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Ma Y, Li L, Yu L, He W, Yi L, Tang Y, Li J, Zhong Z, Wang M, Huang S, Xiong Y, Xiao P, Huang Y. Optimization of Diagnosis-Related Groups for 14,246 Patients with Uterine Leiomyoma in a Single Center in Western China Using a Machine Learning Model. Risk Manag Healthc Policy 2024; 17:473-485. [PMID: 38444948 PMCID: PMC10913598 DOI: 10.2147/rmhp.s442502] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Accepted: 02/23/2024] [Indexed: 03/07/2024] Open
Abstract
Background Uterine leiomyoma (UL) is one of the most common benign tumors in women, and its incidence is gradually increasing in China. The clinical complications of UL have a negative impact on women's health, and the cost of treatment poses a significant burden on patients. Diagnosis-related groups (DRG) are internationally recognized as advanced healthcare payment management methods that can effectively reduce costs. However, there are variations in the design and grouping rules of DRG policies across different regions. Therefore, this study aims to analyze the factors influencing the hospitalization costs of patients with UL and optimize the design of DRG grouping schemes to provide insights for the development of localized DRG grouping policies. Methods The Mann-Whitney U-test or the Kruskal-Wallis H-test was employed for univariate analysis, and multiple stepwise linear regression analysis was utilized to identify the primary influencing factors of hospitalization costs for UL. Case combination classification was conducted using the exhaustive chi-square automatic interactive detection (E-CHAID) algorithm within a decision tree framework. Results Age, occupation, number of hospitalizations, type of medical insurance, Transfer to other departments, length of stay (LOS), type of UL, admission condition, comorbidities and complications, type of primary procedure, other types of surgical procedures, and discharge method had a significant impact on hospitalization costs (P<0.05). Among them, the type of primary procedure, other types of surgical procedures, and LOS were the main factors influencing hospitalization costs. By incorporating the type of primary procedure, other types of surgical procedures, and LOS into the decision tree model, patients were divided into 11 DRG combinations. Conclusion Hospitalization costs for UL are mainly related to the type of primary procedure, other types of surgical procedures, and LOS. The DRG case combinations of UL based on E-CHAID algorithm are scientific and reasonable.
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Affiliation(s)
- Yuan Ma
- Department of Medical Record Management, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, People’s Republic of China
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, Sichuan, People’s Republic of China
| | - Li Li
- Department of Medical Record Management, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, People’s Republic of China
| | - Li Yu
- Department of Medical Record Management, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, People’s Republic of China
| | - Wei He
- Department of Medical Record Management, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, People’s Republic of China
| | - Ling Yi
- Department of Medical Record Management, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, People’s Republic of China
| | - Yuxin Tang
- Department of Medical Record Management, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, People’s Republic of China
| | - Jijie Li
- Department of Medical Record Management, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, People’s Republic of China
| | - Zhigang Zhong
- Department of Prevention, Office of Cancer Prevention and Treatment, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Cancer Hospital Affiliate to University of Electronic Science and Technology of China, Chengdu, Sichuan, People’s Republic of China
| | - Meixian Wang
- National Center for Birth Defects Monitoring, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, People’s Republic of China
| | - Shiyao Huang
- Chinese Evidence-Based Medicine Center, West China Hospital, Sichuan University, Chengdu, Sichuan, People’s Republic of China
- NMPA Key Laboratory for Real World Data Research and Evaluation in Hainan, Chengdu, Sichuan, People’s Republic of China
| | - Yiquan Xiong
- Chinese Evidence-Based Medicine Center, West China Hospital, Sichuan University, Chengdu, Sichuan, People’s Republic of China
- NMPA Key Laboratory for Real World Data Research and Evaluation in Hainan, Chengdu, Sichuan, People’s Republic of China
| | - Pei Xiao
- Medical Insurance Office, West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, People’s Republic of China
| | - Yuxiang Huang
- Department of Medical Record Management, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, People’s Republic of China
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Study of Hospitalization Costs in Patients with Cerebral Ischemia Based on E-CHAID Algorithm. JOURNAL OF HEALTHCARE ENGINEERING 2022; 2022:3978577. [PMID: 35548482 PMCID: PMC9085341 DOI: 10.1155/2022/3978577] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Accepted: 04/06/2022] [Indexed: 02/05/2023]
Abstract
