Analysis of hospitalization costs related to fall injuries in elderly patients

Fei-Yue Su; Mei-Ling Fu; Qing-Hua Zhao; Huan-Huan Huang; Di Luo; Ming-Zhao Xiao

doi:10.12998/wjcc.v9.i6.1271

Analysis of hospitalization costs related to fall injuries in elderly patients

World J Clin Cases. 2021 Feb 26;9(6):1271-1283. doi: 10.12998/wjcc.v9.i6.1271.

Authors

Fei-Yue Su¹, Mei-Ling Fu², Qing-Hua Zhao³, Huan-Huan Huang³, Di Luo¹, Ming-Zhao Xiao⁴

Affiliations

¹ Department of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China.
² Department of Medical Insurance, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China.
³ Department of Nursing, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China.
⁴ Department of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China. xmz.2004@163.com.

Abstract

Background: With the aging world population, the incidence of falls has intensified and fall-related hospitalization costs are increasing. Falls are one type of event studied in the health economics of patient safety, and many developed countries have conducted such research on fall-related hospitalization costs. However, China, a developing country, still lacks large-scale studies in this area.

Aim: To investigate the factors related to the hospitalization costs of fall-related injuries in elderly inpatients and establish factor-based, cost-related groupings.

Methods: A retrospective study was conducted. Patient information and cost data for elderly inpatients (age ≥ 60 years, n = 3362) who were hospitalized between 2016 and 2019 due to falls was collected from the medical record systems of two grade-A tertiary hospitals in China. Quantile regression (QR) analysis was used to identify the factors related to fall-related hospitalization costs. A decision tree model based on the chi-squared automatic interaction detector algorithm for hospitalization cost grouping was built by setting the factors in the regression results as separation nodes.

Results: The total hospitalization cost of fall-related injuries in the included elderly patients was 180479203.03 RMB, and the reimbursement rate of medical benefit funds was 51.0% (92039709.52 RMB/180479203.03 RMB). The medical material costs were the highest component of the total hospitalization cost, followed (in order) by drug costs, test costs, treatment costs, integrated medical service costs and blood transfusion costs The QR results showed that patient age, gender, length of hospital stay, payment method, wound position, wound type, operation times and operation type significantly influenced the inpatient cost (P < 0.05). The cost grouping model was established based on the QR results, and age, length of stay, operation type, wound position and wound type were the most important influencing factors in the model. Furthermore, the cost of each combination varied significantly.

Conclusion: Our grouping model of hospitalization costs clearly reflected the key factors affecting hospitalization costs and can be used to strengthen the reasonable control of these costs.

Keywords: Decision tree model; Elderly; Falls; Hospitalization costs; Prevention; Quantile regression model.