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Campbell IM, Karavite DJ, Mcmanus ML, Cusick FC, Junod DC, Sheppard SE, Lourie EM, Shelov ED, Hakonarson H, Luberti AA, Muthu N, Grundmeier RW. Clinical decision support with a comprehensive in-EHR patient tracking system improves genetic testing follow up. J Am Med Inform Assoc 2023; 30:1274-1283. [PMID: 37080563 PMCID: PMC10280356 DOI: 10.1093/jamia/ocad070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Revised: 03/10/2023] [Accepted: 04/11/2023] [Indexed: 04/22/2023] Open
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.
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Affiliation(s)
- Ian M Campbell
- Department of Biomedical and Health Informatics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
- Division of Clinical Genetics, Department of Pediatrics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
- Division of General Pediatrics, Department of Pediatrics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
- Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
- Center for Applied Genomics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Dean J Karavite
- Department of Biomedical and Health Informatics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Morgan L Mcmanus
- Division of Clinical Genetics, Department of Pediatrics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Fred C Cusick
- Department of Biomedical and Health Informatics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - David C Junod
- Department of Biomedical and Health Informatics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Sarah E Sheppard
- Division of Clinical Genetics, Department of Pediatrics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Eli M Lourie
- Department of Biomedical and Health Informatics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
- Division of General Pediatrics, Department of Pediatrics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
- Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Eric D Shelov
- Department of Biomedical and Health Informatics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Hakon Hakonarson
- Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
- Center for Applied Genomics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Anthony A Luberti
- Department of Biomedical and Health Informatics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Naveen Muthu
- Department of Biomedical and Health Informatics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Robert W Grundmeier
- Department of Biomedical and Health Informatics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
- Division of General Pediatrics, Department of Pediatrics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
- Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
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Dragojlovic N, Borle K, Kopac N, Ellis U, Birch P, Adam S, Friedman JM, Nisselle A, Elliott AM, Lynd LD. The composition and capacity of the clinical genetics workforce in high-income countries: a scoping review. Genet Med 2020; 22:1437-1449. [PMID: 32576987 DOI: 10.1038/s41436-020-0825-2] [Citation(s) in RCA: 58] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2020] [Revised: 04/24/2020] [Accepted: 04/26/2020] [Indexed: 01/25/2023] Open
Abstract
As genetics becomes increasingly integrated into all areas of health care and the use of complex genetic tests continues to grow, the clinical genetics workforce will likely face greatly increased demand for its services. To inform strategic planning by health-care systems to prepare to meet this future demand, we performed a scoping review of the genetics workforce in high-income countries, summarizing all available evidence on its composition and capacity published between 2010 and 2019. Five databases (MEDLINE, Embase, PAIS, CINAHL, and Web of Science) and gray literature sources were searched, resulting in 162 unique studies being included in the review. The evidence presented includes the composition and size of the workforce, the scope of practice for genetics and nongenetics specialists, the time required to perform genetics-related tasks, case loads of genetics providers, and opportunities to increase efficiency and capacity. Our results indicate that there is currently a shortage of genetics providers and that there is a lack of consensus about the appropriate boundaries between the scopes of practice for genetics and nongenetics providers. Moreover, the results point to strategies that may be used to increase productivity and efficiency, including alternative service delivery models, streamlining processes, and the automation of tasks.
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Affiliation(s)
- Nick Dragojlovic
- Collaboration for Outcomes Research and Evaluation, Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, BC, Canada
| | - Kennedy Borle
- Collaboration for Outcomes Research and Evaluation, Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, BC, Canada
| | - Nicola Kopac
- Collaboration for Outcomes Research and Evaluation, Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, BC, Canada
| | - Ursula Ellis
- Woodward Library, University of British Columbia, Vancouver, BC, Canada
| | - Patricia Birch
- Department of Medical Genetics, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada.,BC Children's Hospital Research Institute, Vancouver, BC, Canada
| | - Shelin Adam
- Department of Medical Genetics, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada.,BC Children's Hospital Research Institute, Vancouver, BC, Canada
| | - Jan M Friedman
- Department of Medical Genetics, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada.,BC Children's Hospital Research Institute, Vancouver, BC, Canada
| | - Amy Nisselle
- Australian Genomics Health Alliance, Melbourne, VIC, Australia.,Murdoch Children's Research Institute, Melbourne, VIC, Australia.,Department of Paediatrics, University of Melbourne, Melbourne, VIC, Australia
| | | | - Alison M Elliott
- Department of Medical Genetics, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada.,BC Children's Hospital Research Institute, Vancouver, BC, Canada.,BC Women's Hospital Research Institute, Vancouver, BC, Canada
| | - Larry D Lynd
- Collaboration for Outcomes Research and Evaluation, Faculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, BC, Canada. .,Centre for Health Evaluation and Outcomes Sciences, Providence Health Research Institute, Vancouver, BC, Canada.
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Rashkin MD, Bowes J, Dunaway K, Dhaliwal J, Loomis E, Riffle S, Washington NL, Ziegler C, Lu J, Levin E. Genetic counseling, 2030: An on-demand service tailored to the needs of a price conscious, genetically literate, and busy world. J Genet Couns 2020; 28:456-465. [PMID: 30964579 DOI: 10.1002/jgc4.1123] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2018] [Revised: 03/06/2019] [Accepted: 03/08/2019] [Indexed: 12/20/2022]
Abstract
The practice of genetic counseling is going to be impacted by the public's expectation that goods, services, information, and experiences happen on demand, wherever and whenever people want them. Building from trends that are currently taking shape, this article looks just over a decade into the future-to 2030-to provide a description of how the field of genetics and genetic counseling will be changed, as well as advice for genetic counselors for how to prepare. We build from the prediction that a large portion of the general public will have access to their digitized whole genome sequence anytime, any place, on any device. We focus on five topics downstream of this prediction: public health, personal autonomy, polygenic scores (PGS), evolving clinical practices, and genetic privacy.
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Affiliation(s)
| | | | | | | | | | | | | | | | - James Lu
- Helix Opco, LLC, San Carlos, California
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