摘要
目的 利用DRGs综合绩效评价指标对某三级甲等医院预住院模式的成效进行评价,为预住院模式在控费体系下进一步发展提供参考依据.方法 选取2022年1月1日至2023年6月30日于该院办理预住院登记并成功入院的237例患者相关数据,并纳入同期普通入院的19 323例患者数据,两组患者的住院费用、住院天数差异采用曼-惠特尼秩和检验(Mann-Whitney U型检验),盈余占比差异采用卡方检验比较.采用熵值TOPSIS法对预住院管理模式的DRGs综合绩效进行评价.结果 预住院患者的住院日、材料费、检查费、化验费低于普通入院患者,差异具有统计学意义(P<0.05);盈余占比差异无统计学意义(P>0.05).综合绩效评价排名依次是普外科、肿瘤科、核医学科、血液内科、眼科.结论 预住院模式可有效降低患者材料费、检查费、化验费和住院时间,促进医院DRGs运营收支平衡;各科室可以根据自身情况选择收治方式和发展预住院优势病种.
Abstract
Objective To assess the cost-effectiveness of the pre-hospitalization model at a tertiary hospital using the comprehensive performance evaluation index of Diagnosis-Related Groups(DRGs),aiming to provide evidence for the advancement of the pre-hospitalization model under a cost containment framework.Methods Patient data for those who completed pre-hospitalization registration and were subsequently admitted to the hospital between January 1,2022,and June 30,2023,were extracted.The Mann-Whitney U test was performed to compare differences in hospitalization costs and length of stay between the two groups.Additionally,the Chi-square test was utilized to assess variations in the proportions of surplus outcomes.The entropy-based TOPSIS method was applied to evaluate the comprehensive performance of DRGs in the pre-hospitalization model.Results The duration of hospitalization,material costs,examination fees,and laboratory test fees in pre-hospitalized patients were found to be significantly lower than those for the general admitted patients(all P<0.05),while the difference in the proportion of surplus outcomes showed no statistical significance(P>0.05).The department of general surgery had the highest comprehensive performance,followed by the departments of oncology,nuclear medicine,hematology,and ophthalmology.Conclusion The pre-hospitalization model is effective in diminishing costs associated with materials,examinations,laboratory tests,and hospital stays,thereby facilitating the income-expenditure balance of the DRGs.Departments may select their own admission methodology and cultivate pre-hospitalization priority diseases based on their specific circumstances.
基金项目
2022年安徽医科大学校科研基金(2022xkj316)
维普
万方数据