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...

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Main Authors: Eun-Jung Lee, Soo-Hee Hwang, Jung-A Lee, Yoon Kim
Format: Article
Language:English
Published: Korean Society for Preventive Medicine 2014-07-01
Series:Journal of Preventive Medicine and Public Health
Subjects:
Online Access:http://www.jpmph.org/upload/pdf/jpmph-47-4-206.pdf
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spelling doaj-16597a7bdd91488797333178e40eb25c2020-11-25T00:21:41ZengKorean Society for Preventive MedicineJournal of Preventive Medicine and Public Health1975-83752233-45212014-07-0147420621510.3961/jpmph.2014.47.4.2061788Variations in the Hospital Standardized Mortality Ratios in KoreaEun-Jung Lee0Soo-Hee Hwang1Jung-A Lee2Yoon Kim3 Medical Affairs, Janssen, Seoul, Korea Health Insurance Review & Assessment Research Institute, Health Insurance Review and Assessment Service, Seoul, Korea Institute of Health Policy and Management, Medical Research Center, Seoul National University, Seoul, Korea Institute of Health Policy and Management, Medical Research Center, Seoul National University, Seoul, KoreaObjectives: 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.http://www.jpmph.org/upload/pdf/jpmph-47-4-206.pdfQuality of health careOutcome assessmentHospital mortality
collection DOAJ
language English
format Article
sources DOAJ
author Eun-Jung Lee
Soo-Hee Hwang
Jung-A Lee
Yoon Kim
spellingShingle Eun-Jung Lee
Soo-Hee Hwang
Jung-A Lee
Yoon Kim
Variations in the Hospital Standardized Mortality Ratios in Korea
Journal of Preventive Medicine and Public Health
Quality of health care
Outcome assessment
Hospital mortality
author_facet Eun-Jung Lee
Soo-Hee Hwang
Jung-A Lee
Yoon Kim
author_sort Eun-Jung Lee
title Variations in the Hospital Standardized Mortality Ratios in Korea
title_short 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_sort variations in the hospital standardized mortality ratios in korea
publisher Korean Society for Preventive Medicine
series Journal of Preventive Medicine and Public Health
issn 1975-8375
2233-4521
publishDate 2014-07-01
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.
topic Quality of health care
Outcome assessment
Hospital mortality
url http://www.jpmph.org/upload/pdf/jpmph-47-4-206.pdf
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