Integrating Social Determinants of Health in Machine Learning-Driven Decision Support for Diabetes Case Management: Protocol for a Sequential Mixed Methods Study.

BACKGROUND: The use of both clinical factors and social determinants of health (SDoH) in referral decision-making for case management may improve optimal use of resources and reduce outcome disparities among patients with diabetes. OBJECTIVE: This study proposes the development of a data-driven decision-support system incorporating interactions between clinical factors and SDoH into an algorithm for prioritizing who receives case management services. The paper presents a design for prediction validation and preimplementation assessment that uses a mixed methods approach to guide the implementation of the system. METHODS: Our study setting is a large, tertiary care academic medical center in the Deep South of the United States, where SDoH contribute to disparities in diabetes-specific hospitalizations and emergency department (ED) visits. This project will develop an interpretable artificial intelligence model for a population with diabetes using SDoH and clinical data to identify which posthospitalization cases have a higher likelihood of subsequent ED use. The electronic health record data collected for the study include demographics, SDoH, comorbidities, hospitalization-related factors, laboratory test results, and medication use to predict posthospitalization ED visits. Subsequently, a mixed methods approach will be used to validate prediction outcomes and develop an implementation strategy from insights into patient outcomes from case managers, clinicians, and quality and patient safety experts. RESULTS: As of December 2023, we had abstracted data on 174,871 inpatient encounters between January 2018 and September 2023, involving 89,355 unique inpatients meeting inclusion criteria. Both clinical and SDoH data items were included for these patient encounters. In total, 85% of the inpatient visits (N=148,640) will be used for training (learning from the data) and the remaining 26,231 inpatient visits will be used for mixed-methods validation (testing). CONCLUSIONS: By integrating a critical suite of SDoH with clinical data related to diabetes, the proposed data-driven risk stratification model can enable individualized risk estimation and inform health professionals (eg, case managers) about the risk of patients' upcoming ED use. The prediction outcome could potentially automate case management referrals, helping to better prioritize services. By taking a mixed methods approach, we aim to align the model with the hospital's specific quality and patient safety considerations for the quality of patient care and the optimization of case management resource allocation. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/56049.

The Integration of Quality Improvement and Health Care Simulation: A Scoping Review.

BACKGROUND AND OBJECTIVES: Quality improvement (QI) and simulation employ complementary approaches to improve the care provided to patients. There is a significant opportunity to leverage these disciplines, yet little is known about how they are utilized in concert. The purpose of this study is to explore how QI and simulation have been used together in health care. METHODS: This scoping review includes studies published between 2015 and 2021 in 4 databases: CINAHL, Embase, PubMed, and Scopus. RESULTS: The search yielded 921 unique articles.18 articles met the inclusion criteria and specifically described QI and simulation collaborative projects. Of the 18 articles, 28% focused on improvements in patient care, 17% on educational interventions, 17% on the identification of latent safety threats (LSTs) that could have an impact on clinical care, 11% on the creation of new processes, 11% on checklist creation, and 6% on both LST identification and educational intervention. The review revealed that 61% of the included studies demonstrated a concurrent integration of simulation and QI activities, while 33% used a sequential approach. CONCLUSIONS: There is a paucity of studies detailing the robust and synergistic use of QI and simulation. The findings of this review suggest a positive impact on patient safety when QI and simulation are used in tandem. The systematic integration of these disciplines and the use of established reporting guidelines can promote patient safety in practice and in the literature.

Associations Between Social Networks and COVID-19 Vaccine Uptake in 4 Rural Alabama Counties: Survey Findings.

OBJECTIVES: The COVID-19 pandemic demonstrated how vaccination decisions are influenced by misinformation, disinformation, and social pressures, leading to varied and inequitable uptake rates. In this study, we examined how COVID-19 vaccine messages received via social networks were associated with vaccine uptake in rural Alabama. METHODS: From November 2021 through March 2022, we collected 700 responses to a telephone survey administered in 4 rural Alabama counties. We asked respondents to indicate whether certain social relationships (eg, family, businesses) tried to influence them to (1) obtain or (2) avoid a COVID-19 vaccine. We used χ2 tests, Kruskal-Wallis tests, Mantel-Haenszel χ2 tests, and Fisher exact tests to examine the associations between vaccination status and survey responses. RESULTS: Respondents in majority-African American counties were significantly more likely than those in majority-White counties to have received ≥1 dose of COVID-19 vaccine (89.8% vs 72.3%; P < .001). Respondents who received ≥1 dose had a significantly higher mean age than those who had not (58.0 vs 39.0 years; P < .001). Respondents who were encouraged to get vaccinated by religious leaders were more likely to have received ≥1 dose (P = .001), and those who were encouraged to avoid vaccination by family (P = .007), friends (P = .02), coworkers (P = .003), and health care providers (P < .001) were less likely to have received ≥1 dose. Respondents with more interpersonal relationships that encouraged them to avoid vaccination were more likely to be unvaccinated (P < .001). CONCLUSIONS: Interpersonal relationships and demographic characteristics appeared to be important in COVID-19 vaccine decision-making in rural Alabama. Further research needs to identify how to facilitate vaccine-positive interpersonal relationships, such as peer mentoring and trusted messenger interventions.

