BACKGROUND: Individuals with serious mental illness face a significant burden of disease, yet experience lower quality care across a range of services (1). Hospital readmission within 30 days of discharge is an important, if imperfect, proxy for quality of care. Factors contributing to readmission are well documented (2–5), yet successful interventions to decrease readmissions have been slow to take shape (6–9). To effectively develop and incorporate evidence-based interventions to reduce 30-day psychiatric readmissions into large, geographically diverse inpatient systems; there is a need to conduct in-depth implementation analyses to better understand the relationship between patient-, hospital-, health system-, and community-level factors and their net impact on readmissions. This research addresses this need.
METHODS: Using a modified Consolidated Framework for Implementation Research (CFIR), two state-based case studies were conducted within a large U.S. hospital system. Two hospitals per state were selected-- one with a high and one with a lower readmission rate. We conducted document reviews and semi-structured interviews (N=52) with corporate, clinical and community stakeholders, using the CFIR to identify key themes within each construct. We scored and compared hospitals with lower vs. higher readmission rates. An analysis of EMR data from the hospital system contextualized case study findings.
RESULTS: In one state a complex interplay of factors at all levels contributed to readmission rates in both hospitals. In the second, constructs within the inner hospital setting contribute to differences in hospital readmission rates. Facilities with high readmission rates scored lowest among CFIR constructs “Patient Needs and Resources in the Community” and “External Policies and Incentives.”
CONCLUSIONS: Ours is the first known study to explore a broad range of factors that influence readmission rates among patients with serious mental illness and a range of comorbidities. Findings from two state-based case studies indicate that readmission rates are determined by multiple, interrelated factors which vary in importance based on hospital and community context and political environment. To be effective, systemic interventions to reduce readmissions must be tailored to the specific context at targeted hospitals.
| Identifer | oai:union.ndltd.org:bu.edu/oai:open.bu.edu:2144/36039 |
| Date | 04 June 2019 |
| Creators | Bhosrekar, Sarah Gees |
| Contributors | McCloskey, Lois, Feinberg, Emily |
| Source Sets | Boston University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis/Dissertation |
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