95% CI) (B-AD minus B-AD-EC) p Clinical outcomes Duration of mechanical ventilation 7.2 (–3.3 to 18.9) 0.07–22.3 (–22.5 to –22.0) < 0.001 ICU LOS 3.0 (–6.5 to 13.5)0.16–10.3 (–15.6 to –4.7) 0.03 Hospital LOS b 5.9 (4.6–7.2) 0.01–7.8 (–8.7 to –6.9) 0.006 Cost outcomes Average daily ICU cost 2.69 (–4.9 to 10.9)0.504.4 (–4.5 to 14.1) 0.34 Total ICU cost –0.47 (–22.3 to 27.4)0.97–24.2 (–41.4 to –2.0) 0.03 Total hospital cost –0.06 (–21.4 to 27.0)0.10–30.2 (–46.1 to –9.5) 0.007 A = awakening from sedation, B = spontaneous breathing trial, C = coordination of bundle components, D = delir ium monitoring and management, E = early mobilization, LOS = length of stay. a Both models are adjusted for age, race, ethnicity, prehospital residence, admission location, Charlson Comorbidity Index, primary ad mitting diagnosis, and Acute Physiology and Chronic Health Evaluation IV. b Hospital LOS defined as index ICU LOS + post-ICU LOS. Baseline vs period 1 compares clinical and cost outcomes after AD was imp lemented in both full and partial bundle ICUs. Period 1 vs period 2 compares clinical and cost outcomes in full bundle vs partial bundle ICUs after EC was implemented in full bundle ICU only. Interpretive example: 1) implementation of AD in both ICUs was associated with no differential change in total hospital cost and 2) implementation of EC in full bundle ICU only was associated with a 7.8% reduction in hospital LOS. Copyright © 2019 by the Society of Critical Care Medicine and Wolters Kluwer Health, Inc. All Rights Reserved. Hsieh et al 892 www.ccmjournal.org July 2019 • Volume 47 • Number 7 This is the first report on the financial impact of the en- tire ABCDE bundle. Prior analyses on the awakening/de- lirium bundle components suggested cost savings, but studies on early mobilization have reported conflicting results (35, 46, 47). Using patient-level data, we found that adding EC to B-AD led to substantial cost savings which appear to be prima- rily explained by reductions in LOS (as indicated by decreased overall costs but unchanged average daily ICU cost before and after EC implementation). Our finding that EC implementation was associated with shorter ICU and hospital LOS is consistent with prior random- ized controlled trials (RCTs) and quality improvement studies (17, 35, 48). However, two recent RCTs on early mobilization found no effect on hospital LOS. In Morris et al (49), a seda- tion protocol was not used, which may have limited the effi- cacy of spontaneous breathing trials and early mobilization. In Moss et al (50), mobilization was initiated 8 days after ICU admission (vs 1 d in this study). Given the rapid degradation of muscle of critically ill patients, mobilization may be less effec- tive if initiated after muscle loss has occurred (4). Our study highlights several areas for future research. These include assessment of patient-centered outcomes such as short and long-term disability and readmission rate, determination of return on investment, cost analyses accounting for payer status, and evaluation of bundle dissemination and sustaina- bility. The ABCDE bundle has been reframed since our 2014 study to include assessment, management and prevention of pain, and (F)amily empowerment and engagement (“F” in ABCDEF) (28). Future studies will need to reconcile our find- ings with the updated components. This study has several strengths. Our DiD approach allowed us to adjust for secular trends which could have confounded prior historically-controlled studies. We also fulfilled a ma- jority of the rigorous assumptions required for internal va- lidity of the DiD estimates. Our cost data were generated from costs attributed to individual patients rather than assumptions based on average published costs. Finally, our study evaluated one of the largest cohorts to date. This study has some limitations. Despite adjusting for patient characteristics, unmeasured differences and/or changes in cohort composition could have impacted our results. We also did not in- clude discharge location in our model. Our study was conducted in a single medical center, which may limit generalizability. For example, the bundle’s impact on quality metrics (e.g., pressure ulcers) may be greater in ICUs with higher rates at baseline than sites that have already achieved low rates. There was potential for cross-contamination of practices between the two ICUs. However, cross-contamination would have biased the estimates toward the null. Because cost-to-charge ratios change across cal- endar years, we were unable to compare costs between the same seasonal periods and needed to use a smaller cohort for the cost analyses. Although changes in processes of care were demon- strated in the full bundle ICU, data were not collected in the par - tial bundle ICU for comparison. Finally, we were unable to fulfill the parallel trend assumption for hospital LOS as it increased in the full bundle ICU relative to the partial bundle ICU in period 1. However, this would bias our findings “toward the null” making it more difficult to demonstrate subsequent decreased hospital LOS after EC implementation in period 2. Because hospital LOS decreased despite this bias, our results may underestimate the full impact of ABCDE bundle implementation. CONCLUSIONS This study demonstrates that the complex ABCDE bundle can be successfully implemented into routine care. We showed that the addition of early mobilization and bundle coordination to an established targeted sedation and de- lirium management program led to substantial reductions in MV duration, LOS, and hospital cost, liberated patients from restraints, and reduced iatrogenic complications. 