Workforce Engagement for Compassionate Advocacy, Resilience, and Empowerment (WE CARE): An Evidence-Based Wellness Program.

Poor well-being and burnout among the nursing workforce were heightened by the COVID-19 pandemic. The purpose of this study was to deliver, spread, and sustain an evidence-based wellness program, Workforce Engagement for Compassionate Advocacy, Resilience, and Empowerment (WE CARE), for nurse leaders, staff registered nurses (RNs), and patient care technicians (PCTs) to ameliorate or prevent burnout, promote resilience, and improve the work environment. The program included Community Resiliency Model (CRM) training provided by a certified 6-member wellness team. A baseline and 6-month follow-up survey included measures of well-being, moral distress, burnout, resilience, perceived organizational support (POS), job satisfaction, intent to leave (ITL), and work environment. A total of 4900 inpatient RNs, PCTs, and leaders of a 1207-bed academic medical center in the southeastern United States were analyzed. From baseline (n = 1533) to 6-month follow-up (n = 1457), well-being, moral distress, burnout, job satisfaction, and work environment improved; however, resilience, POS, and ITL did not. Although we have seen some improvements in well-being and mental health indicators, it is still early in the intervention period to have reached a critical mass with the training and other interventions. The mental health and work environment issues among nurses are so complex, no one-size-fits-all intervention can resolve.

Improving Communication with Family Members during a Global Pandemic: Effect on Patient Experience.

OBJECTIVES: Communication with patients and their families/caregivers to facilitate informed decision making is an integral part of patient/family-centered care. Due to the high coronavirus disease 2019 (COVID-19) infection rates and limited personal protective equipment, healthcare systems were forced to restrict patient visitors, limit patient-provider interactions, and implement other changes in treatment protocols that disturbed traditional communications and risked eroding patient/family-centered care and adversely affected patient satisfaction. This article focuses on changes in patient experience in two dedicated COVID-19 units of an academic medical center located in the US South as a result of the enhanced communication process implemented specifically during the COVID-19 pandemic. METHODS: This retrospective quality improvement project used data from Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) surveys, fielded between January 1, 2021 and August 31, 2021, to understand the role of a proactive communication initiative in patient satisfaction. RESULTS: Our results show that HCAHPS scores for hospital unit hospital unit 4 (HSP4) in all categories increased over time, with the greatest improvements seen in the responsiveness of staff and care transition; however, HCAHPS scores for hospital unit HSP3 remained stable, with a small increase in responsiveness of staff. CONCLUSIONS: Our findings suggest that communication is a critical factor in patient satisfaction, demonstrating the efficacy of a swift and innovative initiative to improve communication with family/caregivers, which may have been linked to better patient experiences. Developing communication strategies is crucial for enhancing patient satisfaction.

Evaluation of an Advanced Practice Provider Onboarding and Development Program.

OBJECTIVE: To evaluate the impact of implementing a comprehensive secondary onboarding and development program within a hospital medicine group at a large tertiary academic medical institution. METHODS: This was a mixed-methods study with physician and advanced practice providers (APPs) at an academic medical institution. RESULTS: For quantitative methods, improvement in competencies was determined using a pre-and posttest for APPs and pre- and postevaluation scores from collaborating physicians. APPs also participated in a pre- and post-self-assessment. For qualitative methods, experiences in the secondary onbo.arding and development program were assessed using semistructured interviews. CONCLUSIONS: For quantitative results, there were a total of 25 APPs who completed the pre- and posttest and were evaluated by at least 9 physicians. The average pretest score for APPs was 71.7% and the average posttest score was 83.0%. The average score for physicians' evaluations of APPs was 4.24/5 and increased to 4.38/5 in the postprogram evaluations. The average score for APP self-assessment pretraining was 3.52/5 and after the 12-month onboarding training, average scores increased to 3.84/5. For qualitative results, 4 APPs and 6 physicians were interviewed. Three of the APPs reported having more confidence in treating patients, whereas 1 APP viewed the program as a refresher course. All of the APPs mentioned that they would recommend the program to other APPs. Physicians reported that the program was beneficial in standardizing the care provided among the different types of APPs (physician assistants and nurse practitioners). All of the physicians also would recommend the program to other physicians and APPs.

