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Lunke S, Bouffler SE, Downie L, Caruana J, Amor DJ, Archibald A, Bombard Y, Christodoulou J, Clausen M, De Fazio P, Greaves RF, Hollizeck S, Kanga-Parabia A, Lang N, Lynch F, Peters R, Sadedin S, Tutty E, Eggers S, Lee C, Wall M, Yeung A, Gaff C, Gyngell C, Vears DF, Best S, Goranitis I, Stark Z. Prospective cohort study of genomic newborn screening: BabyScreen+ pilot study protocol. BMJ Open 2024; 14:e081426. [PMID: 38569677 PMCID: PMC11146401 DOI: 10.1136/bmjopen-2023-081426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Accepted: 03/26/2024] [Indexed: 04/05/2024] Open
Abstract
INTRODUCTION Newborn bloodspot screening (NBS) is a highly successful public health programme that uses biochemical and other assays to screen for severe but treatable childhood-onset conditions. Introducing genomic sequencing into NBS programmes increases the range of detectable conditions but raises practical and ethical issues. Evidence from prospectively ascertained cohorts is required to guide policy and future implementation. This study aims to develop, implement and evaluate a genomic NBS (gNBS) pilot programme. METHODS AND ANALYSIS The BabyScreen+ study will pilot gNBS in three phases. In the preimplementation phase, study materials, including education resources, decision support and data collection tools, will be designed. Focus groups and key informant interviews will also be undertaken to inform delivery of the study and future gNBS programmes. During the implementation phase, we will prospectively recruit birth parents in Victoria, Australia, to screen 1000 newborns for over 600 severe, treatable, childhood-onset conditions. Clinically accredited whole genome sequencing will be performed following standard NBS using the same sample. High chance results will be returned by genetic healthcare professionals, with follow-on genetic and other confirmatory testing and referral to specialist services as required. The postimplementation phase will evaluate the feasibility of gNBS as the primary aim, and assess ethical, implementation, psychosocial and health economic factors to inform future service delivery. ETHICS AND DISSEMINATION This project received ethics approval from the Royal Children's Hospital Melbourne Research Ethics Committee: HREC/91500/RCHM-2023, HREC/90929/RCHM-2022 and HREC/91392/RCHM-2022. Findings will be disseminated to policy-makers, and through peer-reviewed journals and conferences.
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Affiliation(s)
- Sebastian Lunke
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Parkville, Victoria, Australia
- University of Melbourne, Melbourne, Victoria, Australia
| | - Sophie E Bouffler
- Australian Genomics Health Alliance, Parkville, Victoria, Australia
- Murdoch Children's Research Institute, Parkville, Victoria, Australia
| | - Lilian Downie
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Parkville, Victoria, Australia
- University of Melbourne, Melbourne, Victoria, Australia
| | - Jade Caruana
- Murdoch Children's Research Institute, Parkville, Victoria, Australia
| | - David J Amor
- University of Melbourne, Melbourne, Victoria, Australia
- Murdoch Children's Research Institute, Parkville, Victoria, Australia
| | - Alison Archibald
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Parkville, Victoria, Australia
- University of Melbourne, Melbourne, Victoria, Australia
| | - Yvonne Bombard
- Genomics Health Services Research Program, St Michael's Hospital, Toronto, Ontario, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
| | - John Christodoulou
- University of Melbourne, Melbourne, Victoria, Australia
- Murdoch Children's Research Institute, Parkville, Victoria, Australia
| | - Marc Clausen
- Genomics Health Services Research Program, St Michael's Hospital, Toronto, Ontario, Canada
| | - Paul De Fazio
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Parkville, Victoria, Australia
| | - Ronda F Greaves
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Parkville, Victoria, Australia
- University of Melbourne, Melbourne, Victoria, Australia
| | - Sebastian Hollizeck
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Parkville, Victoria, Australia
| | - Anaita Kanga-Parabia
- University of Melbourne, Melbourne, Victoria, Australia
- Murdoch Children's Research Institute, Parkville, Victoria, Australia
| | - Nitzan Lang
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Parkville, Victoria, Australia
| | - Fiona Lynch
- University of Melbourne, Melbourne, Victoria, Australia
| | | | - Simon Sadedin
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Parkville, Victoria, Australia
| | - Erin Tutty
- University of Melbourne, Melbourne, Victoria, Australia
- Murdoch Children's Research Institute, Parkville, Victoria, Australia
| | - Stefanie Eggers
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Parkville, Victoria, Australia
| | - Crystle Lee
