Clinical decision support with a comprehensive in-EHR patient tracking system improves genetic testing follow up

Abstract Objective We sought to develop and evaluate an electronic health record (EHR) genetic testing tracking system to address the barriers and limitations of existing spreadsheet-based workarounds. Materials and Methods We evaluated the spreadsheet-based system using mixed effects logistic regre...

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Bibliographic Details
Published in:	Journal of the American Medical Informatics Association : JAMIA Vol. 30; no. 7; pp. 1274 - 1283
Main Authors:	Campbell, Ian M, Karavite, Dean J, Mcmanus, Morgan L, Cusick, Fred C, Junod, David C, Sheppard, Sarah E, Lourie, Eli M, Shelov, Eric D, Hakonarson, Hakon, Luberti, Anthony A, Muthu, Naveen, Grundmeier, Robert W
Format:	Journal Article
Language:	English
Published:	England Oxford University Press 20-06-2023
Subjects:	Decision Support Systems, Clinical Electronic Health Records Follow-Up Studies Genetic Testing Humans Software clinical decision support genetic testing transition of care
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Summary:	Abstract Objective We sought to develop and evaluate an electronic health record (EHR) genetic testing tracking system to address the barriers and limitations of existing spreadsheet-based workarounds. Materials and Methods We evaluated the spreadsheet-based system using mixed effects logistic regression to identify factors associated with delayed follow up. These factors informed the design of an EHR-integrated genetic testing tracking system. After deployment, we assessed the system in 2 ways. We analyzed EHR access logs and note data to assess patient outcomes and performed semistructured interviews with users to identify impact of the system on work. Results We found that patient-reported race was a significant predictor of documented genetic testing follow up, indicating a possible inequity in care. We implemented a CDS system including a patient data capture form and management dashboard to facilitate important care tasks. The system significantly sped review of results and significantly increased documentation of follow-up recommendations. Interviews with key system users identified a range of sociotechnical factors (ie, tools, tasks, collaboration) that contribute to safer and more efficient care. Discussion Our new tracking system ended decades of workarounds for identifying and communicating test results and improved clinical workflows. Interview participants related that the system decreased cognitive and time burden which allowed them to focus on direct patient interaction. Conclusion By assembling a multidisciplinary team, we designed a novel patient tracking system that improves genetic testing follow up. Similar approaches may be effective in other clinical settings.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23
ISSN:	1067-5027 1527-974X
DOI:	10.1093/jamia/ocad070