Reducing hospital acquired pressure injury in a learning health center: Making the case for quality.

Introduction: The purpose of this descriptive study is to examine a learning health system (LHS) continuous improvement and learning approach as a case for increased quality, standardized processes, redesigned workflows, and better resource utilization. Hospital acquired pressure injuries (HAPI) commonly occur in the hospitalized patient and are costly and preventable. This study examines the effect of a LHS approach to reducing HAPI within a large academic medical center. Methods: Our learning health center implemented a 6-year series of iterative improvements that included both process and technology changes, with robust data and analytical reforms. In this descriptive, observational study, we retrospectively examined longitudinal data from April 1, 2018 to March 31, 2022, examining the variables of total number of all-stage HAPI counts and average length of stay (ALOS). We also analyzed patient characteristics observed/expected mortality ratios, as well as total patient days, and the case-mix index to determine whether these factors varied over the study period. We used the Agency for Healthcare Research and Quality cost estimates to identify the estimated financial benefit of HAPI reductions on an annualized basis. Results: HAPI per 1000 patient days for FY 20 (October 1-September 30) and FY 21, decreased from 2.30 to 1.30 and annualized event AHRQ cost estimates for HAPI decreased by $4 786 980 from FY 20 to FY 21. A strong, statistically significant, negative and seemingly counterintuitive correlation was found (r = -.524, P = .003) between HAPI and ALOS. Conclusions: The LHS efforts directed toward HAPI reduction led to sustained improvements during the study period. These results demonstrate the benefits of a holistic approach to quality improvement offered by the LHS model. The LHS model goes beyond a problem-based approach to process improvement. Rather than targeting a specific problem to solve, the LHS system creates structures that yield process improvement benefits over a continued time period.

Evaluating Outcomes and Time Delays of a Non-Trainee-Driven Hospitalist Procedure Service.

BACKGROUND AND OBJECTIVES: Ultrasound guidance has become standard of care in hospital medicine for invasive bedside procedures, especially central venous catheter placement. Despite ultrasound-guided bedside procedures having a high degree of success, only a few hospitalists perform them. This is because these are usually performed by radiologists or in the setting of trainee-run procedure teams. We sought to determine the impact of a non-trainee driven , hospitalist-run procedure service relative to time from consult to procedure. METHODS: The University of Alabama at Birmingham Hospital (UAB), Department of Hospital Medicine, trained 8 non-trainee hospitalist physicians (from existing staff) to implement the ultrasound-guided procedure service. This study examines consult to procedure completion time since the implementation of the procedure service (2014 to 2020). Univariate analyses are used to analyze pre-implementation (2012-2014), pilot (2014-2016), and post-implementation data (2016-2018 initial, and 2018-2020 sustained). RESULTS: Results suggest a 50% reduction in time from consult to procedure completion when compared with the period before implementation of the nontrainee hospitalist procedure service. CONCLUSIONS: A hospitalist procedure service, which does not include trainees, results in less time lag from consult to procedure completion time, which could increase patient satisfaction and improve throughput. As such, this study has wide generalizability to community hospitals and other nonacademic medical centers that may not have trainees.

Letter to the Editor Response: Exploring COVID-19 Vaccine Hesitancy Among Stakeholders in African American and Latinx Communities in the Deep South Through the Lens of the Health Belief Model.

The purpose of this submission to respond to a Letter to the Editor recently submitted regarding our manuscript, "Exploring COVID-19 Vaccine Hesitancy among Stakeholders in African American and Latinx Communities in the Deep South through the Lens of the Health Belief Model" published in the American Journal of Health Promotion in February, 2022. The manuscript reported on a study that had as its purpose to qualitatively explore perceptions related to COVID-19 vaccination intention among African American and Latinx participants and suggest potential intervention strategies.

Achieving Consensus Among Stakeholders Using the Nominal Group Technique: A Perinatal Quality Collaborative Approach.