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Parkville, Victoria, Australia
| | - Meaghan Wall
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Parkville, Victoria, Australia
- University of Melbourne, Melbourne, Victoria, Australia
| | - Alison Yeung
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Parkville, Victoria, Australia
- University of Melbourne, Melbourne, Victoria, Australia
| | - Clara Gaff
- University of Melbourne, Melbourne, Victoria, Australia
- Melbourne Genomics Health Alliance, Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia
| | - Christopher Gyngell
- University of Melbourne, Melbourne, Victoria, Australia
- Murdoch Children's Research Institute, Parkville, Victoria, Australia
| | - Danya F Vears
- University of Melbourne, Melbourne, Victoria, Australia
- Murdoch Children's Research Institute, Parkville, Victoria, Australia
| | - Stephanie Best
- Australian Genomics Health Alliance, Parkville, Victoria, Australia
- Department of Health Services Research, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
| | - Ilias Goranitis
- University of Melbourne, Melbourne, Victoria, Australia
- Australian Genomics Health Alliance, Parkville, Victoria, Australia
| | - Zornitza Stark
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Parkville, Victoria, Australia
- University of Melbourne, Melbourne, Victoria, Australia
- Australian Genomics Health Alliance, Parkville, Victoria, Australia
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Siglen E, Vetti HH, Augestad M, Steen VM, Lunde Å, Bjorvatn C. Evaluation of the Rosa Chatbot Providing Genetic Information to Patients at Risk of Hereditary Breast and Ovarian Cancer: Qualitative Interview Study. J Med Internet Res 2023; 25:e46571. [PMID: 37656502 PMCID: PMC10504626 DOI: 10.2196/46571] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Revised: 06/27/2023] [Accepted: 07/20/2023] [Indexed: 09/02/2023] Open
Abstract
BACKGROUND Genetic testing has become an integrated part of health care for patients with breast or ovarian cancer, and the increasing demand for genetic testing is accompanied by an increasing need for easy access to reliable genetic information for patients. Therefore, we developed a chatbot app (Rosa) that is able to perform humanlike digital conversations about genetic BRCA testing. OBJECTIVE Before implementing this new information service in daily clinical practice, we wanted to explore 2 aspects of chatbot use: the perceived utility and trust in chatbot technology among healthy patients at risk of hereditary cancer and how interaction with a chatbot regarding sensitive information about hereditary cancer influences patients. METHODS Overall, 175 healthy individuals at risk of hereditary breast and ovarian cancer were invited to test the chatbot, Rosa, before and after genetic counseling. To secure a varied sample, participants were recruited from all cancer genetic clinics in Norway, and the selection was based on age, gender, and risk of having a BRCA pathogenic variant. Among the 34.9% (61/175) of participants who consented for individual interview, a selected subgroup (16/61, 26%) shared their experience through in-depth interviews via video. The semistructured interviews covered the following topics: usability, perceived usefulness, trust in the information received via the chatbot, how Rosa influenced the user, and thoughts about future use of digital tools in health care. The transcripts were analyzed using the stepwise-deductive inductive approach. RESULTS The overall finding was that the chatbot was very welcomed by the participants. They appreciated the 24/7 availability wherever they were and the possibility to use it to prepare for genetic counseling and to repeat and ask questions about what had been said afterward. As Rosa was created by health care professionals, they also valued the information they received as being medically correct. Rosa was referred to as being better than Google because it provided specific and reliable answers to their questions. The findings were summed up in 3 concepts: "Anytime, anywhere"; "In addition, not instead"; and "Trustworthy and true." All participants (16/16) denied increased worry after reading about genetic testing and hereditary breast and ovarian cancer in Rosa. CONCLUSIONS Our results indicate that a genetic information chatbot has the potential to contribute to easy access to uniform information for patients at risk of hereditary breast and ovarian cancer, regardless of geographical location. The 24/7 availability of quality-assured information, tailored to the specific situation, had a reassuring effect on our participants. It was consistent across concepts that Rosa was a tool for preparation and repetition; however, none of the participants (0/16) supported that Rosa could replace genetic counseling if hereditary cancer was confirmed. This indicates that a chatbot can be a well-suited digital companion to genetic counseling.
