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

Author:

Campbell Ian M12345ORCID,Karavite Dean J1,Mcmanus Morgan L2,Cusick Fred C1,Junod David C1,Sheppard Sarah E2,Lourie Eli M134ORCID,Shelov Eric D1,Hakonarson Hakon45,Luberti Anthony A1ORCID,Muthu Naveen1,Grundmeier Robert W134

Affiliation:

1. Department of Biomedical and Health Informatics, Children’s Hospital of Philadelphia , Philadelphia, Pennsylvania, USA

2. Division of Clinical Genetics, Department of Pediatrics, Children’s Hospital of Philadelphia , Philadelphia, Pennsylvania, USA

3. Division of General Pediatrics, Department of Pediatrics, Children’s Hospital of Philadelphia , Philadelphia, Pennsylvania, USA

4. Department of Pediatrics, University of Pennsylvania Perelman School of Medicine , Philadelphia, Pennsylvania, USA

5. Center for Applied Genomics, Children’s Hospital of Philadelphia , Philadelphia, Pennsylvania, USA

Abstract

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.

Publisher

Oxford University Press (OUP)

Subject

Health Informatics

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