Study on the Connotation Quality Prediction Model of Inpatient Medical Record Based on Multi-layer Perceptron Neural Network
10.3969/j.issn.1673-6036.2023.11.007
- VernacularTitle:基于多层感知器神经网络的住院病案内涵质量预测模型研究
- Author:
Xiaoqi YUAN
1
;
Yingying ZHAO
Author Information
1. 上海市第一人民医院医务处 上海 200080
- Keywords:
neural network;
inpatient medical record;
connotation quality;
prediction model;
artificial intelligence
- From:
Journal of Medical Informatics
2023;44(11):35-40
- CountryChina
- Language:Chinese
-
Abstract:
Purpose/Significance To explore the important factors affecting the connotation quality of inpatient medical records,and to provide model prediction and improve the connotation quality of inpatient medical records.Method/Process A total of 590 inpatient medical records monitored by quality control in Shanghai First People's Hospital from June to November 2022 are collected.The influen-cing factors are initially screened by single factor analysis,and a multi-layer perceptron neural network prediction model for the connota-tion quality of inpatient medical records is constructed.Result/Conclusion The area under the curve(AUC)of the prediction model is 0.940,95％CI is 0.928～0.951,the sensitivity is 93.73％,and the specificity is 78.22％.The top three independent factors affecting the rating of a case as grade A are concentrated in the surgical safety checklist,the analysis of the first director's ward round,and the surgical nursing record.The multi-layer perceptron neural network connotation quality prediction model has good prediction efficiency,which provides theoretical references for the connotation quality management of inpatient medical records.