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Affiliation(s)
- Elen Siglen
- Western Norway Familial Cancer Center, Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway
- Faculty of Health Studies, VID Specialized University, Bergen, Norway
| | - Hildegunn Høberg Vetti
- Western Norway Familial Cancer Center, Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway
- Faculty of Health Studies, VID Specialized University, Bergen, Norway
| | - Mirjam Augestad
- Faculty of Health Studies, VID Specialized University, Bergen, Norway
| | - Vidar M Steen
- Western Norway Familial Cancer Center, Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway
- Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Åshild Lunde
- Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway
| | - Cathrine Bjorvatn
- Western Norway Familial Cancer Center, Department of Medical Genetics, Haukeland University Hospital, Bergen, Norway
- Faculty of Health Studies, VID Specialized University, Bergen, Norway
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Kodida R, Reble E, Clausen M, Shickh S, Mighton C, Sam J, Forster N, Panchal S, Aronson M, Semotiuk K, Graham T, Silberman Y, Randall Armel S, McCuaig JM, Cohn I, Morel CF, Elser C, Eisen A, Carroll JC, Glogowski E, Schrader KA, Di Gioacchino V, Lerner-Ellis J, Kim RH, Bombard Y. A model for the return and referral of all clinically significant secondary findings of genomic sequencing. J Med Genet 2023; 60:733-739. [PMID: 37217257 DOI: 10.1136/jmg-2022-109091] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Accepted: 04/19/2023] [Indexed: 05/24/2023]
Abstract
Secondary findings (SFs) identified through genomic sequencing (GS) can offer a wide range of health benefits to patients. Resource and capacity constraints pose a challenge to their clinical management; therefore, clinical workflows are needed to optimise the health benefits of SFs. In this paper, we describe a model we created for the return and referral of all clinically significant SFs, beyond medically actionable results, from GS. As part of a randomised controlled trial evaluating the outcomes and costs of disclosing all clinically significant SFs from GS, we consulted genetics and primary care experts to determine a feasible workflow to manage SFs. Consensus was sought to determine appropriate clinical recommendations for each category of SF and which clinician specialist would provide follow-up care. We developed a communication and referral plan for each category of SFs. This involved referrals to specialised clinics, such as an Adult Genetics clinic, for highly penetrant medically actionable findings. Common and non-urgent SFs, such as pharmacogenomics and carrier status results for non-family planning participants, were directed back to the family physician (FP). SF results and recommendations were communicated directly to participants to respect autonomy and to their FPs to support follow-up of SFs. We describe a model for the return and referral of all clinically significant SFs to facilitate the utility of GS and promote the health benefits of SFs. This may serve as a model for others returning GS results transitioning participants from research to clinical settings.
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Affiliation(s)
- Rita Kodida
- Genomics Health Services & Policy Research Program, Li Ka Shing Knowledge Institute, St Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada
| | - Emma Reble
- Genomics Health Services & Policy Research Program, Li Ka Shing Knowledge Institute, St Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada
| | - Marc Clausen
- Genomics Health Services & Policy Research Program, Li Ka Shing Knowledge Institute, St Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada
| | - Salma Shickh
- Genomics Health Services & Policy Research Program, Li Ka Shing Knowledge Institute, St Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada
- Institute of Health Policy, Management & Evaluation, University of Toronto, Toronto, Ontario, Canada
| | - Chloe Mighton
- Genomics Health Services & Policy Research Program, Li Ka Shing Knowledge Institute, St Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada
- Institute of Health Policy, Management & Evaluation, University of Toronto, Toronto, Ontario, Canada
| | - Jordan Sam
- Genomics Health Services & Policy Research Program, Li Ka Shing Knowledge Institute, St Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada
| | - Nicole Forster
- Fred A. Litwin Family Centre in Genetic Medicine, University Health Network, Toronto, Ontario, Canada
| | - Seema Panchal
- The Marvelle Koffler Breast Centre, Mount Sinai Hospital, Sinai Health, Toronto, Ontario, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
| | - Melyssa Aronson
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
- Zane Cohen Centre for Digestive Diseases, Mount Sinai Hospital, Sinai Health, Toronto, Ontario, Canada
| | - Kara Semotiuk
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
- Zane Cohen Centre for Digestive Diseases, Mount Sinai Hospital, Sinai Health, Toronto, Ontario, Canada
| | - Tracy Graham
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
- Odette Cancer Centre, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Yael Silberman
- Odette Cancer Centre, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Susan Randall Armel
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
- Division of Medical Oncology & Hematology, Princess Margaret Hospital Cancer Centre, Toronto, Ontario, Canada
| | - Jeanna M McCuaig
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
- Division of Medical Oncology & Hematology, Princess Margaret Hospital Cancer Centre, Toronto, Ontario, Canada
| | - Iris Cohn
- Division of Clinical Pharmacology & Toxicology, Hospital for Sick Children, Toronto, Ontario, Canada
| | - Chantal F Morel
- Fred A. Litwin Family Centre in Genetic Medicine, University Health Network, Toronto, Ontario, Canada
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Christine Elser
- The Marvelle Koffler Breast Centre, Mount Sinai Hospital, Sinai Health, Toronto, Ontario, Canada
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Andrea Eisen
- Odette Cancer Centre, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - June C Carroll
- Department of Family & Community Medicine, University of Toronto, Toronto, Ontario, Canada
- Granovsky Gluskin Family Medicine Centre, Mount Sinai Hospital, Sinai Health, Toronto, Ontario, Canada
| | | | - Kasmintan A Schrader
- British Columbia Cancer Agency, Vancouver, British Columbia, Canada
- Department of Medical Genetics, The University of British Columbia, Vancouver, British Columbia, Canada
| | - Vanessa Di Gioacchino
- The Marvelle Koffler Breast Centre, Mount Sinai Hospital, Sinai Health, Toronto, Ontario, Canada
- Pathology & Laboratory Medicine, Mount Sinai Hospital, Sinai Health, Toronto, Ontario, Canada
| | - Jordan Lerner-Ellis
- Pathology & Laboratory Medicine, Mount Sinai Hospital, Sinai Health, Toronto, Ontario, Canada
- Lunenfeld Tanenbaum Research Institute, Mount Sinai Hospital, Sinai Health, Toronto, Ontario, Canada
| | - Raymond H Kim
- Division of Medical Oncology & Hematology, Princess Margaret Hospital Cancer Centre, Toronto, Ontario, Canada
- Department of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Yvonne Bombard
- Genomics Health Services & Policy Research Program, Li Ka Shing Knowledge Institute, St Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada
- Institute of Health Policy, Management & Evaluation, University of Toronto, Toronto, Ontario, Canada
