1
Views
0
CrossRef citations to date
0
Altmetric
Research Article

Defect Analysis and Strategy Discussion of Admission Notes Written by Interns of Cardiology Department

, , , &
Pages 131-134 | Published online: 23 Apr 2014
 

Abstract

Objective. To analyze the defects of admission notes written by interns of the cardiology department and to discuss strategies of improving their quality. Sixty-nine admission notes of our department from May 2013 to December 2013 were retrospectively analyzed according to the requirements of the Basic Criterion of Documentation of the Medical Record, which was issued by the Ministry of Health in 2010. Results. The defective medical records accounted for 82.6% (57/69), of which those having inaccurate general item filling accounted for 21.7% (15/69), those having problems in the filling of chief complaint accounted for 26.1% (18/69), those having problems in the filling of the history of present illness accounted for 62.3% (43/69), those having omission or inaccurate description in the fields of past history, personal history, menstrual obstetrical history and family history accounted for 20.3% (14/69), those having problems in the physical examination accounted for 46.4% (32/69), and those having problems in primary diagnosis accounted for 56.5% (39/69). Conclusions. Most of the interns commit multiple mistakes in writing the admission notes. We should improve the interns’ legal awareness, strengthen three-base training and pre-service training, and give full play to the “teaching, helping and guiding” role of clinical teachers, so as to improve the level of interns of the cardiology department in writing the admission notes.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access
  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 65.00 Add to cart
* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.