title: Procedure-based severity index for inpatients: development and validation using administrative database.
abstract: BACKGROUND
  Risk adjustment is important in studies using administrative databases. Although utilization of diagnostic and therapeutic procedures can represent patient severity, the usability of procedure records in risk adjustment is not well-documented. Therefore, we aimed to develop and validate a severity index calculable from procedure records.
  
  
  METHODS
  Using the Japanese nationwide Diagnosis Procedure Combination database of acute-care hospitals, we identified patients discharged between 1 April 2012 and 31 March 2013 with an admission-precipitating diagnosis of acute myocardial infarction, congestive heart failure, acute cerebrovascular disease, gastrointestinal hemorrhage, pneumonia, or septicemia. Subjects were randomly assigned to the derivation cohort or the validation cohort. In the derivation cohort, we used multivariable logistic regression analysis to identify procedures performed on admission day which were significantly associated with in-hospital death, and a point corresponding to regression coefficient was assigned to each procedure. An index was then calculated in the validation cohort as sum of points for performed procedures, and performance of mortality-predicting model using the index and other patient characteristics was evaluated.
  
  
  RESULTS
  Of the 539 385 hospitalizations included, 270 054 and 269 331 were assigned to the derivation and validation cohorts, respectively. Nineteen significant procedures were identified from the derivation cohort with points ranging from -3 to 23, producing a severity index with possible range of -13 to 69. In the validation cohort, c-statistic of mortality-predicting model was 0.767 (95 % confidence interval: 0.764-0.770). The ω-statistic representing contribution of the index relative to other variables was 1.09 (95 % confidence interval: 1.03-1.17).
  
  
  CONCLUSIONS
  Procedure-based severity index predicted mortality well, suggesting that procedure records in administrative database are useful for risk adjustment.
authors.affiliation: Department of Clinical Epidemiology and Health Economics, School of Public Health, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan. yamana-tky@umin.ac.jp.|Bunkyo City Public Health Center, 1-16-21 Kasuga, Bunkyo-ku, Tokyo, 112-8555, Japan. yamana-tky@umin.ac.jp.
authors.forename: Hayato
authors.initials: H
authors.lastname: Yamana
authors.affiliation: Department of Clinical Epidemiology and Health Economics, School of Public Health, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan. ptmatsui-tky@umin.ac.jp.
authors.forename: Hiroki
authors.initials: H
authors.lastname: Matsui
authors.affiliation: Department of Health Policy and Informatics, Tokyo Medical and Dental University Graduate School of Medicine, 1-5-45 Yushima, Bunkyo-ku, Tokyo, 113-8510, Japan. kfushimi.hci@tmd.ac.jp.
authors.forename: Kiyohide
authors.initials: K
authors.lastname: Fushimi
authors.affiliation: Department of Clinical Epidemiology and Health Economics, School of Public Health, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan. yasunagah-tky@umin.ac.jp.
authors.forename: Hideo
authors.initials: H
authors.lastname: Yasunaga
mesh_terms: D000208:Acute Disease; D000328:Adult; D000368:Aged; D016208:Databases, Factual; D005260:Female; D006333:Heart Failure / Q000401:mortality; D006760:Hospitalization; D006801:Humans; D007297:Inpatients; D008297:Male; D008875:Middle Aged; D011014:Pneumonia / Q000401:mortality; D020379:Risk Adjustment; D012720:Severity of Illness Index