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Review
Patient-facing digital tools for delivering genetic services: a systematic review
  1. Whiwon Lee1,2,
  2. Salma Shickh2,3,
  3. Daniel Assamad1,
  4. Stephanie Luca1,
  5. Marc Clausen3,
  6. Cherith Somerville1,
  7. Abby Tafler1,
  8. Angela Shaw3,4,
  9. Robin Hayeems1,2,
  10. Yvonne Bombard2,3
  11. Genetics Navigator Study Team
    1. 1 Child Health Evaluative Sciences, The Hospital for Sick Children, Toronto, Ontario, Canada
    2. 2 Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
    3. 3 Genomics Health Services Research Program, Li Ka Shing Knowledge Institute, St Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada
    4. 4 Illumina, San Diego, California, USA
    5. 1 Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
    6. 2 Genomics Health Services Research Program, Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Unity Health Toronto, Toronto, ON, Canada
    7. 3 Child Health Evaluative Sciences, The Hospital for Sick Children, Toronto, ON, Canada
    8. 4 Fred A. Litwin Family Centre in Genetic Medicine, University Health Network and Sinai Health, Toronto, ON, Canada
    9. 5 Zane Cohen Centre for Digestive Diseases, Sinai Health, Toronto, Toronto, ON, Canada
    10. 6 Department of Medical Genetics, Alberta Children’s Hospital, Calgary, AB, Canada
    11. 7 HPC4Health Consortium, Toronto, ON, Canada
    12. 8 Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, ON, Canada
    13. 9 Division of Clinical and Metabolic Genetics, The Hospital for Sick Children, Toronto, ON, Canada
    14. 10 Department of Pediatrics, University of Toronto, Toronto, ON, Canada
    15. 11 Department of Bioethics, The Hospital for Sick Children, Toronto, ON, Canada
    16. 12 Care Experience Institute, Unity Health Toronto, Toronto, ON, Canada
    17. 13 Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
    18. 14 Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
    19. 15 Department of Medical Genetics, Le Centre hospitalier universitaire Sainte-Justine, Montreal, QC, Canada
    20. 16 Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
    21. 17 Department of Data Science and Advanced Analytics, Li Ka Shing Knowledge Institute, St. Michael’s Hospital, Unity Health Toronto, Toronto, ON, Canada
    22. 18 Division of Genome Diagnostics, Department of Pediatric Laboratory Medicine, The Hospital for Sick Children, Toronto, ON, Canada
    23. 19 Children’s Hospital of Eastern Ontario Research Institute, University of Ottawa, Ottawa, ON, Canada
    24. 20 Centre for Global eHealth Innovation University Health Network, Toronto, ON, Canada
    25. 21 Vector Institute for Artificial Intelligence, Toronto, ON, Canada
    26. 22 Workplace Safety and Insurance Board, Toronto, ON, Canada
    27. 23 Department of Occupational Science and Occupational Therapy, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
    28. 24 Patient Partner, Canadian Organization for Rare Disorders, Toronto, ON, Canada
    29. 25 Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
    30. 26 Department of Medicine, University of Toronto, Toronto, ON, Canada
    31. 27 Division of General Internal Medicine, St Michael's Hospital/Unity Health Toronto, Toronto, ON, Canada
    1. Correspondence to Dr Yvonne Bombard, University of Toronto, Toronto, ON M5B 1T8, Canada; yvonne.bombard{at}utoronto.ca

    Abstract

    This study systematically reviewed the literature on the impact of digital genetics tools on patient care and system efficiencies. MEDLINE and Embase were searched for articles published between January 2010 and March 2021. Studies evaluating the use of patient-facing digital tools in the context of genetic service delivery were included. Two reviewers screened and extracted patient-reported and system-focused outcomes from each study. Data were synthesised using a descriptive approach. Of 3226 unique studies identified, 87 were included. A total of 70 unique digital tools were identified. As a result of using digital tools, 84% of studies reported a positive outcome in at least one of the following patient outcomes: knowledge, psychosocial well-being, behavioural/management changes, family communication, decision-making or level of engagement. Digital tools improved workflow and efficiency for providers and reduced the amount of time they needed to spend with patients. However, we identified a misalignment between study purpose and patient-reported outcomes measured and a lack of tools that encompass the entire genetic counselling and testing trajectory. Given increased demand for genetic services and the shift towards virtual care, this review provides evidence that digital tools can be used to efficiently deliver patient-centred care. Future research should prioritise development, evaluation and implementation of digital tools that can support the entire patient trajectory across a range of clinical settings. PROSPERO registration numberCRD42020202862.

    • Genetics
    • Patient Care
    • Genetic Testing
    • Genetic Counseling

    https://doi.org/10.1136/jmg-2022-108653

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      Footnotes

      • WL and SS contributed equally.

      • Collaborators Genetics Navigator Study Team: Yvonne Bombard (co-PI), Robin Hayeems (co-PI), Melyssa Aronson, Francois Bernier, Michael Brudno, June Carroll, Lauren Chad, Marc Clausen, Ronald Cohn, Gregory Costain, Irfan Dhalla, Hanna Faghfoury, Jan Friedman, Stacy Hewson, Rebekah Jobling, Rita Kodida, Anne-Marie Laberge, Jordan Lerner-Ellis, Eriskay Liston, Stephanie Luca, Muhammad Mamdani, Christian Marshall, Matthew Osmond, Quynh Pham, Emma Reble, Frank Rudzicz, Emily Seto, Serena Shastri-Estrada, Cheryl Shuman, Josh Silver, Maureen Smith, Kevin Thorpe, Wendy Ungar, Trevor Jamieson.

      • Contributors Conceptualisation: WL, SS, RH, YB, DA, SL, MC. Data collection: WL, SS, DA, SL, CS, AT, AS. Formal analysis: WL, SS, DA. Funding acquisition: RH, YB. Writing - original draft: WL, SS. Writing - review and editing: DA, SL, MC, CS, AT, AS, RH, YB, WL, SS. Supervision: RH, YB.

      • Funding This work was supported by the McLaughlin Catalyst Grant through the University of Toronto and a bridge grant from the Canadian Institutes of Health Research (CIHR; 175409).

      • Competing interests None declared.

      • Provenance and peer review Not commissioned; externally peer reviewed.

      • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.