論文

査読有り
2014年12月

Development of a risk-adjusted in-hospital mortality prediction model for community-acquired pneumonia: a retrospective analysis using a Japanese administrative database

BMC PULMONARY MEDICINE
  • Hironori Uematsu
  • ,
  • Susumu Kunisawa
  • ,
  • Noriko Sasaki
  • ,
  • Hiroshi Ikai
  • ,
  • Yuichi Imanaka

14
開始ページ
203
終了ページ
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1186/1471-2466-14-203
出版者・発行元
BIOMED CENTRAL LTD

Background: Community-acquired pneumonia (CAP) is a common cause of patient hospitalization and death, and its burden on the healthcare system is increasing in aging societies. Here, we develop and internally validate risk-adjustment models and scoring systems for predicting mortality in CAP patients to enable more precise measurements of hospital performance.
Methods: Using a multicenter administrative claims database, we analyzed 35,297 patients hospitalized for CAP who had been discharged between April 1, 2012 and September 30, 2013 from 303 acute care hospitals in Japan. We developed hierarchical logistic regression models to analyze predictors of in-hospital mortality, and validated the models using the bootstrap method. Discrimination of the models was assessed using c-statistics. Additionally, we developed scoring systems based on predictors identified in the regression models.
Results: The 30-day in-hospital mortality rate was 5.8%. Predictors of in-hospital mortality included advanced age, high blood urea nitrogen level or dehydration, orientation disturbance, respiratory failure, low blood pressure, high C-reactive protein levels or high degree of pneumonic infiltration, cancer, and use of mechanical ventilation or vasopressors. Our models showed high levels of discrimination for mortality prediction, with a c-statistic of 0.89 (95% confidence interval: 0.89-0.90) in the bootstrap-corrected model. The scoring system based on 8 selected variables also showed good discrimination, with a c-statistic of 0.87 (95% confidence interval: 0.86-0.88).
Conclusions: Our mortality prediction models using administrative data showed good discriminatory power in CAP patients. These risk-adjustment models may support improvements in quality of care through accurate hospital evaluations and inter-hospital comparisons.

Web of Science ® 被引用回数 : 16

リンク情報
DOI
https://doi.org/10.1186/1471-2466-14-203
PubMed
https://www.ncbi.nlm.nih.gov/pubmed/25514976
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000347254600001&DestApp=WOS_CPL
ID情報
  • DOI : 10.1186/1471-2466-14-203
  • ISSN : 1471-2466
  • PubMed ID : 25514976
  • Web of Science ID : WOS:000347254600001

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