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Background:With the rising incidence as well as the medical expenditure among patients with unstable angina pectoris, the research aimed to investigate the inpatient medical expenditure through the combination of diagnosis-related groups (DRGs) among patients with unstable angina pectoris in a Grade A tertiary hospital to conduct the referential standards of medical costs for the diagnosis.Methods:Single-factor analysis and multiple linear stepwise regression method were used to investigate 3933 cases between 2014 and 2016 in Beijing Hospital (China) whose main diagnosis was defined as unstable angina pectoris to determine the main factors influencing the inpatient medical expenditure, and decision tree method was adopted to establish the model of DRGs grouping combinations.Results:The major influential factors of inpatient medical expenditure included age, operative method, therapeutic effects as well as comorbidity and complications (CCs) of the disease, and the 3933 cases were divided into ten DRGs by four factors: age, CCs, therapeutic effects, and the type of surgery with corresponding inpatient medical expenditure standards setup. Data of nonparametric test on medical costs among different groups were all significant (P < 0.001, by Kruskal-Wallis test), with R2 = 0.53 and coefficient of variation (CV) = 0.524.Conclusions:The classification of DRGs by adopting the type of surgery as the main branch node to develop cost control standards in inpatient treatment of unstable angina pectoris is conducive in standardizing the diagnosis and treatment behaviors of the hospital and reducing economic burdens among patients.

Background:Cervical cancer shows a growing incidence and medical cost in recent years that has increased severe financial pressure on patients and medical insurance institutions. This study aimed to investigate the medical economic characteristics of cervical cancer patients with different payment modes within a Grade A tertiary hospital to provide evidence and suggestions for inpatient cost control and to verify the application of Gamma model in medical cost analysis.Methods:The basic and cost information of cervical cancer cases within a Grade A tertiary hospital in the year 2011–2016 were collected. The Gamma model was adopted to analyze the differences in each cost item between medical insured patient and uninsured patients. Meanwhile, the marginal means of different cost items were calculated to estimate the influence of payment modes toward different medical cost items among cervical cancer patients in the study.Results:A total of 1321 inpatients with cervical cancer between the 2011 and 2016 were collected through the medical records system. Of the 1321 cases, 65.9% accounted for medical insured patients and 34.1% were uninsured patients. The total inpatient medical expenditure of insured patients was RMB 29,509.1 Yuan and uninsured patients was RMB 22,114.3 Yuan, respectively. Payment modes, therapeutic options as well as the recurrence and metastasis of tumor toward the inpatient medical expenditures between the two groups were statistically significant. To the specifics, drug costs accounted for 37.7% and 33.8% of the total, surgery costs accounted for 21.5% and 25.5%, treatment costs accounted for 18.7% and 16.4%, whereas the costs of imaging and laboratory examinations accounted for 16.4% and 15.2% for the insured patient and uninsured patients, respectively. As the effects of covariates were controlled, the total hospitalization costs, drug costs, treatment costs as well as imaging and laboratory examination costs showed statistical significance. The total hospitalization costs, drug costs, treatment costs as well as imaging and laboratory examination costs of insured patient were 1.33, 1.42, 1.52, and 1.44 times of uninsured patients.Conclusions:The analysis of different payment modes toward the medical economic characteristics based on Gamma model is basically rational. Medical payment modes are having certain influence toward the hospitalization expenses of cervical cancer patients in an extent, as drug costs, treatment costs, and examination costs appear to be the main causes.

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BackgroundMedical disputes are common in hospitals and a major challenge for the operations of medical institutions. However, few studies have looked into the association between medical disputes and hospital legal constructions. The purpose of the study was to investigate the relationship between hospital legal constructions and medical disputes, and it also aimed to develop a nomogram to estimate the likelihood of medical disputes.MethodsBetween July and September 2021, 2,716 administrators from 130 hospitals were enrolled for analysis. The study collected seventeen variables for examination. To establish a nomogram, administrators were randomly split into a training group (n = 1,358) and a validation group (n = 1,358) with a 50:50 ratio. The nomogram was developed using data from participants in the training group, and it was validated in the validation group. The nomogram contained significant variables that were linked to medical disputes and were identified by multivariate analysis. The nomogram's predictive performance was assessed utilizing discriminative and calibrating ability. A web calculator was developed to be conducive to model utility.ResultsMedical disputes were observed in 41.53% (1,128/2,716) of participants. Five characteristics, including male gender, higher professional ranks, longer length of service, worse understanding of the hospital charters, and worse construction status of hospital rule of law, were significantly associated with more medical disputes based on the multivariate analysis. As a result, these variables were included in the nomogram development. The AUROC was 0.67 [95% confident interval (CI): 0.64–0.70] in the training group and 0.68 (95% CI: 0.66–0.71) in the validation group. The corresponding calibration slopes were 1.00 and 1.05, respectively, and intercepts were 0.00 and −0.06, respectively. Three risk groups were created among the participants: Those in the high-risk group experienced medical disputes 2.83 times more frequently than those in the low-risk group (P &lt; 0.001).ConclusionMedical dispute is prevailing among hospital administrators, and it can be reduced by the effective constructions of hospital rule of law. This study proposes a novel nomogram to estimate the likelihood of medical disputes specifically among administrators in tertiary hospitals, and a web calculator can be available at https://ymgarden.shinyapps.io/Predictionofmedicaldisputes/.