734
Views
12
CrossRef citations to date
0
Altmetric
Research Article

Automatic scoring of medical students’ clinical notes to monitor learning in the workplace

, , , , , , & show all
Pages 68-72 | Published online: 07 Nov 2013
 

Abstract

Background: Educators need efficient and effective means to track students’ clinical experiences to monitor their progress toward competency goals.

Aim: To validate an electronic scoring system that rates medical students’ clinical notes for relevance to priority topics of the medical school curriculum.

Method: The Vanderbilt School of Medicine Core Clinical Curriculum enumerates 25 core clinical problems (CCP) that graduating medical students must understand. Medical students upload clinical notes pertinent to each CCP to a web-based dashboard, but criteria for determining relevance of a note and consistent uploading practices by students are lacking. The Vanderbilt Learning Portfolio (VLP) system automates both tasks by rating relevance for each CCP and uploading the note to the student's electronic dashboard. We validated this electronic scoring system by comparing the relevance of 265 clinical notes written by third year medical students to each of the 25 core patient problems as scored by VLP verses an expert panel of raters.

Results: We established the threshold score which yielded 75% positive prediction of relevance for 16 of the 25 clinical problems to expert opinion.

Discussion: Automated scoring of student's clinical notes provides a novel, efficient and standardized means of tracking student's progress toward institutional competency goals.

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

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 771.00 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.