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4
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Bouffler SE, Lee L, Lynch F, Martyn M, Lynch E, Macciocca I, Curnow L, McCorkell G, Lunke S, Chong B, Marum JE, Delatycki M, Downie L, Goranitis I, Vears DF, Best S, Clausen M, Bombard Y, Stark Z, Gaff CL. Two-step offer and return of multiple types of additional genomic findings to families after ultrarapid trio genomic testing in the acute care setting: a study protocol. BMJ Open 2023; 13:e072999. [PMID: 37270192 DOI: 10.1136/bmjopen-2023-072999] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/05/2023] Open
Abstract
INTRODUCTION As routine genomic testing expands, so too does the opportunity to look for additional health information unrelated to the original reason for testing, termed additional findings (AF). Analysis for many different types of AF may be available, particularly to families undergoing trio genomic testing. The optimal model for service delivery remains to be determined, especially when the original test occurs in the acute care setting. METHODS AND ANALYSIS Families enrolled in a national study providing ultrarapid genomic testing to critically ill children will be offered analysis for three types of AF on their stored genomic data: paediatric-onset conditions in the child, adult-onset conditions in each parent and reproductive carrier screening for the parents as a couple. The offer will be made 3-6 months after diagnostic testing. Parents will have access to a modified version of the Genetics Adviser web-based decision support tool before attending a genetic counselling appointment to discuss consent for AF. Parental experiences will be evaluated using qualitative and quantitative methods on data collected through surveys, appointment recordings and interviews at multiple time points. Evaluation will focus on parental preferences, uptake, decision support use and understanding of AF. Genetic health professionals' perspectives on acceptability and feasibility of AF will also be captured through surveys and interviews. ETHICS AND DISSEMINATION This project received ethics approval from the Melbourne Health Human Research Ethics Committee as part of the Australian Genomics Health Alliance protocol: HREC/16/MH/251. Findings will be disseminated through peer-review journal articles and at conferences nationally and internationally.
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Affiliation(s)
| | - Ling Lee
- Melbourne Genomics Health Alliance, Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia
- Murdoch Children's Research Institute, Parkville, Victoria, Australia
| | - Fiona Lynch
- Murdoch Children's Research Institute, Parkville, Victoria, Australia
- Department of Paediatrics, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, Victoria, Australia
| | - Melissa Martyn
- Melbourne Genomics Health Alliance, Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia
- Murdoch Children's Research Institute, Parkville, Victoria, Australia
| | - Elly Lynch
- Melbourne Genomics Health Alliance, Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Parkville, Victoria, Australia
| | - Ivan Macciocca
- Department of Paediatrics, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, Victoria, Australia
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Parkville, Victoria, Australia
| | - Lisette Curnow
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Parkville, Victoria, Australia
| | - Giulia McCorkell
- Australian Genomics Health Alliance, Parkville, Victoria, Australia
- Department of Paediatrics, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, Victoria, Australia
| | - Sebastian Lunke
- Department of Paediatrics, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, Victoria, Australia
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Parkville, Victoria, Australia
| | - Belinda Chong
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Parkville, Victoria, Australia
| | - Justine E Marum
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Parkville, Victoria, Australia
| | - Martin Delatycki
- Department of Paediatrics, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, Victoria, Australia
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Parkville, Victoria, Australia
| | - Lilian Downie
- Murdoch Children's Research Institute, Parkville, Victoria, Australia
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Parkville, Victoria, Australia
| | - Ilias Goranitis
- Australian Genomics Health Alliance, Parkville, Victoria, Australia
- Health Economics Unit, Centre for Health Policy, Melbourne Schoold of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Danya F Vears
- Murdoch Children's Research Institute, Parkville, Victoria, Australia
- Department of Paediatrics, Faculty of Medicine, Dentistry and Health Sciences, The University of Melbourne, Melbourne, Victoria, Australia
| | - Stephanie Best
- Australian Genomics Health Alliance, Parkville, Victoria, Australia
- Department of Health Services Research, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
| | - Marc Clausen
- Genomics Health Services Research Program, St. Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada
| | - Yvonne Bombard
- Genomics Health Services Research Program, St. Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
| | - Zornitza Stark
- Australian Genomics Health Alliance, Parkville, Victoria, Australia
- Victorian Clinical Genetics Services, Murdoch Children's Research Institute, Parkville, Victoria, Australia
| | - Clara L Gaff
- Melbourne Genomics Health Alliance, Walter and Eliza Hall Institute of Medical Research, Melbourne, Victoria, Australia
- Murdoch Children's Research Institute, Parkville, Victoria, Australia
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Shickh S, Leventakos K, Lewis MA, Bombard Y, Montori VM. Shared Decision Making in the Care of Patients With Cancer. Am Soc Clin Oncol Educ Book 2023; 43:e389516. [PMID: 37339391 DOI: 10.1200/edbk_389516] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/22/2023]
Abstract
Shared decision making (SDM) is a method of care that is suitable for the care of patients with cancer. It involves a collaborative conversation seeking to respond sensibly to the problematic situation of the patient, cocreating a plan of care that makes sense intellectually, practically, and emotionally. Genetic testing to identify whether a patient has a hereditary cancer syndrome represents a prime example of the importance for SDM in oncology. SDM is important for genetic testing because not only results affect current cancer treatment, cancer surveillance, and care of relatives but also these tests generate both complex results and psychological concerns. SDM conversations should take place without interruptions, disruptions, or hurry and be supported, where available, by tools that assist in conveying the relevant evidence and in supporting plan development. Examples of these tools include treatment SDM encounter aids and the Genetics Adviser. Patients are expected to play a key role in making decisions and implementing plans of care, but several evolving challenges related to the unfettered access to information and expertise of varying trustworthiness and complexity in between interactions with clinicians can both support and complicate this role. SDM should result in a plan of care that is maximally responsive to the biology and biography of each patient, maximally supportive of each patient's goals and priorities, and minimally disruptive of their lives and loves.
