Next generation of electronic medical record search engines to support chart reviews: A systematic user study and future research direction

Objective: Little research has been done on the user-centered document ranking approach, especially in a crowdsourcing chart review environment. As the starting point of designing and implementing the next generation of Electronic Medical Record (EMR) search engines, a systematic user study is neede...

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Main Authors: Cheng Ye, Daniel Fabbri
Format: Article
Language:English
Published: KeAi Communications Co., Ltd. 2024-11-01
Series:Journal of Economy and Technology
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Online Access:http://www.sciencedirect.com/science/article/pii/S2949948824000179
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author Cheng Ye
Daniel Fabbri
author_facet Cheng Ye
Daniel Fabbri
author_sort Cheng Ye
collection DOAJ
description Objective: Little research has been done on the user-centered document ranking approach, especially in a crowdsourcing chart review environment. As the starting point of designing and implementing the next generation of Electronic Medical Record (EMR) search engines, a systematic user study is needed to better understand the users' needs, challenges, and future research directions of EMR search engines. Materials and methods: One primary observation during the user study is the need for a ranking method to better support the so-called ''early stopping'' reviewing strategy (i.e., reviewing only a subset of EMRs of one patient to make the final decision) during the clinical chart reviews. The authors proposed two novel user-centered ranking metrics: ''critical documents'' and ''negative guarantee ratio,'' to better measure the power of a ranking method in supporting the “early stopping” requirements during clinical chart reviews. Results: The evaluation results show that i) traditional information retrieval metrics, such as the precision-at-K, have limitations in guiding the design and development of EMR search engines to better support clinical chart reviews; ii) there is not a global optimal ranking method that fits the needs of different chart reviews and different users; iii) a learning-to-rank approach cannot guarantee a stable and optimal ranking for different chart reviews and different users; and iv) A user-centered ranking metric, such as the negative guarantee ratio (NGR) metric is able to measure the “early-stopping” performance of ranking methods. Conclusions: User-centered ranking metrics can better measure the power of ranking methods in supporting clinical chart reviews. Future research should explore more user-centered ranking metrics and evaluate their impact on real-world EMR search engines.
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institution Kabale University
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spelling doaj-art-4f6fe14151d5410d81b8535ed7da60232024-11-12T05:22:25ZengKeAi Communications Co., Ltd.Journal of Economy and Technology2949-94882024-11-0122230Next generation of electronic medical record search engines to support chart reviews: A systematic user study and future research directionCheng Ye0Daniel Fabbri1Correspondence to: Department of Biomedical Informatics, Vanderbilt University Medical Center, 2525 West End Ave # 1475, Nashville, TN 37203, USA.; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USADepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USAObjective: Little research has been done on the user-centered document ranking approach, especially in a crowdsourcing chart review environment. As the starting point of designing and implementing the next generation of Electronic Medical Record (EMR) search engines, a systematic user study is needed to better understand the users' needs, challenges, and future research directions of EMR search engines. Materials and methods: One primary observation during the user study is the need for a ranking method to better support the so-called ''early stopping'' reviewing strategy (i.e., reviewing only a subset of EMRs of one patient to make the final decision) during the clinical chart reviews. The authors proposed two novel user-centered ranking metrics: ''critical documents'' and ''negative guarantee ratio,'' to better measure the power of a ranking method in supporting the “early stopping” requirements during clinical chart reviews. Results: The evaluation results show that i) traditional information retrieval metrics, such as the precision-at-K, have limitations in guiding the design and development of EMR search engines to better support clinical chart reviews; ii) there is not a global optimal ranking method that fits the needs of different chart reviews and different users; iii) a learning-to-rank approach cannot guarantee a stable and optimal ranking for different chart reviews and different users; and iv) A user-centered ranking metric, such as the negative guarantee ratio (NGR) metric is able to measure the “early-stopping” performance of ranking methods. Conclusions: User-centered ranking metrics can better measure the power of ranking methods in supporting clinical chart reviews. Future research should explore more user-centered ranking metrics and evaluate their impact on real-world EMR search engines.http://www.sciencedirect.com/science/article/pii/S2949948824000179Electronic medical recordsClinical chart reviewsSearch engineRanking metricsUser studySemantic embeddings
spellingShingle Cheng Ye
Daniel Fabbri
Next generation of electronic medical record search engines to support chart reviews: A systematic user study and future research direction
Journal of Economy and Technology
Electronic medical records
Clinical chart reviews
Search engine
Ranking metrics
User study
Semantic embeddings
title Next generation of electronic medical record search engines to support chart reviews: A systematic user study and future research direction
title_full Next generation of electronic medical record search engines to support chart reviews: A systematic user study and future research direction
title_fullStr Next generation of electronic medical record search engines to support chart reviews: A systematic user study and future research direction
title_full_unstemmed Next generation of electronic medical record search engines to support chart reviews: A systematic user study and future research direction
title_short Next generation of electronic medical record search engines to support chart reviews: A systematic user study and future research direction
title_sort next generation of electronic medical record search engines to support chart reviews a systematic user study and future research direction
topic Electronic medical records
Clinical chart reviews
Search engine
Ranking metrics
User study
Semantic embeddings
url http://www.sciencedirect.com/science/article/pii/S2949948824000179
work_keys_str_mv AT chengye nextgenerationofelectronicmedicalrecordsearchenginestosupportchartreviewsasystematicuserstudyandfutureresearchdirection
AT danielfabbri nextgenerationofelectronicmedicalrecordsearchenginestosupportchartreviewsasystematicuserstudyandfutureresearchdirection