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Under-specification as the source of ambiguity and vagueness in narrative phenotype algorithm definitions

Authors :
Jingzhi Yu
Jennifer A. Pacheco
Anika S. Ghosh
Yuan Luo
Chunhua Weng
Ning Shang
Barbara Benoit
David S. Carrell
Robert J. Carroll
Ozan Dikilitas
Robert R. Freimuth
Vivian S. Gainer
Hakon Hakonarson
George Hripcsak
Iftikhar J. Kullo
Frank Mentch
Shawn N. Murphy
Peggy L. Peissig
Andrea H. Ramirez
Nephi Walton
Wei-Qi Wei
Luke V. Rasmussen
Source :
BMC Medical Informatics and Decision Making, Vol 22, Iss 1, Pp 1-9 (2022)
Publication Year :
2022
Publisher :
BMC, 2022.

Abstract

Abstract Introduction Currently, one of the commonly used methods for disseminating electronic health record (EHR)-based phenotype algorithms is providing a narrative description of the algorithm logic, often accompanied by flowcharts. A challenge with this mode of dissemination is the potential for under-specification in the algorithm definition, which leads to ambiguity and vagueness. Methods This study examines incidents of under-specification that occurred during the implementation of 34 narrative phenotyping algorithms in the electronic Medical Record and Genomics (eMERGE) network. We reviewed the online communication history between algorithm developers and implementers within the Phenotype Knowledge Base (PheKB) platform, where questions could be raised and answered regarding the intended implementation of a phenotype algorithm. Results We developed a taxonomy of under-specification categories via an iterative review process between two groups of annotators. Under-specifications that lead to ambiguity and vagueness were consistently found across narrative phenotype algorithms developed by all involved eMERGE sites. Discussion and conclusion Our findings highlight that under-specification is an impediment to the accuracy and efficiency of the implementation of current narrative phenotyping algorithms, and we propose approaches for mitigating these issues and improved methods for disseminating EHR phenotyping algorithms.

Details

Language :
English
ISSN :
14726947
Volume :
22
Issue :
1
Database :
Directory of Open Access Journals
Journal :
BMC Medical Informatics and Decision Making
Publication Type :
Academic Journal
Accession number :
edsdoj.8ee69ddf0a344c46bc959566a833582c
Document Type :
article
Full Text :
https://doi.org/10.1186/s12911-022-01759-z