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Affiliation(s)
- Salma Shickh
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
- Genomics Health Services Research Program, Li Ka Shing Knowledge Institute, St Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada
| | - Konstantinos Leventakos
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, MN
- Department of Medical Oncology, Mayo Clinic, Rochester, MN
| | - Mark A Lewis
- Division of Gastrointestinal Oncology, Intermountain Healthcare, Salt Lake City, UT
| | - Yvonne Bombard
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
- Genomics Health Services Research Program, Li Ka Shing Knowledge Institute, St Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada
- Ontario Institute for Cancer Research, Toronto, ON, Canada
| | - Victor M Montori
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, MN
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6
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Shickh S, Sebastian A, Clausen M, Mighton C, Elser C, Eisen A, Waldman L, Panchal S, Ward T, Carroll JC, Glogowski E, Schrader KA, Lerner-Ellis J, Kim RH, Thorpe KE, Bombard Y. Great expectations: patients' preferences for clinically significant results from genomic sequencing. Hum Genet 2023; 142:553-562. [PMID: 36943453 PMCID: PMC11249280 DOI: 10.1007/s00439-023-02543-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Accepted: 03/05/2023] [Indexed: 03/23/2023]
Abstract
We aimed to describe patient preferences for a broad range of secondary findings (SF) from genomic sequencing (GS) and factors driving preferences. We assessed preference data within a trial of the Genomics ADvISER, (SF decision aid) among adult cancer patients. Participants could choose from five categories of SF: (1) medically actionable; (2) polygenic risks; (3) rare diseases; (4) early-onset neurological diseases; and (5) carrier status. We analyzed preferences using descriptive statistics and drivers of preferences using multivariable logistic regression models. The 133 participants were predominantly European (74%) or East Asian or mixed ancestry (13%), female (90%), and aged > 50 years old (60%). The majority chose to receive SF. 97% (129/133) chose actionable findings with 36% (48/133) choosing all 5 categories. Despite the lack of medical actionability, participants were interested in receiving SF of polygenic risks (74%), carrier status (75%), rare diseases (59%), and early-onset neurologic diseases (53%). Older participants were more likely to be interested in receiving results for early-onset neurological diseases, while those exhibiting lower decisional conflict were more likely to select all categories. Our results highlight a disconnect between cancer patient preferences and professional guidelines on SF, such as ACMG's recommendations to only return medically actionable secondary findings. In addition to clinical evidence, future guidelines should incorporate patient preferences.
