[1]蔡金花,郭 洁,李政稷.DRGs背景下感染科疾病入组率及入组异常原因分析[J].医学信息,2026,39(01):75-78.[doi:10.3969/j.issn.1006-1959.2026.01.012]
　CAI Jinhua,GUO Jie,LI Zhengji.Analysis of the Enrollment Rate of Diseases and the Causes of Abnormal Enrollmentin Infection Department Under the Background of DRGs[J].Journal of Medical Information,2026,39(01):75-78.[doi:10.3969/j.issn.1006-1959.2026.01.012]
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DRGs背景下感染科疾病入组率及入组异常原因分析()

医学信息[ISSN:1006-1959/CN:61-1278/R]

卷:
39卷
期数:
2026年01期
页码:
75-78
栏目:
卫生管理信息学
出版日期:
2026-01-01

文章信息/Info

Title:
Analysis of the Enrollment Rate of Diseases and the Causes of Abnormal Enrollmentin Infection Department Under the Background of DRGs
文章编号:
1006-1959（2026）01-0075-04
作者:
蔡金花; 郭 洁; 李政稷
天津市第二人民医院病案科，天津 300192
Author(s):
CAI Jinhua;  GUO Jie;  LI Zhengji
Department of Medical Record, Tianjin Second People′s Hospital, Tianjin 300192, China
关键词:
疾病诊断相关分组; 感染科; 入组率; 歧义病案; 主要诊断; 诊断编码
Keywords:
Diagnosis Related Groups;  Infection department;  Enrollment rate;  Ambiguous medical records;  Main diagnosis;  Diagnostic code
分类号:
R197.323
DOI:
10.3969/j.issn.1006-1959.2026.01.012
文献标志码:
A
摘要:
目的 分析感染科疾病诊断相关分组（DRGs）的主要影响因素。方法 通过病案检索系统调取2022年1月-2024年12月天津市第二人民医院感染科住院病案1326份，统计其DRGs入组情况，从医师与编码员两方面入手，统计感染科DRGs入组异常病案的问题类型，随后结合异常病案数据，分析感染科DRGs入组异常与医师、编码员行为的相关性。结果 本次1326份病案中，DRGs入组率为96.53%，DRGs入组异常病案共46例（歧义病案35例、费用异常病案11例），占比3.47%。感染科DRGs入组异常病案中，医师诊断填写不规范问题最为常见，共18例，占比39.13%，其次为编码员诊断编码错误问题，共12例，占比26.09%。经Spearman相关性分析，感染科DRGs入组异常（歧义病案、费用异常病案）发生率与医师诊断填写不规范、编码员诊断编码错误呈强相关（P＜0.05）。结论 医师诊断填写不规范、编码员诊断编码错误是影响感染科DRGs入组的主要因素。
Abstract:
Objective To analyze the main influencing factors of diagnosis related groups (DRGs) in infection department. Methods From January 2022 to December 2024, 1326 inpatient medical records in infection department of Tianjin Second People′s Hospital were retrieved through the medical record retrieval system, and the DRGs enrollment was counted. Starting from the two parties of doctors and coders, the types of problems in the abnormal medical records of DRGs enrollment in infection department were counted. Then, combined with the abnormal medical record data, the correlation between the abnormal DRGs enrollment in infection department and the behavior of doctors and coders was analyzed. Results Among the 1326 medical records, the DRGs enrollment rate was 96.53%, and there were 46 cases of abnormal DRGs enrollment (35 cases of ambiguous medical records and 11 cases of abnormal medical records), accounting for 3.47%. Among the abnormal medical records of DRGs in infection department, the most common problem was the non-standard filling of doctors′ diagnosis, a total of 18 cases, accounting for 39.13%, followed by the problem of coding errors diagnosed by coders, a total of 12 cases, accounting for 26.09%. Spearman correlation analysis showed that the incidence of abnormal DRGs (ambiguous medical records, abnormal cost medical records) in infection department was strongly correlated with the non-standard filling of doctors′ diagnosis and the coding errors of coders′ diagnosis (P<0.05). Conclusion The main factors affecting the inclusion of DRGs in infection department are the non-standard filling of doctors′ diagnosis and the coding error of coders′ diagnosis.

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更新日期/Last Update: 1900-01-01