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find Author "PAN Weibing" 1 results
  • Study of hospitalization expenses and optimization of case mix in patients with obstructive hydronephrosis based on decision tree model

    Objective To analyze the influencing factors of hospitalization costs of obstructive hydronephrosis and explore the optimal grouping of diagnosis-intervention packet (DIP), so as to provide a basis for hospitals to strengthen the cost control of diseases, improve the level of refined management, and improve the compensation mechanism of DIP expenses by medical insurance departments. Methods The homepage data of medical records of Pingshan District People’s Hospital of Shenzhen City from January 2019 to December 2021 were collected, and the information of the discharged patients with the International Classification of Diseases-10th revision code as N13.2 was selected. The factors affecting hospitalization costs were analyzed by single factor analyses and multiple stepwise linear regression, the main surgical methods, number of other operations, and influencing factors of expenses were used as classification nodes, and the decision tree model was used to group and predict costs. Results A total of 1319 patients were included, the median inpatient expense was 10889.59 yuan, and the interquartile range was 10943.89 yuan. The case classification, days of hospitalization, condition of admission, whether it was hospitalized for the first time, whether clinical pathway was implemented, the way of discharge, the number of other diagnoses, and admission path were important factors affecting the inpatient expenses, and 12 groups of case mixes and corresponding expense standards were formed. The reduction in variance was 86.10%, the maximum coefficient of variation was 0.33, and the cost analysis ratio was 96.25%. Conclusions Combining the DIP grouping principle and the multi-factor grouping strategy of diagnosis-related groups, the grouping of obstructive hydronephrosis cases constructed by decision tree model is reasonable and the cost standard is close to reality. The case mixes and cost criteria can provide data support and decision-making reference for hospitals and medical insurance institutions.

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