BACKGROUND AND OBJECTIVES: Public health systems exhibiting strong connections across the workforce experience substantial population health improvements. This is especially important for improving quality and achieving value among vulnerable populations such as mothers and infants. The purpose of this research was to demonstrate how Alabama's newly formed perinatal quality collaborative (Alabama Perinatal Quality Collaborative [ALPQC]) used evidenced-based processes to achieve consensus in identifying population quality improvement (QI) initiatives. METHODS: This multiphase quantitative and qualitative study engaged stakeholders (n = 44) at the ALPQC annual meeting. Maternal and neonatal focused QI project topics were identified and catalogued from active perinatal quality collaborative websites. The Delphi method and the nominal group technique (NGT) were used to prioritize topics using selected criteria ( impact , enthusiasm , alignment , and feasibility ) and stakeholder input. RESULTS: Using the Delphi method, 11 of 27 identified project topics met inclusion criteria for stakeholder consideration. Employing the NGT, maternal projects received more total votes (n = 535) than neonatal projects (n = 313). Standard deviations were higher for neonatal projects (SD: feasibility = 10.9, alignment = 17.9, enthusiasm = 19.2, and impact = 22.1) than for maternal projects (SD: alignment = 5.9, enthusiasm = 7.3, impact = 7.9, and feasibility = 11.1). Hypertension in pregnancy (n = 117) and neonatal abstinence syndrome (n = 177) achieved the most votes total and for impact (n = 35 and n = 54, respectively) but variable support for feasibility . CONCLUSIONS: Together, these techniques achieved valid consensus across multidisciplinary stakeholders in alignment with state public health priorities. This model can be used in other settings to integrate stakeholder input and enhance the value of a common population QI agenda.

Competency analysis and educational strategies to meet the demand for a learning health system workforce.

Learning Health Systems (LHS) require a workforce with specific knowledge and skills to identify and address healthcare quality issues, develop solutions to address those issues, and sustain and spread improvements within and outside the organization. Educational programs are tasked with designing learning opportunities that can meet these organizational needs. This manuscript explores different mechanisms for addressing challenges to creating educational programs to prepare individuals who can work in and lead LHS. Strategies and recommendations for educational programs to support the LHS include the creation of a new program, collaborating across existing programs, and producing a set of instructional materials.

Multiple Electronic Health Record-Based Measures of Social Determinants of Health to Predict Return to the Emergency Department Following Discharge.

Health care systems continue to struggle with preventing 30-day readmissions to their institutions. Social determinants of health (SDOH) are important predictors of repeat visits to the hospital. In many health systems, SDOH data are limited to those variables that are most relevant to care delivery or payment (eg, race, gender, insurance status). Despite calls for integrating a more robust set of measures (eg, measures of health behaviors and living conditions) into the electronic health record (EHR), these data often have missing values necessitating the use of imputation to build a comprehensive picture of patients who are likely to return to the health system. Using logistic regression analyses and imputation of missing data from 2017 to 2018, this study uses measures found in the EHR (eg, tobacco use, living situation, problems at home, education) to assess those SDOH that might predict a return to the emergency department within 30 days of discharge from a health system. In both imputed and raw data, the total number of recorded health conditions was the most important predictor and collectively SDOH variables made a relatively small contributions in determining the likelihood of a return to the hospital. Although SDOH variables might be important in the design of programs aimed at preventing readmissions, they may not be useful in readmission predictive models.

COVID-19 Vaccine Knowledge, Attitudes, and Practices in Alabama: The Case for Primary Health Care Providers.

OBJECTIVE: To examine knowledge, attitudes, and practices about COVID-19 in Alabama, with a primary focus on vaccination perception and utilization. DESIGN: We used a COVID-19 Knowledge, Attitudes, and Practices survey and recruited adult Alabama residents in April-May 2021. PARTICIPANTS: Initial surveys from 1324 Alabamian participants were considered for analysis; after careful review of incomplete responses, 953 were ultimately included for analysis. MAIN OUTCOME MEASURE: Vaccine behavior and hesitancy comprise a self-reported response contained in the survey instrument. Three primary vaccine groups were used to assess differences in demographic characteristics, health status, perception of susceptibility and severity of COVID-19, sources of information, and trust about COVID-19. RESULTS: Of the 953 survey participants included for analysis, 951 had self-identified vaccine status in which 153 (16.1%) reported to have received the vaccine at the time of the survey, 375 (39.4%) were very likely or somewhat likely to get an approved COVID-19 vaccine if it was offered, and 423 (44.5%) were somewhat unlikely or very unlikely to get an approved COVID-19 vaccine. Health care providers were the most trusted sources of information, regardless of vaccine status. For participants unlikely to receive a vaccine, social media and local news sources were consistently more trusted and utilized than those who were vaccinated or were likely to be. CONCLUSIONS: The perceptions among unvaccinated participants are actionable and provide teachable opportunities to decrease vaccine apprehension.

