Cargando…

Variations in the Hospital Standardized Mortality Ratios in Korea

OBJECTIVES: The hospital standardized mortality ratio (HSMR) has been widely used because it allows for robust risk adjustment using administrative data and is important for improving the quality of patient care. METHODS: All inpatients discharged from hospitals with more than 700 beds (66 hospitals...

Descripción completa

Detalles Bibliográficos
Autores principales: Lee, Eun-Jung, Hwang, Soo-Hee, Lee, Jung-A, Kim, Yoon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korean Society for Preventive Medicine 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4162118/
https://www.ncbi.nlm.nih.gov/pubmed/25139167
http://dx.doi.org/10.3961/jpmph.2014.47.4.206
_version_ 1782334649564921856
author Lee, Eun-Jung
Hwang, Soo-Hee
Lee, Jung-A
Kim, Yoon
author_facet Lee, Eun-Jung
Hwang, Soo-Hee
Lee, Jung-A
Kim, Yoon
author_sort Lee, Eun-Jung
collection PubMed
description OBJECTIVES: The hospital standardized mortality ratio (HSMR) has been widely used because it allows for robust risk adjustment using administrative data and is important for improving the quality of patient care. METHODS: All inpatients discharged from hospitals with more than 700 beds (66 hospitals) in 2008 were eligible for inclusion. Using the claims data, 29 most responsible diagnosis (MRDx), accounting for 80% of all inpatient deaths among these hospitals, were identified, and inpatients with those MRDx were selected. The final study population included 703 571 inpatients including 27 718 (3.9% of all inpatients) in-hospital deaths. Using logistic regression, risk-adjusted models for predicting in-hospital mortality were created for each MRDx. The HSMR of individual hospitals was calculated for each MRDx using the model coefficients. The models included age, gender, income level, urgency of admission, diagnosis codes, disease-specific risk factors, and comorbidities. The Elixhauser comorbidity index was used to adjust for comorbidities. RESULTS: For 26 out of 29 MRDx, the c-statistics of these mortality prediction models were higher than 0.8 indicating excellent discriminative power. The HSMR greatly varied across hospitals and disease groups. The academic status of the hospital was the only factor significantly associated with the HSMR. CONCLUSIONS: We found a large variation in HSMR among hospitals; therefore, efforts to reduce these variations including continuous monitoring and regular disclosure of the HSMR are required.
format Online
Article
Text
id pubmed-4162118
institution National Center for Biotechnology Information
language English
publishDate 2014
publisher Korean Society for Preventive Medicine
record_format MEDLINE/PubMed
spelling pubmed-41621182014-09-12 Variations in the Hospital Standardized Mortality Ratios in Korea Lee, Eun-Jung Hwang, Soo-Hee Lee, Jung-A Kim, Yoon J Prev Med Public Health Original Article OBJECTIVES: The hospital standardized mortality ratio (HSMR) has been widely used because it allows for robust risk adjustment using administrative data and is important for improving the quality of patient care. METHODS: All inpatients discharged from hospitals with more than 700 beds (66 hospitals) in 2008 were eligible for inclusion. Using the claims data, 29 most responsible diagnosis (MRDx), accounting for 80% of all inpatient deaths among these hospitals, were identified, and inpatients with those MRDx were selected. The final study population included 703 571 inpatients including 27 718 (3.9% of all inpatients) in-hospital deaths. Using logistic regression, risk-adjusted models for predicting in-hospital mortality were created for each MRDx. The HSMR of individual hospitals was calculated for each MRDx using the model coefficients. The models included age, gender, income level, urgency of admission, diagnosis codes, disease-specific risk factors, and comorbidities. The Elixhauser comorbidity index was used to adjust for comorbidities. RESULTS: For 26 out of 29 MRDx, the c-statistics of these mortality prediction models were higher than 0.8 indicating excellent discriminative power. The HSMR greatly varied across hospitals and disease groups. The academic status of the hospital was the only factor significantly associated with the HSMR. CONCLUSIONS: We found a large variation in HSMR among hospitals; therefore, efforts to reduce these variations including continuous monitoring and regular disclosure of the HSMR are required. Korean Society for Preventive Medicine 2014-07 2014-07-31 /pmc/articles/PMC4162118/ /pubmed/25139167 http://dx.doi.org/10.3961/jpmph.2014.47.4.206 Text en Copyright © 2014 The Korean Society for Preventive Medicine This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Lee, Eun-Jung
Hwang, Soo-Hee
Lee, Jung-A
Kim, Yoon
Variations in the Hospital Standardized Mortality Ratios in Korea
title Variations in the Hospital Standardized Mortality Ratios in Korea
title_full Variations in the Hospital Standardized Mortality Ratios in Korea
title_fullStr Variations in the Hospital Standardized Mortality Ratios in Korea
title_full_unstemmed Variations in the Hospital Standardized Mortality Ratios in Korea
title_short Variations in the Hospital Standardized Mortality Ratios in Korea
title_sort variations in the hospital standardized mortality ratios in korea
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4162118/
https://www.ncbi.nlm.nih.gov/pubmed/25139167
http://dx.doi.org/10.3961/jpmph.2014.47.4.206
work_keys_str_mv AT leeeunjung variationsinthehospitalstandardizedmortalityratiosinkorea
AT hwangsoohee variationsinthehospitalstandardizedmortalityratiosinkorea
AT leejunga variationsinthehospitalstandardizedmortalityratiosinkorea
AT kimyoon variationsinthehospitalstandardizedmortalityratiosinkorea