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Moss M, Nordon-Craft A, Malone D, et al: A randomized trial of an intensive physical therapy program for patients with acute respiratory failure. Am J Respir Crit Care Med 2016; 193:1101–1110 Please read directions carefully!!! all components must be entered ( must be familiar with excel ) Before beginning this assignment, read Chapter 12 in Clinical Analytics and Data Management for the 1519285 - S prin ger P ublis h in g C om pany © 1519285 - S prin ger P ublis h in g C om pany © 1519285 - S prin ger P ublis h in g C om pany © S U M MARY This chapte r e xp la in s th e pro cess of m ovin g fro m data colle ctio n to th e cre atio n of a ﬁnal a naly s is data s et. S yn ta x is hig hlig hte d as a m eth od fo r d ocum entin g th e ste ps of th is pro cedure fro m im porta tio n of th e data set in to S PSS and th ro ughout th e re m ain in g ste ps of th e entir e data analy s is . T he m ost im porta nt goal in cre atin g th e ﬁnal a naly s is data set is th e achie ve m ent a nd m ain te nance of a hig h-q ualit y d ata set in w hic h erro rs have been id entiﬁ ed and m anaged, a nd th e stru ctu re achie ve s w hat w as outlin ed in th e orig in al d ata analy s is pla n. T his opera tio n is one of th e m ost tim e-c onsum in g and possib ly c um bers om e activ it ie s of d ata m anagem ent; h ow eve r, w hen done w ell, it p ave s th e path to hig h-q ualit y re sult s . EX ER CIS E 1 . D ata dic tio nary : 1 . U sin g th e fo rm at in Table 12.5 , c re ate a data dic tio nary fo r th e C apsto ne P ro je ct. 2 . U sin g syn ta x: 1 . U sin g a C apsto ne data set (o r th e sam ple data set p ro vid ed in th e supple m enta l m ate ria ls ), c om ple te th e fo llo w in g exe rc is es usin g S PSS. ( N ote : I f S PSS is not a va ila ble , t h is e xe rc is e can be exe cute d w it h any s oftw are used to m anage data . T he syn ta x ﬁ le can be m anually c re ate d in a M ic ro soft W ord docum ent a s th e ste ps in th e exe rc is e are exe cute d.) 1 . E nte r th e data in to S PSS. 2 . I n th e va ria ble vie w of th e data set • E nsure th at e ach va ria ble has a la bel a nd assig ned all p ossib le va lu e la bels . • E nsure th e appro pria te le ve l o f m easure m ent f o r e ach va ria ble . 1519285 - S prin ger P ublis h in g C om pany © 3 . C re ate a syn ta x ﬁ le to docum ent a ll o f th e subsequent re quir e m ents of th is e xe rc is e. U se com ments in th e syn ta x ﬁ le to describ e w hat is done. 4 . R un th e C odebook c om mand fo r e ach of th e pertin ent d em ogra phic , descrip tiv e , o r o utc om e va ria ble s. • I n S PSS, u se A naly ze, R eports , C odebook ( re m em ber th at th e syn ta x ﬁle should conta in docum enta tio n fo r th ese pro cesses). 5 . P la ce com ments in th e syn ta x ﬁ le th at d escrib e any p ertin ent ﬁ ndin gs as a re sult o f ru nnin g th e C odebook c om mand. F or in sta nce, a re th ere m is sin g data fo r a ny o f th e va ria ble s, a re all t h e va ria ble s id entiﬁ ed at th e appro pria te le ve l o f m easure m ent? 6 . R un fre quencie s fo r n om in al a nd ord in al v a ria ble s and descrip tiv e sta tis tic s fo r in te rv a l a nd ra tio le ve l v a ria ble s. • If c om parin g tw o gro ups (e it h er p re -/ p ostm easure m ent o r tw o in dependent g ro ups), r u n th e fre quencie s and descrip tiv e s by g ro up in addit io n to ove ra ll. 7 . P la ce com ments in th e syn ta x ﬁ le th at d escrib e any p ertin ent ﬁ ndin gs as a re sult o f ru nnin g fre quencie s and descrip tiv e s. 8 . C re ate a ﬁnal c le an copy o f th e syn ta x ﬁ le and th e outp ut ﬁ le . I t is im porta nt fo r th ese tw o docum ents to be unders ta ndable fo r s om eone w ho is not in tim ate ly in vo lv e d w it h th e pro je ct. R EFER EN CES Gero nto lo gy R esearc h G ro up. (2 017, M ay 2 3). G RG W orld Sup erc enta ria ns R ankin g s Lis t . R etrie ved fro m http :/ / w ww.g rg .o rg /s c/s cin dex.h tm l IB M . (2 016). IB M SPSS Sta tis tic s fo r W in d ow s, v ers io n 2 4.0 . A rm onk, N Y: A uth or. R etre iv ed fro m http s:/ / w ww.ib m .c o m /p ro ducts /s p ss-s ta tis tic s J ohns H opkin s U niv ers it y S ch ool o f N urs in g. (2 012, A ugust 3 1). D NP evid en ce tra n sla tio n pro je ct. “ N o pain pro vid es b ig gain s.” S cie nceD aily . R etrie ved fro m http :/ / w ww.s cie n ced aily .c o m /re le ases/2 012/0 8/1 20831130653.h tm