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Use of Expert Relevancy Ratings to Validate Task-Specific Search Strategies for Electronic Medical Records

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...

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Detalles Bibliográficos
Autores principales: Harvey, Harlan, Krishnaraj, Arun, Alkasab, Tarik K
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Gunther Eysenbach 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4288078/
https://www.ncbi.nlm.nih.gov/pubmed/25601018
http://dx.doi.org/10.2196/medinform.3205
Descripción
Sumario: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.