ArticleJournal of general internal medicine2022
Implementation Experience with a 30-Day Hospital Readmission Risk Score in a Large, Integrated Health System: A Retrospective Study.
Article in Journal of general internal medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed, 8 citations in OpenAlex.
- Developing and Applying the BE-FAIR Equity Framework to a Population Health Predictive Model: A Retrospective Observational Cohort Study.Journal of general internal medicine · 2025Observational
- Postsurgical Remote Patient Monitoring Outcomes and Perceptions: A Mixed-Methods Assessment.Mayo Clinic proceedings. Innovations, quality & outcomes · 2022Article
- Explainable machine learning for predicting conversion to neurological disease: Results from 52,939 medical records.Digital healthArticle
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Authors and funding
9 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDriven by quality outcomes and economic incentives, predicting 30-day hospital readmissions remains important for healthcare systems. The Cleveland Clinic Health System (CCHS) implemented an internally validated readmission risk score in the electronic medical record (EMR).
objectiveWe evaluated the predictive accuracy of the readmission risk score across CCHS hospitals, across primary discharge diagnosis categories, between surgical/medical specialties, and by race and ethnicity.
designRetrospective cohort study.
participantsAdult patients discharged from a CCHS hospital April 2017-September 2020. MAIN MEASURES: Data was obtained from the CCHS EMR and billing databases. All patients discharged from a CCHS hospital were included except those from Oncology and Labor/Delivery, patients with hospice orders, or patients who died during admission. Discharges were categorized as surgical if from a surgical department or surgery was performed. Primary discharge diagnoses were classified per Agency for Healthcare Research and Quality Clinical Classifications Software Level 1 categories. Discrimination performance predicting 30-day readmission is reported using the c-statistic.
resultsThe final cohort included 600,872 discharges from 11 Northeast Ohio and Florida CCHS hospitals. The readmission risk score for the cohort had a c-statistic of 0.6875 with consistent yearly performance. The c-statistic for hospital sites ranged from 0.6762, CI [0.6634, 0.6876], to 0.7023, CI [0.6903, 0.7132]. Medical and surgical discharges showed consistent performance with c-statistics of 0.6923, CI [0.6807, 0.7045], and 0.6802, CI [0.6681, 0.6925], respectively. Primary discharge diagnosis showed variation, with lower performance for congenital anomalies and neoplasms. COVID-19 had a c-statistic of 0.6387. Subgroup analyses showed c-statistics of > 0.65 across race and ethnicity categories.
conclusionsThe CCHS readmission risk score showed good performance across diverse hospitals, across diagnosis categories, between surgical/medical specialties, and by patient race and ethnicity categories for 3 years after implementation, including during COVID-19. Evaluating clinical decision-making tools post-implementation is crucial to determine their continued relevance, identify opportunities to improve performance, and guide their appropriate use.
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