目的 探讨通过优化病案首页质控体系提高误入DRG低权重组病例转出率的效果。方法 采用PDCA循环法，通过实施分层级编码培训、基于AI赋能的专项质控模式及智能化反馈机制构建等系统性地改进措施优化质控体系。通过对比分析质控系统优化前后（2022年1—7月和2023年1—7月）DRG低权重组病例的病案首页质控过程、“经质控低权重病例入组率”和“误入低权重组病例转出率”等指标，评估质控体系优化的实施效果。结果 质控体系优化后，低权重组病例转出率由3.27%提升至4.15%（P=0.018），经质控低权重病例入组率由16.98%降至14.96%（P＜0.001）。结论 AI赋能的专项质控、分层级编码培训与智能化反馈机制三项措施并举可以系统优化质控体系，进而提升DRG低权重组病例转出率。
Objective To investigate the effect of optimizing the medical record front page quality control system on improving the transfer-out rate of cases mistakenly assigned to low-weight DRG groups．Methods The Plan-Do-Check-Act（PDCA）cycle methodology was employed．Systemic improvements were implemented to optimize the medical record front page quality control system，including hierarchical coding training，innovation of a specialized quality control model based on AI empowerment，and establishment of an intelligent feedback mechanism．The implementation effectiveness was evaluated by comparative analysis of the following indicators before（January-July 2022）and after（January-July 2023）optimization：the medical record quality control process for low-weight DRG cases，the rate of low-weight cases assigned to groups after quality control，and the transfer-out rate of cases mistakenly entering low-weight groups．Results After optimizing the medical record front page quality control system，the transfer-out rate of cases from low-weight groups increased from 3.27% to 4.15%（P=0.018），while the rate of low-weight cases assigned to groups after quality control decreased from 16.98% to 14.96%（P＜0.001）．Conclusions Implementing a three-pronged approach—AI-powered specialized quality control，hierarchical coding training，and an intelligent feedback mechanism—can systematically optimize the medical record front page quality control system，thereby improving the transfer-out rate of cases mistakenly assigned to low-weight DRG groups．
目的 探寻病案首页国际疾病分类(ICD)编码的准确率对按疾病诊断相关分组(DRGs)分值付费影响。方法 整体抽取2019年心血管内科和脊柱关节外科医保病例,分析DRGs分值付费存在的问题,对全院病案首页ICD编码采取相应的干预措施。结果 2019年病案首页ICD编码准确率为81.55%,DRGs分值付费亏损2 812 804.7元,经干预后,2020年病案首页ICD编码准确率为97.13%,DRGs分值付费结余14 089 039.36元。结论 准确、规范的填写病案首页ICD编码,提高病案首页ICD编码的准确率,避免医院在DRGs分值付费模式下出现亏损有重要意义。
Objective To investigate the influence of the front page International Classification of Diseases(ICD) coding accuracy of medical records on diagnosis related groups(DRGs) score payment system.Methods Medical insurance cases of cardiovascular medicine and spine and joint surgery in 2019 were totally selected,the problems of DRGs score payment system were investigated and analyzed,and managements improving the ICD coding on the medical records of discharged patients were carried out.Results In 2019,the accuracy of ICD coding of medical records was 81.55%,and the DRGs score payment system had lost 2 812 804.7 yuan.After improving,in 2020,the ICD coding accuracy achieved 97.13%,and DRGs score payment system had a positive balance of 14 089 039.36 yuan.Conclusions The accuracy and standardization of ICD coding on the medical records is of great significance in avoiding losses on DRGs score payment system.
目的 调查分析病案首页疾病诊断存在的问题,以提出针对性的干预对策。方法 由病案科编码员根据《卫生部关于修订下发住院病案首页的通知》相关规定,对抽取的4200份病案首页的疾病诊断进行检查,对疾病诊断问题分类记录,同时对其发生原因进行问卷调查,建立相应数据库,应用Excel统计工具进行统计分析。结果 共748份的疾病诊断存在问题,发生率高达17.8%,包括疾病诊断中主要诊断选择错误8.3%、疾病诊断的名称不规范7.6%,以及漏诊问题1.8%。疾病诊断存在问题发生率较高的临床科室为内分泌科38.0%,骨科科32.8%,肿瘤科31.6%。在读研究生最容易出现疾病诊断问题,发生率高达48.0%。结论 对疾病诊断存在问题的高发临床医师群体和临床科室进行针对性干预对策,有望降低病案首页疾病诊断问题的发生率。
Objective To investigate the defects analysis and targeted intervention on the diseases diagnosis in the home pages of medical records. Methods To conduct an inspection analysis on the four thousand and two hundred medical records according to the related requirements of “Notification on Standard writing in Home Pages of Hospitalization Medical Records announced by the Ministry of Health” by professional medical records staff.They found out and classified the defects on the diseases diagnosis in the home pages of medical records,at the same time,questionnaire survey were carried on to investigate the related causes,and the corresponding database establish ed.Excel statistical tools were applied for statistical analysis. Results There were defects on the diseases diagnosis in a total of seven hundred and forty-eight cases,the incidence of which was 17.8%,including 8.3% of mistakes of main diagnosis,7.6% of lack of standardization in diagnosis names,1.8% of missed diagnosis respectively.Defects on the diseases diagnosis occurred in a higher rate in the clinical departments,such as department of endocrine with 38.0%,department of orthopedics with 32.8%,and department of oncology with 31.6%.Graduate students most prone to make mistakes with defects on the diseases diagnosis,the incidence of which was 48.0%. Conclusion Targeted interventions to clinician groups and clinical departments with high incidence of defects on the diseases diagnosis,is expected to reduce the incidence of which in the home pages of medical records.
