A Lean Six Sigma Quality Improvement Project Improves Timeliness of Discharge from the Hospital.

BACKGROUND: Hospital overcrowding has become a widespread problem, with constrained bed capacity and admission bottlenecks having far-reaching negative impacts on quality and safety. Focus on timing of discharge may be the least disruptive and most effective way to address constrained bed capacity, yet there may be significant institution-specific barriers to implementation. METHODS: With the creation of a "Value Team," a 627-bed, tertiary care academic medical center embarked on a quality improvement (QI) project using Lean Six Sigma process improvement methodology. After defining the problems around timeliness of discharge, the team went through the steps in the Define, Measure, Analyze, Improve, Control (DMAIC) framework. Interventions, which were implemented on the basis of an in-depth analysis of barriers to the discharge process, included geographic cohorts of internal medicine physicians on specific hospital units and multidisciplinary huddles one day before anticipated discharge. RESULTS: After accounting for the concurrent trends in the control group, the percentage of discharge orders released by 10:00 a.m. increased by 21.3 points (p < 0.001; adjusted odds ratio [OR] = 2.62; 95% confidence interval [CI] = 1.91-3.59), and the percentage of patients discharged by noon increased by 7.5 points (p = 0.001; adjusted OR = 1.70; 95% CI 1.15-2.51). There were no significant changes in the 30-day readmission rate or length of stay. CONCLUSION: A QI program shaped by Lean Six Sigma principles and reinforced by clinician huddles and geographic cohorting was associated with earlier posting of discharge orders and physical discharge by noon.

How Context Influences Hospital Readmissions from Skilled Nursing Facilities: A Rapid Ethnographic Study.

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.