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Affiliation(s)
- Salma Shickh
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
- Genomics Health Services Research Program, Li Ka Shing Knowledge Institute of St. Michael's Hospital, Unity Health Toronto, 30 Bond Street, Toronto, ON, M5B 1W8, Canada
| | - Agnes Sebastian
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
- Genomics Health Services Research Program, Li Ka Shing Knowledge Institute of St. Michael's Hospital, Unity Health Toronto, 30 Bond Street, Toronto, ON, M5B 1W8, Canada
| | - Marc Clausen
- Genomics Health Services Research Program, Li Ka Shing Knowledge Institute of St. Michael's Hospital, Unity Health Toronto, 30 Bond Street, Toronto, ON, M5B 1W8, Canada
| | - Chloe Mighton
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
- Genomics Health Services Research Program, Li Ka Shing Knowledge Institute of St. Michael's Hospital, Unity Health Toronto, 30 Bond Street, Toronto, ON, M5B 1W8, Canada
| | - Christine Elser
- University Health Network, Toronto, ON, Canada
- Department of Medicine, University of Toronto, Toronto, ON, Canada
| | - Andrea Eisen
- Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Larissa Waldman
- Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
| | - Seema Panchal
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
- Marvelle Koffler Breast Centre, Mount Sinai Hospital, Sinai Health, Toronto, ON, Canada
| | - Thomas Ward
- Zane Cohen Centre, Mount Sinai Hospital, Sinai Health, Toronto, ON, Canada
| | - June C Carroll
- Ray D Wolfe Department of Family Medicine, Sinai Health, Toronto, ON, Canada
- Department of Family and Community Medicine, University of Toronto, Toronto, ON, Canada
| | | | - Kasmintan A Schrader
- BC Cancer, Vancouver, BC, Canada
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
| | - Jordan Lerner-Ellis
- Lunenfeld Tanenbaum Research Institute, Mount Sinai Hospital, Sinai Health, Toronto, ON, Canada
- Pathology and Laboratory Medicine, Mount Sinai Hospital, Sinai Health, Toronto, ON, Canada
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
| | - Raymond H Kim
- Department of Medicine, University of Toronto, Toronto, ON, Canada
- Division of Medical Oncology and Hematology, Princess Margaret Cancer Centre, University Health Network and Sinai Health, Toronto, ON, Canada
- Division of Clinical and Metabolic Genetics, The Hospital for Sick Children, Toronto, ON, Canada
- Ontario Institute for Cancer Research, Toronto, ON, Canada
| | - Kevin E Thorpe
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
- Applied Health Research Centre, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Toronto, ON, Canada
| | - Yvonne Bombard
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada.
- Genomics Health Services Research Program, Li Ka Shing Knowledge Institute of St. Michael's Hospital, Unity Health Toronto, 30 Bond Street, Toronto, ON, M5B 1W8, Canada.
- Ontario Institute for Cancer Research, Toronto, ON, Canada.
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Whiwon L, Salma S, Daniel A, Stephanie L, Marc C, Cherith S, Abby T, Angela S, Robin H, Yvonne B. Patient-facing digital tools for delivering genetic services: a systematic review. J Med Genet 2023; 60:1-10. [PMID: 36137613 DOI: 10.1136/jmg-2022-108653] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Accepted: 07/19/2022] [Indexed: 02/04/2023]
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.
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Affiliation(s)
- Lee Whiwon
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
| | - Shickh Salma
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
| | - Assamad Daniel
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
| | - Luca Stephanie
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
| | - Clausen Marc
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
| | - Somerville Cherith
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
| | - Tafler Abby
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
| | - Shaw Angela
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
- Genomics Health Services Research Program, Li Ka Shing Knowledge Institute, St Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada
| | - Hayeems Robin
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
- Genomics Health Services Research Program, Li Ka Shing Knowledge Institute, St Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada
| | - Bombard Yvonne
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
- Genomics Health Services Research Program, Li Ka Shing Knowledge Institute, St Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada
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8
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Torr B, Jones C, Choi S, Allen S, Kavanaugh G, Hamill M, Garrett A, MacMahon S, Loong L, Reay A, Yuan L, Valganon Petrizan M, Monson K, Perry N, Fallowfield L, Jenkins V, Gold R, Taylor A, Gabe R, Wiggins J, Lucassen A, Manchanda R, Gandhi A, George A, Hubank M, Kemp Z, Evans DG, Bremner S, Turnbull C. A digital pathway for genetic testing in UK NHS patients with cancer: BRCA-DIRECT randomised study internal pilot. J Med Genet 2022; 59:1179-1188. [PMID: 35868849 PMCID: PMC9691828 DOI: 10.1136/jmg-2022-108655] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Accepted: 07/03/2022] [Indexed: 01/12/2023]
Abstract
BACKGROUND Germline genetic testing affords multiple opportunities for women with breast cancer, however, current UK NHS models for delivery of germline genetic testing are clinician-intensive and only a minority of breast cancer cases access testing. METHODS We designed a rapid, digital pathway, supported by a genetics specialist hotline, for delivery of germline testing of BRCA1/BRCA2/PALB2 (BRCA-testing), integrated into routine UK NHS breast cancer care. We piloted the pathway, as part of the larger BRCA-DIRECT study, in 130 unselected patients with breast cancer and gathered preliminary data from a randomised comparison of delivery of pretest information digitally (fully digital pathway) or via telephone consultation with a genetics professional (partially digital pathway). RESULTS Uptake of genetic testing was 98.4%, with good satisfaction reported for both the fully and partially digital pathways. Similar outcomes were observed in both arms regarding patient knowledge score and anxiety, with <5% of patients contacting the genetics specialist hotline. All progression criteria established for continuation of the study were met. CONCLUSION Pilot data indicate preliminary demonstration of feasibility and acceptability of a fully digital pathway for BRCA-testing and support proceeding to a full powered study for evaluation of non-inferiority of the fully digital pathway, detailed quantitative assessment of outcomes and operational economic analyses. TRIAL REGISTRATION NUMBER ISRCTN87845055.
