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Implementation Experience with a 30-Day Hospital Readmission Risk Score in a Large, Integrated Health System: A Retrospective Study.

Authors :
Misra-Hebert AD
Felix C
Milinovich A
Kattan MW
Willner MA
Chagin K
Bauman J
Hamilton AC
Alberts J
Source :
Journal of general internal medicine [J Gen Intern Med] 2022 Sep; Vol. 37 (12), pp. 3054-3061. Date of Electronic Publication: 2022 Feb 07.
Publication Year :
2022

Abstract

Background: Driven 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).<br />Objective: We 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.<br />Design: Retrospective cohort study.<br />Participants: Adult patients discharged from a CCHS hospital April 2017-September 2020.<br />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.<br />Results: The 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.<br />Conclusions: The 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.<br /> (© 2022. The Author(s) under exclusive licence to Society of General Internal Medicine.)

Details

Language :
English
ISSN :
1525-1497
Volume :
37
Issue :
12
Database :
MEDLINE
Journal :
Journal of general internal medicine
Publication Type :
Academic Journal
Accession number :
35132549
Full Text :
https://doi.org/10.1007/s11606-021-07277-4