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

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). OBJECTIVE: We...

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Autores principales: Misra-Hebert, Anita D., Felix, Christina, Milinovich, Alex, Kattan, Michael W., Willner, Marc A., Chagin, Kevin, Bauman, Janine, Hamilton, Aaron C., Alberts, Jay
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8821785/
https://www.ncbi.nlm.nih.gov/pubmed/35132549
http://dx.doi.org/10.1007/s11606-021-07277-4
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author Misra-Hebert, Anita D.
Felix, Christina
Milinovich, Alex
Kattan, Michael W.
Willner, Marc A.
Chagin, Kevin
Bauman, Janine
Hamilton, Aaron C.
Alberts, Jay
author_facet Misra-Hebert, Anita D.
Felix, Christina
Milinovich, Alex
Kattan, Michael W.
Willner, Marc A.
Chagin, Kevin
Bauman, Janine
Hamilton, Aaron C.
Alberts, Jay
author_sort Misra-Hebert, Anita D.
collection PubMed
description 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). 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. DESIGN: Retrospective cohort study. PARTICIPANTS: Adult 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. 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. 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11606-021-07277-4.
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spelling pubmed-88217852022-02-08 Implementation Experience with a 30-Day Hospital Readmission Risk Score in a Large, Integrated Health System: A Retrospective Study Misra-Hebert, Anita D. Felix, Christina Milinovich, Alex Kattan, Michael W. Willner, Marc A. Chagin, Kevin Bauman, Janine Hamilton, Aaron C. Alberts, Jay J Gen Intern Med Original Research 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). 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. DESIGN: Retrospective cohort study. PARTICIPANTS: Adult 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. 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. 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11606-021-07277-4. Springer International Publishing 2022-02-07 2022-09 /pmc/articles/PMC8821785/ /pubmed/35132549 http://dx.doi.org/10.1007/s11606-021-07277-4 Text en © The Author(s) under exclusive licence to Society of General Internal Medicine 2022
spellingShingle Original Research
Misra-Hebert, Anita D.
Felix, Christina
Milinovich, Alex
Kattan, Michael W.
Willner, Marc A.
Chagin, Kevin
Bauman, Janine
Hamilton, Aaron C.
Alberts, Jay
Implementation Experience with a 30-Day Hospital Readmission Risk Score in a Large, Integrated Health System: A Retrospective Study
title Implementation Experience with a 30-Day Hospital Readmission Risk Score in a Large, Integrated Health System: A Retrospective Study
title_full Implementation Experience with a 30-Day Hospital Readmission Risk Score in a Large, Integrated Health System: A Retrospective Study
title_fullStr Implementation Experience with a 30-Day Hospital Readmission Risk Score in a Large, Integrated Health System: A Retrospective Study
title_full_unstemmed Implementation Experience with a 30-Day Hospital Readmission Risk Score in a Large, Integrated Health System: A Retrospective Study
title_short Implementation Experience with a 30-Day Hospital Readmission Risk Score in a Large, Integrated Health System: A Retrospective Study
title_sort implementation experience with a 30-day hospital readmission risk score in a large, integrated health system: a retrospective study
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8821785/
https://www.ncbi.nlm.nih.gov/pubmed/35132549
http://dx.doi.org/10.1007/s11606-021-07277-4
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