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Affiliation(s)
- Bethany Torr
- Institute of Cancer Research, Division of Genetics and Epidemiology, Sutton, UK
| | - Christopher Jones
- Clinical Trials Unit, Brighton and Sussex Medical School, Brighton, UK
| | - Subin Choi
- Institute of Cancer Research, Division of Genetics and Epidemiology, Sutton, UK
| | - Sophie Allen
- Institute of Cancer Research, Division of Genetics and Epidemiology, Sutton, UK
| | - Grace Kavanaugh
- Institute of Cancer Research, Division of Genetics and Epidemiology, Sutton, UK
| | - Monica Hamill
- Institute of Cancer Research, Division of Genetics and Epidemiology, Sutton, UK
| | - Alice Garrett
- Institute of Cancer Research, Division of Genetics and Epidemiology, Sutton, UK
| | - Suzanne MacMahon
- Centre for Molecular Pathology, Institute of Cancer Research Sutton, Sutton, UK
| | - Lucy Loong
- Institute of Cancer Research, Division of Genetics and Epidemiology, Sutton, UK
| | - Alistair Reay
- Centre for Molecular Pathology, Institute of Cancer Research Sutton, Sutton, UK
| | - Lina Yuan
- Centre for Molecular Pathology, Institute of Cancer Research Sutton, Sutton, UK
| | | | - Kathryn Monson
- Sussex Health Outcomes, Research and Education in Cancer (SHORE-C), Brighton and Sussex Medical School, Brighton, UK
| | - Nicky Perry
- Clinical Trials Unit, Brighton and Sussex Medical School, Brighton, UK
| | - Lesley Fallowfield
- Sussex Health Outcomes, Research and Education in Cancer (SHORE-C), Brighton and Sussex Medical School, Brighton, UK
| | - Valerie Jenkins
- Sussex Health Outcomes, Research and Education in Cancer (SHORE-C), Brighton and Sussex Medical School, Brighton, UK
| | | | - Amy Taylor
- Clinical Genetics, East Anglian Medical Genetics Service, Cambridge, UK
| | - Rhian Gabe
- Wolfson Institute of Population Health, Queen Mary's University of London, London, UK
| | - Jennifer Wiggins
- Cancer Genetics Unit, Royal Marsden NHS Foundation Trust, London, UK
| | - Anneke Lucassen
- Clinical Ethics and Law at Southampton (CELS), University of Southampton, Southampton, UK
- Department of Medicine, Univerity of Oxford Nuffield, Oxford, UK
| | - Ranjit Manchanda
- Wolfson Institute of Population Health, Queen Mary's University of London, London, UK
- Department of Gynaecological Oncology, Barts Health NHS Trust, London, UK
- Department of Health Services Research, Faculty of Public Health & Policy, London School of Hygiene and Tropical Medicine, London, UK
| | - Ashu Gandhi
- School of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
- Prevent Breast Cancer Centre, Wythenshawe Hospital Manchester Universities Foundation Trust, Manchester, UK
| | - Angela George
- Institute of Cancer Research, Division of Genetics and Epidemiology, Sutton, UK
- Cancer Genetics Unit, Royal Marsden NHS Foundation Trust, London, UK
| | - Michael Hubank
- Centre for Molecular Pathology, Institute of Cancer Research Sutton, Sutton, UK
| | - Zoe Kemp
- Institute of Cancer Research, Division of Genetics and Epidemiology, Sutton, UK
- Cancer Genetics Unit, Royal Marsden NHS Foundation Trust, London, UK
| | - D Gareth Evans
- Nightingale and Genesis Breast Cancer Centre, University Hospital of South Manchester NHS Foundation Trust, Manchester, UK
- Division of Evolution and Genomic Sciences, The University of Manchester, Manchester, UK
| | - Stephen Bremner
- Clinical Trials Unit, Brighton and Sussex Medical School, Brighton, UK
| | - Clare Turnbull
- Institute of Cancer Research, Division of Genetics and Epidemiology, Sutton, UK
- Cancer Genetics Unit, Royal Marsden NHS Foundation Trust, London, UK
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9
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Mighton C, Shickh S, Aguda V, Krishnapillai S, Adi-Wauran E, Bombard Y. From the patient to the population: Use of genomics for population screening. Front Genet 2022; 13:893832. [PMID: 36353115 PMCID: PMC9637971 DOI: 10.3389/fgene.2022.893832] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Accepted: 09/26/2022] [Indexed: 10/22/2023] Open
Abstract
Genomic medicine is expanding from a focus on diagnosis at the patient level to prevention at the population level given the ongoing under-ascertainment of high-risk and actionable genetic conditions using current strategies, particularly hereditary breast and ovarian cancer (HBOC), Lynch Syndrome (LS) and familial hypercholesterolemia (FH). The availability of large-scale next-generation sequencing strategies and preventive options for these conditions makes it increasingly feasible to screen pre-symptomatic individuals through public health-based approaches, rather than restricting testing to high-risk groups. This raises anew, and with urgency, questions about the limits of screening as well as the moral authority and capacity to screen for genetic conditions at a population level. We aimed to answer some of these critical questions by using the WHO Wilson and Jungner criteria to guide a synthesis of current evidence on population genomic screening for HBOC, LS, and FH.
