Under-specification as the source of ambiguity and vagueness in narrative phenotype algorithm definitions
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...
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| Format: | Article |
| Language: | English |
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BMC
2022-01-01
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| Series: | BMC Medical Informatics and Decision Making |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12911-022-01759-z |
| _version_ | 1828889984835256320 |
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| author | 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 |
| author_facet | 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 |
| author_sort | Jingzhi Yu |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-13T12:50:39Z |
| format | Article |
| id | doaj.art-8ee69ddf0a344c46bc959566a833582c |
| institution | Directory Open Access Journal |
| issn | 1472-6947 |
| language | English |
| last_indexed | 2024-12-13T12:50:39Z |
| publishDate | 2022-01-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Medical Informatics and Decision Making |
| spelling | doaj.art-8ee69ddf0a344c46bc959566a833582c2022-12-21T23:45:20ZengBMCBMC Medical Informatics and Decision Making1472-69472022-01-012211910.1186/s12911-022-01759-zUnder-specification as the source of ambiguity and vagueness in narrative phenotype algorithm definitionsJingzhi Yu0Jennifer A. Pacheco1Anika S. Ghosh2Yuan Luo3Chunhua Weng4Ning Shang5Barbara Benoit6David S. Carrell7Robert J. Carroll8Ozan Dikilitas9Robert R. Freimuth10Vivian S. Gainer11Hakon Hakonarson12George Hripcsak13Iftikhar J. Kullo14Frank Mentch15Shawn N. Murphy16Peggy L. Peissig17Andrea H. Ramirez18Nephi Walton19Wei-Qi Wei20Luke V. Rasmussen21Center for Health Information Partnerships (CHIP), Northwestern University Feinberg School of MedicineNorthwestern University Feinberg School of MedicineNorthwestern University Feinberg School of MedicineNorthwestern University Feinberg School of MedicineDepartment of Biomedical Informatics, Columbia UniversityDepartment of Biomedical Informatics, Columbia UniversityResearch IS and Computing, Massachusetts General Hospital BrighamKaiser Permanente Washington Health Research InstituteDepartment of Biomedical Informatics, Vanderbilt University Medical CenterDepartment of Cardiovascular Medicine, Mayo ClinicDepartment of Health Sciences Research, Mayo ClinicResearch IS and Computing, Massachusetts General Hospital BrighamCenter for Applied Genomics, Children’s Hospital of PhiladelphiaDepartment of Biomedical Informatics, Columbia UniversityDepartment of Cardiovascular Medicine, Mayo ClinicCenter for Applied Genomics, Children’s Hospital of PhiladelphiaResearch IS and Computing, Massachusetts General Hospital BrighamBiomedical Informatics Research Center, Marshfield Clinic Research InstituteDepartment of Biomedical Informatics, Vanderbilt University Medical CenterIntermountain Precision Genomics, Intermountain HealthcareDepartment of Biomedical Informatics, Vanderbilt University Medical CenterDepartment of Preventive Medicine, Northwestern University Feinberg School of MedicineAbstract 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.https://doi.org/10.1186/s12911-022-01759-zElectronic Health Records (EHR)PhenotypingAmbiguityVaguenessUnder-SpecificationAlgorithm: Natural Language |
| spellingShingle | 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 Under-specification as the source of ambiguity and vagueness in narrative phenotype algorithm definitions BMC Medical Informatics and Decision Making Electronic Health Records (EHR) Phenotyping Ambiguity Vagueness Under-Specification Algorithm: Natural Language |
| title | Under-specification as the source of ambiguity and vagueness in narrative phenotype algorithm definitions |
| title_full | Under-specification as the source of ambiguity and vagueness in narrative phenotype algorithm definitions |
| title_fullStr | Under-specification as the source of ambiguity and vagueness in narrative phenotype algorithm definitions |
| title_full_unstemmed | Under-specification as the source of ambiguity and vagueness in narrative phenotype algorithm definitions |
| title_short | Under-specification as the source of ambiguity and vagueness in narrative phenotype algorithm definitions |
| title_sort | under specification as the source of ambiguity and vagueness in narrative phenotype algorithm definitions |
| topic | Electronic Health Records (EHR) Phenotyping Ambiguity Vagueness Under-Specification Algorithm: Natural Language |
| url | https://doi.org/10.1186/s12911-022-01759-z |
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