Exploring a Need for a Cardiometabolic Disease Staging System as a Computerized Clinical Decision Support Tool: Qualitative Study.

BACKGROUND: Although cardiometabolic diseases are leading causes of morbidity and mortality in the United States, computerized tools for risk assessment of cardiometabolic disease are rarely integral components of primary care practice. Embedding cardiometabolic disease staging systems (CMDS) into computerized clinical decision support systems (CDSS) may assist with identifying and treating patients at greatest risk for developing cardiometabolic disease. OBJECTIVE: This study aimed to explore the current approach to medical management of obesity and the need for CMDS designed to aid medical management of people living with obesity, at risk of being obese, or diabetic at the point of care. METHODS: Using a general inductive approach, this qualitative research study was guided by an interpretive epistemology. The method included semistructured, in-depth interviews with primary care providers (PCPs) from university-based community health clinics. The literature informed the interview protocol and included questions on PCPs' experiences and the need for a tool to improve their ability to manage and prevent complications from overweight and obesity. RESULTS: PCPs (N=10) described their current approaches and emphasized behavioral treatments consisting of combined diet, physical activity, and behavior therapy as the first line of treatment for people who were overweight or obese. Results suggest that beneficial features of CDSS include (1) clinically relevant and customizable support, (2) provision of a comprehensive medical summary with trends, (3) availability of patient education materials and community resources, and (4) simplicity and ease of navigation. CONCLUSIONS: Implementation of a CMDS via a CDSS could enable PCPs to conduct comprehensive cardiometabolic disease risk assessments, supporting clinical management of overweight, obesity, and diabetes. Results from this study provide unique insights to developers and researchers by identifying areas for design optimization, improved end user experience, and successful adoption of the CDSS.

Physician, Nurse, and Advanced Practice Provider Perspectives on the Rapid Transition to Inpatient and Outpatient Telemedicine.

Background: Many health systems transitioned rapidly to using inpatient and outpatient telemedicine during the COVID-19 pandemic. Prior research has examined clinician satisfaction and experiences with telemedicine in a siloed approach for specific provider types. Less is known about how experiences with the rapid transition to telemedicine affected the entire clinical team, and how this contributed to their overall distress. Methods: A survey was conducted within a large academic medical center in the Southeastern United States during June of 2020. The survey asked about experiences with inpatient and outpatient telemedicine and overall distress. Analysis of variance was calculated to examine differences in experiences among physicians, nurses, and advanced practice providers (APPs) with both inpatient and outpatient telemedicine. Multivariate regression analysis was conducted to determine whether reported telemedicine stressors were associated with changes in overall distress scores. Qualitative comments provided during the survey were included to illustrate the quantitative findings. Results: Of the 1130 survey respondents, 237 indicated that they used telemedicine. Telemedicine use was not statistically significantly associated with overall distress scores. The APPs indicated the greatest satisfaction with telemedicine, followed by physicians and then nurses. Team members differed on their perceptions of quality of care and safety for inpatient and outpatient telemedicine. Physicians (70%) and APPs (64%) felt safer having the option to use inpatient telemedicine, whereas only 26% of nurses reported the same. Overall, >70% of physicians and APPs would like to continue having the option to use inpatient and outpatient telemedicine in the future, whereas <50% of nurses reported the same. Discussion: These results suggest that telemedicine holds promise for providing care beyond the pandemic, and it may be a mechanism to improve flexibility, autonomy, and expand patient access. Implementation of new technologies must consider the experiences of the entire team, rather than a siloed approach to determining satisfaction with the changes.

Mapping 2 Decades of Research in Health Services Research, Health Policy, and Health Economics Journals.

