Roman Ayele1, Kirstin A Manges2, Chelsea Leonard3, Marcie Lee3, Emily Galenbeck3, Mithu Molla4, Cari Levy5, Robert E Burke6. 1. Denver-Seattle Center of Innovation, Eastern Colorado Healthcare System, Aurora, CO, USA; University of Colorado, Anschutz Medical Campus, Aurora, CO, USA. Electronic address: Roman.Ayele@va.gov. 2. National Clinician Scholar, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA; Hospital Medicine Section, Division of General Internal Medicine, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA. 3. Denver-Seattle Center of Innovation, Eastern Colorado Healthcare System, Aurora, CO, USA. 4. Hospital Medicine Section, UC Davis Health System, Sacramento, CA, USA. 5. Denver-Seattle Center of Innovation, Eastern Colorado Healthcare System, Aurora, CO, USA; University of Colorado, Anschutz Medical Campus, Aurora, CO, USA. 6. Hospital Medicine Section, Division of General Internal Medicine, Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA; Center for Health Equity Research and Promotion (CHERP), Corporal Crescenz VA Medical Center, Philadelphia, PA, USA.
Abstract
INTRODUCTION: Improving hospital discharge processes and reducing adverse outcomes after hospital discharge to skilled nursing facilities (SNFs) are gaining national recognition. However, little is known about how the social-contextual factors of hospitals and their affiliated SNFs may influence the discharge process and drive variations in patient outcomes. We sought to categorize contextual drivers that vary between high- and low-performing hospitals in older adult transition from hospitals to SNFs. DESIGN: To identify contextual drivers, we used a rapid ethnographic approach with interviews and direct observations of hospital and SNF clinicians involved in discharging patients. We conducted thematic analysis to categorize contextual factors and compare differences in high- and low-performing sites. SETTING AND PARTICIPANTS: We stratified hospitals on 30-day hospital readmission rates from SNFs and used convenience sampling to identify high- and low-performing sites and associated SNFs. The final sample included 4 hospitals (n = 2 high performing, n = 2 low performing) and affiliated SNFs (n = 5) with 148 hours of observations. MEASURES: Central themes related to how contextual factors influence variations in high- and low-performing hospitals. RESULTS: We identified 3 main contextual factors that differed across high- and low-performing hospitals and SNFs: team dynamics, patient characteristics, and organizational context. First, we observed high-quality communication, situational awareness, and shared mental models among team members in high-performing sites. Second, the types of patients cared for at high-performing hospitals had better insurance coverage that made it feasible for clinicians to place patients based on their needs instead of financial abilities. Third, at high-performing hospitals a more engaged staff in the transition process and building rapport with SNFs characterized smooth transitions from hospitals to SNFs. CONCLUSIONS AND IMPLICATIONS: Contextual factors distinguish high- and low-performing hospitals in transitions to SNF and can be used to develop interventions to reduce adverse outcomes in transitions. Published by Elsevier Inc.
INTRODUCTION: Improving hospital discharge processes and reducing adverse outcomes after hospital discharge to skilled nursing facilities (SNFs) are gaining national recognition. However, little is known about how the social-contextual factors of hospitals and their affiliated SNFs may influence the discharge process and drive variations in patient outcomes. We sought to categorize contextual drivers that vary between high- and low-performing hospitals in older adult transition from hospitals to SNFs. DESIGN: To identify contextual drivers, we used a rapid ethnographic approach with interviews and direct observations of hospital and SNF clinicians involved in discharging patients. We conducted thematic analysis to categorize contextual factors and compare differences in high- and low-performing sites. SETTING AND PARTICIPANTS: We stratified hospitals on 30-day hospital readmission rates from SNFs and used convenience sampling to identify high- and low-performing sites and associated SNFs. The final sample included 4 hospitals (n = 2 high performing, n = 2 low performing) and affiliated SNFs (n = 5) with 148 hours of observations. MEASURES: Central themes related to how contextual factors influence variations in high- and low-performing hospitals. RESULTS: We identified 3 main contextual factors that differed across high- and low-performing hospitals and SNFs: team dynamics, patient characteristics, and organizational context. First, we observed high-quality communication, situational awareness, and shared mental models among team members in high-performing sites. Second, the types of patients cared for at high-performing hospitals had better insurance coverage that made it feasible for clinicians to place patients based on their needs instead of financial abilities. Third, at high-performing hospitals a more engaged staff in the transition process and building rapport with SNFs characterized smooth transitions from hospitals to SNFs. CONCLUSIONS AND IMPLICATIONS: Contextual factors distinguish high- and low-performing hospitals in transitions to SNF and can be used to develop interventions to reduce adverse outcomes in transitions. Published by Elsevier Inc.
Entities:
Keywords:
Context of care; older adults; transitions of care
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