- Variations in the Hospital Standardized Mortality Ratios in Korea
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Eun-Jung Lee, Soo-Hee Hwang, Jung-A Lee, Yoon Kim
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J Prev Med Public Health. 2014;47(4):206-215. Published online July 31, 2014
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DOI: https://doi.org/10.3961/jpmph.2014.47.4.206
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 Abstract
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- 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.
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Summary
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Citations
Citations to this article as recorded by  - Differences in trends in discharge location in a cohort of hospitalized patients with cancer and non-cancer diagnoses receiving specialist palliative care: A retrospective cohort study
Michael Bonares, Kalli Stillos, Lise Huynh, Debbie Selby
Palliative Medicine.2023; 37(8): 1241. CrossRef - Functional training and timed nutrition intervention in infectious medical patients
M Holst, L N Søndergaard, M D Bendtsen, J Andreasen
European Journal of Clinical Nutrition.2016; 70(9): 1039. CrossRef
- The Impact of COVID-19 on Admissions and In-hospital Mortality of Patients with Stroke in Korea: An Interrupted Time Series Analysis
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Youngs Chang, Soo-Hee Hwang, Haibin Bai, Seowoo Park, Eunbyul Cho, Dohoung Kim, Hyejin Lee, Jin Yong Lee
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Received August 8, 2024 Accepted October 2, 2024 Published online October 28, 2024
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DOI: https://doi.org/10.3961/jpmph.24.432
[Accepted]
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Abstract
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- Objectives
This study aimed to investigate the impact of COVID-19 on admission rates and in-hospital mortality among patients with ischemic and hemorrhagic stroke.
Methods
We constructed a dataset detailing the monthly hospitalizations and mortality rates of inpatients with stroke from January 2017 to December 2021. Employing an interrupted time series analysis, we explored the impact of COVID-19 on hospitalizations and 30-day in-hospital mortality among stroke patients.
Results
The number of ischemic stroke admissions decreased by 18.5%, from 5,335 to 4,348, immediately following the COVID-19 outbreak (p<0.001). The in-hospital mortality rate for ischemic stroke increased slightly from 3.3% to 3.4% immediately after the outbreak, although it showed a decreasing trend over time. The number of hemorrhagic stroke admissions fell by 7.5%, from 2,014 to 1,864, immediately following the COVID-19 outbreak. The 30-day in-hospital mortality rate for hemorrhagic stroke initially decreased from 12.9% to 12.7%, but subsequently showed an increasing trend.
Conclusions
We confirmed that COVID-19 impacted both the admission and death rates of stroke patients. The admission rate for both ischemic and hemorrhagic strokes decreased, while in-hospital mortality increased. Specifically, in-hospital mortality from ischemic stroke rose initially after the outbreak before stabilizing. Additionally, our findings indicate variable effects based on sex, age, and socioeconomic status, suggesting that certain groups may be more susceptible. This underscores the need to identify and support vulnerable populations to mitigate adverse health outcomes.
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