OBJECTIVE: To identify major research topics and exhibit trends in these topics in 15 health services research, health policy, and health economics journals over 2 decades. DATA SOURCES: The study sample of 35,159 abstracts (1999-2020) were collected from PubMed for 15 journals. STUDY DESIGN: The study used a 3-phase approach for text analyses: (1) developing the corpus of 40,618 references from PubMed (excluding 5459 of those without abstract or author information); (2) preprocessing and generating the term list using natural language processing to eliminate irrelevant textual data and identify important terms and phrases; (3) analyzing the preprocessed text data using latent semantic analysis, topic analyses, and multiple correspondence analysis. PRINCIPAL FINDINGS: Application of analyses generated 16 major research topics: (1) implementation/intervention science; (2) HIV and women's health; (3) outcomes research and quality; (4) veterans/military studies; (5) provider/primary-care interventions; (6) geriatrics and formal/informal care; (7) policies and health outcomes; (8) medication treatment/therapy; (9) patient interventions; (10) health insurance legislation and policies; (11) public health policies; (12) literature reviews; (13) cost-effectiveness and economic evaluation; (14) cancer care; (15) workforce issues; and (16) socioeconomic status and disparities. The 2-dimensional map revealed that some journals have stronger associations with specific topics. Findings were not consistent with previous studies based on user perceptions. CONCLUSION: Findings of this study can be used by the stakeholders of health services research, policy, and economics to develop future research agendas, target journal submissions, and generate interdisciplinary solutions by examining overlapping journals for particular topics.

Exploring COVID-19 Vaccine Hesitancy Among Stakeholders in African American and Latinx Communities in the Deep South Through the Lens of the Health Belief Model.

PURPOSE: The purpose of this study was to qualitatively explore perceptions related to COVID-19 vaccination intention among African American and Latinx participants and suggest intervention strategies. APPROACH: Ninety minute virtual focus groups (N = 8), segmented by county, race and ethnicity were conducted with stakeholders from 3 vulnerable Alabama counties. PARTICIPANTS: Participants (N = 67) were primarily African American and Latinx, at least 19 years, and residents or stakeholders in Jefferson, Mobile, and Dallas counties. SETTING: Focus groups took place virtually over Zoom. METHODS: The semi-structured guide explored perceptions of COVID-19, with an emphasis on barriers and facilitators to vaccine uptake. Focus groups lasted approximately 90 minutes and were audio recorded, transcribed, and analyzed by a team of 3 investigators, according to the guidelines of Thematic Analysis using NVivo 12. To provide guidance in the development of interventions to decrease vaccine hesitancy, we examined how themes fit with the constructs of the Health Belief Model. RESULTS: We found that primary themes driving COVID-19 vaccine hesitancy, ordered from most to least discussed, are mistrust, fear, and lack of information. Additionally, interventions to decrease vaccine hesitancy should be multi-modal, community engaged, and provide consistent, comprehensive messages delivered by trusted sources.

Using Accountable Care Teams to Improve Timely Discharge: A Pilot Study.

BACKGROUND AND OBJECTIVE: Hospitals worldwide are faced with the problem of discharging patients on time. Delayed discharge creates domino effects with significant implications for hospitals. The accountable care team (ACT) is a multidisciplinary, unit-based approach to identifying opportunities to improve patient care and address inefficiencies in care delivery and throughput, including assuring timely discharges. In response to concerns about emergency department boarding times and delays in timely discharge, the ACT recommended a set of strategies to improve communication across team members and to reduce wait times for transportation within and outside the hospital. Collectively these strategies were thought to increase the proportion of patients discharged on time. In this article, we describe and assess changes in timely discharge resulting from the implementation of strategies recommended by the ACT. METHODS: This study uses a retrospective, quasi-experimental design to compare the percentage of discharges by 1 pm of hospital units implementing the ACT intervention to those units not implementing the intervention. Median discharge time was compared pre- and post-implementation using the Wilcoxon rank sum test. Difference-in-differences modeling was employed to assess whether changes in the percentage of discharges by 1 pm differed between units implementing the intervention and units not implementing the intervention. RESULTS: One month post-implementation, the percentage discharged by 1 pm was statistically significantly higher for units implementing the intervention (53.6%) compared with comparison units (22.5%, t = -4.48, P < .01). Statistically significant differences in the percentage discharged by 1 pm were also seen at 3 and 6 months post-implementation. The median discharge time showed a statistically significant decrease by 77 minutes from the baseline to intervention period ( P < .01). CONCLUSION: The result from the study suggests that ACTs can be used to develop approaches aimed at improving patient care in general, and discharge efficiencies in particular. Health care organizations are encouraged to utilize and then evaluate the specific activities of multidisciplinary teams aimed at developing recommendations for practice improvement.