Current Situation and Consideration of Refinement of Hospital Team Service based on Value-based Medicine
Objective To describe and analyze the current situation of the four same type of departments in an hospital in order to provide a reference for the construction of"the most cost-effective medical care".Methods The CN-DRG were used to automatically group and compare the medical capacity and inpatient service efficiency of the hospital department groups,and in the refined analysis,one DRG disease group of in situ cancer and non-malignant disease loss uterine surgery and single species uterine fibroid was included,and the Kruskal-Wallis H test was used to further compare the differences in length of stay and various costs.Results It included a total of 22630 patients,whose weights varied from a maximum of 3948.62 in diagnostic group 1 to a minimum of 133.55 in diagnostic group 11.The cost consumption indexes ranged from a minimum of 0.89 in diagnostic group 5 to a maximum of 1.04 in diagnostic group 2,while the time consumption indexes ranged from a minimum of 0.48 in diagnostic group 11 to a maximum of 0.81 in diagnostic group 5.When comparing the diagnostic groups,there were statistically significant differences(P＜0.05)in hospitalization days,total cost,diagnostic cost,therapeutic cost,and cost of supplies.Specifically,when comparing the diagnostic and treatment groups within departments,the differences in hospitalization days and all costs were statistically significant(P＜0.05)in departments 1 and 2,the differences in diagnostic cost,therapeutic cost,and cost of supplies were statistically significant(P＜0.05)in department 3.Conclusion There exists a notable disparity in the extent to which each diagnostic and treatment group contributes to the hospital's service capacity and cost variability.Consequently,it is necessary to reasonably evaluate the length of hospital stay and medical cost of patients to achieve the highest cost-effective medical treatment.
diagnosis and treatment teamvalue medicinesingle diseaseDRG
万方数据
维普
