Open AccessUse of Expert Relevancy Ratings to Validate Task-Specific Search Strategies for Electronic Medical Records
Author(s) -
H. Benjamin Harvey,
Arun Krishnaraj,
Tarik K. Alkasab
Publication year - 2014
Publication title -
jmir medical informatics
Language(s) - English
Resource type - Journals
ISSN - 2291-9694
DOI - 10.2196/medinform.3205
Subject(s) - medical record , relevance (law) , task (project management) , electronic medical record , computer science , gold standard (test) , process (computing) , data science , information retrieval , medicine , management , internet privacy , political science , law , economics , radiology , operating system
As electronic medical records (EMRs) grow in size and complexity, there is increasing need for automated EMR tools that highlight the medical record items most germane to a practitioner’s task-specific needs. The development of such tools would be aided by gold standards of information relevance for a series of different clinical scenarios. We have previously proposed a process in which exemplar medical record data are extracted from actual patients’ EMRs, anonymized, and presented to clinical experts, who then score each medical record item for its relevance to a specific clinical scenario. In this paper, we present how that body of expert relevancy data can be used to create a test framework to validate new EMR search strategies.