Effect of gamification with a support partner to increase physical activity in older adults at risk for Alzheimer's disease: The STEP 4Life randomized clinical trial.

INTRODUCTION: Physical activity is associated with reduced risk of cognitive and functional decline but scalable, sustainable interventions for populations at risk for Alzheimer's disease (AD) and AD and related dementias (ADRD) are lacking. METHODS: A 12-week randomized-controlled trial was conducted with a 3-week follow-up using a national AD prevention registry (GeneMatch). The control group (n = 50) set step goals and received daily feedback. The intervention group (n = 44) also received a behaviorally designed game based on achieving step goals and reinforced by a support partner. RESULTS: Intervention participants (94 participants, mean age 70, 78% female) had greater change in mean daily step count than control of 1699 steps/day (95% confidence interval [CI], 1149-2249), P < 0.0001, which was sustained in the follow-up period at 1219 steps/day (95% CI, 455-1983), P = 0.0018. Carriers of the apolipoprotein E ε4 gene (high risk) did not perform differently than non-carriers; however, high self-reported risk perception was associated with higher activity. DISCUSSION: A gamified intervention was effective in promoting and sustaining higher physical activity in older adults at genetic risk for AD/ADRD. HIGHLIGHTS: A simple game played with a support partner increased walking in older adults at risk for Alzheimer's disease (AD). The game also increased minutes of moderate-to-vigorous physical activity per day. Perception of lifelong AD risk was associated with increased activity but genetic risk (apolipoprotein E ε4+) was not. TRIAL REGISTRATION: ClinicalTrials.gov: NCT05069155.

Pilot Process Evaluation of the Supporting Older Adults at Risk Model: A RE-AIM Approach.

ABSTRACT: Despite evidence supporting transitional care models, hospitals report challenges implementing and sustaining them. The Discharge to Assess (D2A) Model is an innovative solution to this problem but required translation from a national health system context to an U.S.-based context. We translated the central tenets of the D2A model to establish the Supporting Older Adults at Risk (SOAR) Model, which unfolds in three phases: Prepare, Transition, and Support. The purpose of this project was to conduct a process evaluation of the SOAR Model in practice using the RE-AIM Framework (Reach, Effectiveness, Adoption, Implementation, and Maintenance). Forty patients completed all SOAR Model components for a Reach of 21%. Patients averaged 80 years of age, 53% were female, and 64% Black/AA. SOAR significantly improved discharge before noon, time to first home visit, and use of the in-house pharmacy. SOAR also improved length of hospital stay, emergency department visits, and readmissions. Twenty-one of the 26 Implementation measures unfolded with 75% or greater fidelity. Sixteen of the 24 Adoption measures unfolded with 75% or greater fidelity. COVID-19 limited Maintenance. Given the model unfolds across settings over time, requiring adoption from interprofessional team members, patients, and families, future work should focus on improving reach and adoption.

Reducing Physical Therapy Consults for Patients With High Functional Mobility in the Acute Medical Inpatient Setting: A Difference-in-Difference Analysis.

OBJECTIVE: To evaluate the effectiveness of clinical decision support for reducing misallocation of physical therapy (PT) consults. DESIGN: A prospective quasi-experimental study. Between October 2018 and November 2021, routinely documented data on functional status and physical therapy referrals were collected from electronic medical records. SETTING: Hospital Medicine and General Internal Medicine service lines at a large quaternary academic medical center. PARTICIPANTS: 20,810 adult patients hospitalized on any of the included treatment (hospital medicine) or control (general internal medicine) service lines. MAIN OUTCOME MEASURE: The primary outcome was "change in proportion of misallocated PT consults" measured as likelihood of PT consults for patients admitted with high functional mobility scores. Changes in the primary outcome from the pre-intervention to post-intervention period were compared in the control and treatment groups using propensity score-weighted difference-in-differences multivariable logit regression adjusting for clinically relevant covariates. INTERVENTION: The intervention period was measured for 20 months and consisted of a clinical decision support tool embedded in the daily note templates for hospital medicine providers. The tool provided education on patient mobility scores and their relation to need for PT consult. The tool was rolled out without any further announcements or education. RESULTS: Our cohort included 20,810 unique admissions (mean age 58.9, 55% women, 83% Black). Post-intervention, the likelihood of PT referrals for patients with high baseline mobility (AM-PAC >18) decreased by 7.3% (P<.001) for the treatment group compared with control, adjusted for age, sex, race, ethnicity, length-of-stay, and mobility change. CONCLUSION: Mobility score-based clinical decision support can decrease unneeded PT consults in the inpatient setting. This could help allocate therapy time for at-risk patients while also having a positive effect on health care systems.

Trends in Before Medically Advised Discharges for Patients With Opioid Use Disorder, 2016-2020.

This study examines discharge trends for opioid-related admissions from 2016-2020 with a focus on admissions with opioid use disorder and an injection-related infection.

A Data-Driven Analysis of Ward Capacity Strain Metrics That Predict Clinical Outcomes Among Survivors of Acute Respiratory Failure.