Background. The aging of the population has led to a rapid increase in the prevalence of most neurological diseases between 1990 and 2016, with a growth rate of up to 117%, which has put enormous pressure on medical insurance funds. As one of the core diseases of disease diagnosis grouping, the hospitalization cost composition and grouping research of patients with cerebral ischemic disease can help to determine scientific payment standards and reduce the economic burden of patients. Aim. We aimed to understand the cost composition and influencing factors of hospitalized patients with cerebral ischemic diseases and to identify a reasonable cost grouping scheme. Methods. The data come from the homepage of medical records of inpatients with cerebral ischemia in a tertiary hospital in Sichuan Province from 2018 to 2020. After cleaning the data, a total of 5,204 pieces of data were obtained. Nonparametric tests and gamma regression models were used to explore the influencing factors of hospitalization costs. Taking the influencing factors as the predictor variables and the hospitalization cost as the target variable, the exhaustive Chi-squared automatic interaction detector (E-CHAID) algorithm was used to form the costs grouping, and the payment standard of the hospitalization cost for each group was determined. The rationality of cost grouping was evaluated by coefficient of variation (CV) and Kruskal–Wallis H test. Results. From 2018 to 2020, the average hospital stay of 5,204 inpatients with cerebral ischemic disease was 10.70 days, and the average hospitalization cost was 17,206.09 RMB yuan. Among the hospitalization costs, diagnosis costs and drug costs accounted for the highest proportion, accounting for 41.18% and 22.38%, respectively, in 2020. Gender, age, admission route, comorbidities and complications, super length of stay (>30 days), and discharge mode had significant effects on hospitalization costs (P < 0.05). Patients were divided into 10 cost groups, and the grouping nodes included comorbidities and complications, discharge mode, age, gender, and admission route. The CV of 9 of the 10 cost groups is less than or equal to 1. The Kruskal–Wallis H test showed that the difference between groups was statistically significant (P < 0.05). Conclusion. The cost grouping of patients with cerebral ischemic diseases based on the E-CHAID algorithm is reasonable. This study examined the effects of super length of stay (>30 days), comorbidities and complications, and age on hospitalization cost in patients with cerebral ischemic disease. This study can provide a theoretical basis for advancing the China Healthcare Security Diagnosis Related Groups (CHS-DRG) grouping program and medical expense payment, thereby reducing the disease burden of patients.
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Cost Control of Treatment for Cerebrovascular Patients Using a Machine Learning Model in Western China. JOURNAL OF HEALTHCARE ENGINEERING 2021; 2021:6158961. [PMID: 34853670 PMCID: PMC8629638 DOI: 10.1155/2021/6158961] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Accepted: 11/08/2021] [Indexed: 11/30/2022]
Abstract
Background Cerebrovascular disease has been the leading cause of death in China since 2017, and the control of medical expenses for these diseases is an urgent issue. Diagnosis-related groups (DRG) are increasingly being used to decrease the costs of healthcare worldwide. However, the classification variables and rules used vary from region to region. Of these variables, the question of whether the length of stay (LOS) should be used as a grouping variable is controversial. Aim To identify the factors influencing inpatient medical expenditure in cerebrovascular disease patients. The performance of two sets of classification rules, and the effects of the extent of control of unreasonable medical treatment, were compared, to investigate whether the classification variables should include LOS. Methods Data from 45,575 inpatients from a Healthcare Security Administration of a city in western China were used. Kruskal–Wallis H tests were used for single-factor analysis, and multiple linear stepwise regression was used to determine the main factors. A chi-squared automatic interaction detector (CHAID) algorithm was built as a decision tree model for grouping related data. The intensity of oversupply of service was controlled step by step from 10% to 100%, and the performance was calculated for each group. Results The average hospitalization cost was 1,284 US dollars, and the total was 51.17 million US dollars. Of this, 43.42 million were paid by the government, and 7.75 million were paid by individuals. Factors including gender, age, type of insurance, level of hospital, LOS, surgery, therapeutic outcomes, main concomitant disease, and hypertension significantly influenced inpatient expenditure (P < 0.05). Incorporating LOS, the patients were divided into seven DRG groups, while without LOS, the patients were divided into eight DRG groups. More clinical variables were needed to achieve good results without LOS. Of the two rule sets, smaller coefficient of variation (CV) and a lower upper limit for patient costs were found in the group including LOS. Using this type of economic control, 3.35 million US dollars could be saved in one year.
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Chen H, Dong Q, Zheng X. Efficacy of Shexiang Baoxin Pills for the treatment of unstable angina pectoris: Protocol of systemic review and meta-analysis. Medicine (Baltimore) 2019; 98:e17119. [PMID: 31517850 PMCID: PMC6750257 DOI: 10.1097/md.0000000000017119] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND Shexiang Baoxin Pills (SBP) is widely used for the treatment of unstable angina pectoris (UAP) in China. However, the clinical evidence on the efficacy of SBP for the treatment of UAP is not well concluded. METHODS Seven electronic databases will be searched for eligible studies: MEDLINE, EMBASE, The Cochrane Library, Wanfang database, Chinese National Knowledge Infrastructure database, VIP database, and Chinese Biological and Medicine database. Data of included studies will be extracted, and quality will be evaluated. Data synthesis will be performed using RevMan software. Subgroup analysis and sensitivity analysis will also be carried out. Publication bias will be evaluated using funnel plot if included studies are sufficient. RESULTS This systemic review and meta-analysis will provide synthesized result of clinical efficacy of SBP for the treatment of UAP. CONCLUSIONS This systemic review and meta-analysis will provide high-quality evidence on the clinical efficacy of SBP for the treatment of UAP. REGISTRATION PEROSPERO CRD42019124668.
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