Abstract
BackgroundRisk 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.MethodsUsing 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.ResultsOf 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).ConclusionsProcedure-based severity index predicted mortality well, suggesting that procedure records in administrative database are useful for risk adjustment.Electronic supplementary materialThe online version of this article (doi:10.1186/s12913-015-0889-x) contains supplementary material, which is available to authorized users.
Highlights
Risk adjustment is important in studies using administrative databases
Yamana et al BMC Health Services Research (2015) 15:261 addition to patients’ demographic characteristics, comorbid illnesses recorded in administrative data enabled risk adjustment using measures such as the Charlson comorbidity index (CCI) [11]
Data source The Diagnosis Procedure Combination database is a national administrative database of acute-care inpatients in Japan that is linked with a payment system
Summary
Risk adjustment is important in studies using administrative databases. Utilization of diagnostic and therapeutic procedures can represent patient severity, the usability of procedure records in risk adjustment is not well-documented. Risk adjustment is an important component in clinical epidemiology and health services research using administrative databases, but its methods remain controversial. Administrative databases are widely used in studies because of their availability and large sample sizes, and riskadjusted mortality is employed as one of the outcome measures. Previous studies have shown that the performance of risk-adjustment models using administrative databases improves when detailed clinical information is added. In. Yamana et al BMC Health Services Research (2015) 15:261 addition to patients’ demographic characteristics, comorbid illnesses recorded in administrative data enabled risk adjustment using measures such as the Charlson comorbidity index (CCI) [11]. An alternative method has been reported, in which surgeries and major therapeutic procedures are associated with in-hospital death [20]
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