Cargando…
Impact on hospital ranking of basing readmission measures on a composite endpoint of death or readmission versus readmissions alone
BACKGROUND: Readmission penalties are central to the Centers for Medicare and Medicaid Services (CMS) efforts to improve patient outcomes and reduce health care spending. However, many clinicians believe that readmission metrics may unfairly penalize low-mortality hospitals because mortality and rea...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5420148/ https://www.ncbi.nlm.nih.gov/pubmed/28476128 http://dx.doi.org/10.1186/s12913-017-2266-4 |
_version_ | 1783234356526972928 |
---|---|
author | Glance, Laurent G. Li, Yue Dick, Andrew W. |
author_facet | Glance, Laurent G. Li, Yue Dick, Andrew W. |
author_sort | Glance, Laurent G. |
collection | PubMed |
description | BACKGROUND: Readmission penalties are central to the Centers for Medicare and Medicaid Services (CMS) efforts to improve patient outcomes and reduce health care spending. However, many clinicians believe that readmission metrics may unfairly penalize low-mortality hospitals because mortality and readmission are competing risks. The objective of this study is to compare hospital ranking based on a composite outcome of death or readmission versus readmission alone. METHODS: We performed a retrospective observational study of 344,565 admissions for acute myocardial infarction (AMI), congestive heart failure (CHF), or pneumoniae (PNEU) using population-based data from the New York State Inpatient Database (NY SID) between 2011 and 2013. Hierarchical logistic regression modeling was used to estimate separate risk-adjustment models for the (1) composite outcome (in-hospital death or readmission within 7-days), and (2) 7-day readmission. Hospital rankings based on the composite measure and the readmission measure were compared using the intraclass correlation coefficient and kappa analysis. RESULTS: Using data from all AMI, CHF, and PNEU admissions, there was substantial agreement between hospital adjusted odds ratio (AOR) based on the composite outcome versus the readmission outcome (intraclass correlation coefficient [ICC] 0.67; 95% CI: 0.56, 0.75). For patients admitted with AMI, there was moderate agreement (ICC 0.53; 95% CI: 0.41, 0.62); for CHF, substantial agreement (ICC 0.72; 95% CI: 0.66, 0.78); and for PNEU, substantial agreement (ICC 0.71; 95% CI: 0.61, 0.78). There was moderate agreement when the composite and readmission metrics were used to classify hospitals as high, average, and low-performance hospitals (κ = 0.54, SE = 0.050). For patients admitted with AMI, there was slight agreement (κ = 0.14, SE = 0.037) between the two metrics. CONCLUSIONS: Hospital performance on readmissions is significantly different from hospital performance on a composite metric based on readmissions and mortality. CMS and policy makers should consider re-assessing the use of readmission metrics for measuring hospital performance. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12913-017-2266-4) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5420148 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-54201482017-05-08 Impact on hospital ranking of basing readmission measures on a composite endpoint of death or readmission versus readmissions alone Glance, Laurent G. Li, Yue Dick, Andrew W. BMC Health Serv Res Research Article BACKGROUND: Readmission penalties are central to the Centers for Medicare and Medicaid Services (CMS) efforts to improve patient outcomes and reduce health care spending. However, many clinicians believe that readmission metrics may unfairly penalize low-mortality hospitals because mortality and readmission are competing risks. The objective of this study is to compare hospital ranking based on a composite outcome of death or readmission versus readmission alone. METHODS: We performed a retrospective observational study of 344,565 admissions for acute myocardial infarction (AMI), congestive heart failure (CHF), or pneumoniae (PNEU) using population-based data from the New York State Inpatient Database (NY SID) between 2011 and 2013. Hierarchical logistic regression modeling was used to estimate separate risk-adjustment models for the (1) composite outcome (in-hospital death or readmission within 7-days), and (2) 7-day readmission. Hospital rankings based on the composite measure and the readmission measure were compared using the intraclass correlation coefficient and kappa analysis. RESULTS: Using data from all AMI, CHF, and PNEU admissions, there was substantial agreement between hospital adjusted odds ratio (AOR) based on the composite outcome versus the readmission outcome (intraclass correlation coefficient [ICC] 0.67; 95% CI: 0.56, 0.75). For patients admitted with AMI, there was moderate agreement (ICC 0.53; 95% CI: 0.41, 0.62); for CHF, substantial agreement (ICC 0.72; 95% CI: 0.66, 0.78); and for PNEU, substantial agreement (ICC 0.71; 95% CI: 0.61, 0.78). There was moderate agreement when the composite and readmission metrics were used to classify hospitals as high, average, and low-performance hospitals (κ = 0.54, SE = 0.050). For patients admitted with AMI, there was slight agreement (κ = 0.14, SE = 0.037) between the two metrics. CONCLUSIONS: Hospital performance on readmissions is significantly different from hospital performance on a composite metric based on readmissions and mortality. CMS and policy makers should consider re-assessing the use of readmission metrics for measuring hospital performance. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12913-017-2266-4) contains supplementary material, which is available to authorized users. BioMed Central 2017-05-05 /pmc/articles/PMC5420148/ /pubmed/28476128 http://dx.doi.org/10.1186/s12913-017-2266-4 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Glance, Laurent G. Li, Yue Dick, Andrew W. Impact on hospital ranking of basing readmission measures on a composite endpoint of death or readmission versus readmissions alone |
title | Impact on hospital ranking of basing readmission measures on a composite endpoint of death or readmission versus readmissions alone |
title_full | Impact on hospital ranking of basing readmission measures on a composite endpoint of death or readmission versus readmissions alone |
title_fullStr | Impact on hospital ranking of basing readmission measures on a composite endpoint of death or readmission versus readmissions alone |
title_full_unstemmed | Impact on hospital ranking of basing readmission measures on a composite endpoint of death or readmission versus readmissions alone |
title_short | Impact on hospital ranking of basing readmission measures on a composite endpoint of death or readmission versus readmissions alone |
title_sort | impact on hospital ranking of basing readmission measures on a composite endpoint of death or readmission versus readmissions alone |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5420148/ https://www.ncbi.nlm.nih.gov/pubmed/28476128 http://dx.doi.org/10.1186/s12913-017-2266-4 |
work_keys_str_mv | AT glancelaurentg impactonhospitalrankingofbasingreadmissionmeasuresonacompositeendpointofdeathorreadmissionversusreadmissionsalone AT liyue impactonhospitalrankingofbasingreadmissionmeasuresonacompositeendpointofdeathorreadmissionversusreadmissionsalone AT dickandreww impactonhospitalrankingofbasingreadmissionmeasuresonacompositeendpointofdeathorreadmissionversusreadmissionsalone |