Capturing the trends in hospital standardized mortality ratios for pneumonia: a retrospective observational study in Japan (2010 to 2018).
10.1186/s12199-019-0842-4
- Author:
Rebeka AMIN
1
;
Yosuke HATAKEYAMA
2
;
Takefumi KITAZAWA
3
;
Kunichika MATSUMOTO
2
;
Shigeru FUJITA
2
;
Kanako SETO
2
;
Tomonori HASEGAWA
4
Author Information
1. Department of Social Medicine, Toho University Graduate School of Medicine, 5-21-16, Omori-nishi, Ota-ku, Tokyo, 143-8540, Japan.
2. Department of Social Medicine, Toho University School of Medicine, 5-21-16, Omori-nishi, Ota-ku, Tokyo, 143-8540, Japan.
3. Faculty of Health Sciences, Tokyo Kasei University, 2-15-1, Inariyama, Sayama-shi, Saitama, 350-1398, Japan.
4. Department of Social Medicine, Toho University School of Medicine, 5-21-16, Omori-nishi, Ota-ku, Tokyo, 143-8540, Japan. health@med.toho-u.ac.jp.
- Publication Type:Journal Article
- Keywords:
Benchmarking;
Health care/standards;
In-hospital mortality;
Japan;
Pneumonia;
Quality indicator
- From:Environmental Health and Preventive Medicine
2020;25(1):2-2
- CountryJapan
- Language:English
-
Abstract:
BACKGROUND:Pneumonia has a high human toll and a substantial economic burden in developed countries like Japan, where the crude mortality rate was 77.7 per 100,000 people in 2017. As this trend is going to continue with increasing number of the elderly multi-morbid population in Japan; monitoring performance over time is a social need to alleviate the disease burden. The study objective was to determine the characteristics of hospital standardized mortality ratios (HSMRs) for pneumonia in Japan from 2010 to 2018 to describe this trend.
METHODS:Data of the DPC (Diagnostic Procedures Combination) database were used, which is an administrative claims and discharge summary database for acute care in-patients in Japan. HSMRs were calculated using the actual and expected numbers of in-hospital deaths, the latter of which was calculated using logistic regression model, with a number of explanatory variables, e.g., age, sex, urgency of admission, mode of transportation, patient volume per month in each hospital, A-DROP score, and Charlson comorbidity index (CCI). We constructed two HSMR models: a single-year model, which included hospitals with > 10 in-patients per month and, a 9-year model, which included those hospitals with complete 9-year data. Predictive accuracy of the logistic models was assessed using c-index (area under receiver operating curve).
RESULTS:Total 230,372 patients were included for the analysis over the 9-year study period. Calculated HSMRs showed wide variation among hospitals. The proportion of hospitals with HSMR less than 100 increased from 36.4% in 2010 to 60.6% in 2018. Both models showed good predictive ability with a c-statistic of 0.762 for the 9-year model, and no less than 0.717 for the single-year model.
CONCLUSION:This study denoted that HSMRs of pneumonia can be calculated using DPC data in Japan and revealed significant variations among hospitals with comparable case-mixes. Therefore, HSMR can be used as yet another measure to help improve quality of care over time if other indicators are examined in parallel and to get a clear picture of where hospitals excel and lack.
