%0 Journal Article
%T Retrospective analysis of hospitalization costs using two payment systems: the diagnosis related groups (DRG) and the Queralt system, a newly developed case-mix tool for hospitalized patients.
%A Folguera J
%A Buj E
%A Monterde D
%A Carot-Sans G
%A Cano I
%A Piera-Jiménez J
%A Arrufat M
%J Health Econ Rev
%V 14
%N 1
%D 2024 Jun 26
%M 38922476
%F 2.118
%R 10.1186/s13561-024-00522-6
%X <B>BACKGROUND: </B>Hospital services are typically reimbursed using case-mix tools that group patients according to diagnoses and procedures. We recently developed a case-mix tool (i.e., the Queralt system) aimed at supporting clinicians in patient management. In this study, we compared the performance of a broadly used tool (i.e., the APR-DRG) with the Queralt system.<BR><B>METHODS: </B>Retrospective analysis of all admissions occurred in any of the eight hospitals of the Catalan Institute of Health (i.e., approximately, 30% of all hospitalizations in Catalonia) during 2019. Costs were retrieved from a full cost accounting. Electronic health records were used to calculate the APR-DRG group and the Queralt index, and its different sub-indices for diagnoses (main diagnosis, comorbidities on admission, andcomplications occurred during hospital stay) and procedures (main and secondary procedures). The primary objective was the predictive capacity of the tools; we also investigated efficiency and within-group homogeneity.<BR><B>RESULTS: </B>The analysis included 166,837 hospitalization episodes, with a mean cost of € 4,935 (median 2,616; interquartile range 1,011-5,543). The components of the Queralt system had higher efficiency (i.e., the percentage of costs and hospitalizations covered by increasing percentages of groups from each case-mix tool) and lower heterogeneity. The logistic model for predicting costs at pre-stablished thresholds (i.e., 80th, 90th, and 95th percentiles) showed better performance for the Queralt system, particularly when combining diagnoses and procedures (DP): the area under the receiver operating characteristics curve for the 80th, 90th, 95th cost percentiles were 0.904, 0.882, and 0.863 for the APR-DRG, and 0.958, 0.945, and 0.928 for the Queralt DP; the corresponding values of area under the precision-recall curve were 0.522, 0.604, and 0.699 for the APR-DRG, and 0.748, 0.7966, and 0.834 for the Queralt DP. Likewise, the linear model for predicting the actual cost fitted better in the case of the Queralt system.<BR><B>CONCLUSIONS: </B>The Queralt system, originally developed to predict hospital outcomes, has good performance and efficiency for predicting hospitalization costs.