Supply-demand mismatch of ward resources ("ward capacity strain") alters care and outcomes. Narrow strain definitions and heterogeneous populations limit strain literature. Evaluate the predictive utility of a large set of candidate strain variables for in-hospital mortality and discharge destination among acute respiratory failure (ARF) survivors. In a retrospective cohort of ARF survivors transferred from intensive care units (ICUs) to wards in five hospitals from 4/2017-12/2019, we applied 11 machine learning (ML) models to identify ward strain measures during the first 24 hours after transfer most predictive of outcomes. Measures spanned patient volume (census, admissions, discharges), staff workload (medications administered, off-ward transports, transfusions, isolation precautions, patients per respiratory therapist and nurse), and average patient acuity (Laboratory Acute Physiology Score version 2, ICU transfers) domains. The cohort included 5,052 visits in 43 wards. Median age was 65 years (IQR 56-73); 2,865 (57%) were male; and 2,865 (57%) were white. 770 (15%) patients died in the hospital or had hospice discharges, and 2,628 (61%) were discharged home and 964 (23%) to skilled nursing facilities (SNFs). Ward admissions, isolation precautions, and hospital admissions most consistently predicted in-hospital mortality across ML models. Patients per nurse most consistently predicted discharge to home and SNF, and medications administered predicted SNF discharge. In this hypothesis-generating analysis of candidate ward strain variables' prediction of outcomes among ARF survivors, several variables emerged as consistently predictive of key outcomes across ML models. These findings suggest targets for future inferential studies to elucidate mechanisms of ward strain's adverse effects.

Geographic cohorting by clinical care team: a narrative review.

BACKGROUND AND OBJECTIVE: Geographic cohorting refers to localization of inpatients to designated hospital areas (typically a unit or a set of beds) based on specified criteria. One such criterion that has been commonly discussed and studied since the early days of the hospitalist movement in the US is a patient's assigned clinical care team. Because implementing cohorting of this type requires substantial operational investment, it is important to understand the benefits and the tradeoffs associated with bringing patients into closer spatial proximity with their full team of providers and allowing clinicians to work within a defined clinical space. METHODS: We conducted a narrative review of the evidence around geographic cohorting of patients by clinical care team. We performed a comprehensive search of the PubMed, Embase, Cinahl and Scopus databases, identifying relevant English language articles. We used an inductive approach to developing thematic domains for categorization of article content. KEY CONTENT AND FINDINGS: We reviewed eighteen articles published between 2008 and 2022, and identified four thematic outcomes domains: patient-centered outcomes, communication, efficiency, and satisfaction. The existing literature demonstrates associations with improved communication and staff satisfaction. The data regarding patient outcomes and overall work efficiency, on the other hand, are equivocal and, in general, limited by study methodology. CONCLUSIONS: Geographic cohorting of inpatients according to clinical care team offers some promise for improved workplace culture. More rigorously designed studies are needed, however, to understand its impact on patient outcomes, and there should be added attention paid to throughput metrics and tradeoffs that often limit its implementation.

Prevalence and Causes of Diagnostic Errors in Hospitalized Patients Under Investigation for COVID-19.

BACKGROUND: The COVID-19 pandemic required clinicians to care for a disease with evolving characteristics while also adhering to care changes (e.g., physical distancing practices) that might lead to diagnostic errors (DEs). OBJECTIVE: To determine the frequency of DEs and their causes among patients hospitalized under investigation (PUI) for COVID-19. DESIGN: Retrospective cohort. SETTING: Eight medical centers affiliated with the Hospital Medicine ReEngineering Network (HOMERuN). TARGET POPULATION: Adults hospitalized under investigation (PUI) for COVID-19 infection between February and July 2020. MEASUREMENTS: We randomly selected up to 8 cases per site per month for review, with each case reviewed by two clinicians to determine whether a DE (defined as a missed or delayed diagnosis) occurred, and whether any diagnostic process faults took place. We used bivariable statistics to compare patients with and without DE and multivariable models to determine which process faults or patient factors were associated with DEs. RESULTS: Two hundred and fifty-seven patient charts underwent review, of which 36 (14%) had a diagnostic error. Patients with and without DE were statistically similar in terms of socioeconomic factors, comorbidities, risk factors for COVID-19, and COVID-19 test turnaround time and eventual positivity. Most common diagnostic process faults contributing to DE were problems with clinical assessment, testing choices, history taking, and physical examination (all p < 0.01). Diagnostic process faults associated with policies and procedures related to COVID-19 were not associated with DE risk. Fourteen patients (35.9% of patients with errors and 5.4% overall) suffered harm or death due to diagnostic error. LIMITATIONS: Results are limited by available documentation and do not capture communication between providers and patients. CONCLUSION: Among PUI patients, DEs were common and not associated with pandemic-related care changes, suggesting the importance of more general diagnostic process gaps in error propagation.

Participants' Perspectives on Payment for Research Participation: A Qualitative Study.

Investigators commonly offer payments to research participants to promote recruitment and retention. Yet the ethics of offering monetary incentives to research participants continues to be debated. Prior conceptual work has addressed some of these concerns; there is, however, also a need for empirical evidence to understand the effects of payment on participants. Here, we report the results of a qualitative study comprising (1) discourse analysis of recruitment conversations between study coordinators and potential participants for an actual clinical trial and (2) semistructured interviews with participants addressing the effects of an incentive on their decision-making. Many participants reported that money had been a motivation for enrolling in the clinical trial but did not use reasoning that suggested undue influence or unjust inducement. These findings add to a growing body of literature suggesting that payment is an ethically acceptable tool for promoting recruitment and retention in clinical trials.