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Affiliation(s)
- Chloe Mighton
- Genomics Health Services Research Program, St. Michael’s Hospital, Unity Health Toronto, Toronto, ON, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
| | - Salma Shickh
- Genomics Health Services Research Program, St. Michael’s Hospital, Unity Health Toronto, Toronto, ON, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
| | - Vernie Aguda
- Genomics Health Services Research Program, St. Michael’s Hospital, Unity Health Toronto, Toronto, ON, Canada
- Centre for Medical Education, School of Medicine, Cardiff University, Cardiff, United Kingdom
| | - Suvetha Krishnapillai
- Genomics Health Services Research Program, St. Michael’s Hospital, Unity Health Toronto, Toronto, ON, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
| | - Ella Adi-Wauran
- Genomics Health Services Research Program, St. Michael’s Hospital, Unity Health Toronto, Toronto, ON, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
| | - Yvonne Bombard
- Genomics Health Services Research Program, St. Michael’s Hospital, Unity Health Toronto, Toronto, ON, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
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10
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Bombard Y, Ginsburg GS, Sturm AC, Zhou AY, Lemke AA. Digital health-enabled genomics: Opportunities and challenges. Am J Hum Genet 2022; 109:1190-1198. [PMID: 35803232 PMCID: PMC9300757 DOI: 10.1016/j.ajhg.2022.05.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
Abstract
Digital health solutions, with apps, virtual care, and electronic medical records, are gaining momentum across all medical disciplines, and their adoption has been accelerated, in part, by the COVID-19 pandemic. Personal wearables, sensors, and mobile technologies are increasingly being used to identify health risks and assist in diagnosis, treatment, and monitoring of health and disease. Genomics is a vanguard of digital healthcare as we witness a convergence of the fields of genomic and digital medicine. Spurred by the acute need to increase health literacy, empower patients' preference-sensitive decisions, or integrate vast amounts of complex genomic data into the clinical workflow, there has been an emergence of digital support tools in genomics-enabled care. We present three use cases that demonstrate the application of these converging technologies: digital genomics decision support tools, conversational chatbots to scale the genetic counseling process, and the digital delivery of comprehensive genetic services. These digital solutions are important to facilitate patient-centered care delivery, improve patient outcomes, and increase healthcare efficiencies in genomic medicine. Yet the development of these innovative digital genomic technologies also reveals strategic challenges that need to be addressed before genomic digital health can be broadly adopted. Alongside key evidentiary gaps in clinical and cost-effectiveness, there is a paucity of clinical guidelines, policy, and regulatory frameworks that incorporate digital health. We propose a research agenda, guided by learning healthcare systems, to realize the vision of digital health-enabled genomics to ensure its sustainable and equitable deployment in clinical care.
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Affiliation(s)
- Yvonne Bombard
- University of Toronto, Genomics Health Services Research Program, St. Michael’s Hospital, Unity Health Toronto, 30 Bond Street, Toronto, ON, M5B 1W8, Canada,Corresponding author
| | - Geoffrey S. Ginsburg
- All of Us Research Program, National Institutes of Health, Bethesda, MD 20892, USA
| | - Amy C. Sturm
- 23andMe, 223 North Mathilda Avenue, Sunnyvale, CA 94086, USA
| | - Alicia Y. Zhou
- Color Health, Inc, 831 Mitten Road, Burlingame, CA 94010, USA
| | - Amy A. Lemke
- Norton Children’s Research Institute, Affiliated with the University of Louisville School of Medicine, 571 South Floyd Street, Louisville, KY 40202, USA
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11
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Shickh S, Mighton C, Clausen M, Adi-Wauran E, Hirjikaka D, Kodida R, Krishnapillai S, Reble E, Sam J, Shaw A, Lerner-Ellis J, Baxter NN, Laupacis A, Bombard Y. "Doctors shouldn't have to cheat the system": Clinicians' real-world experiences of the utility of genomic sequencing. Genet Med 2022; 24:1888-1898. [PMID: 35612591 DOI: 10.1016/j.gim.2022.04.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Revised: 04/27/2022] [Accepted: 04/28/2022] [Indexed: 11/24/2022] Open
Abstract
PURPOSE Emerging genetic tests such as genomic sequencing (GS) can generate a broad range of benefits, but funding criteria only prioritize diagnosis and clinical management. There is limited evidence on all types of benefits obtained from GS in practice. We aimed to explore real-world experiences of Canadian clinicians across specialties on the full range of benefits obtained from the results from GS. METHODS We conducted a qualitative study using semistructured interviews with Canadian clinicians. Transcripts were thematically analyzed using constant comparison. RESULTS In total, 25 clinicians participated, including 12 geneticists, 7 genetic counselors, 4 oncologists, 1 neurologist, and 1 family physician. Although diagnoses and management were the most valued benefits of GS, clinicians also prioritized nontraditional utility, such as access to community supports. However, clinicians felt "restricted" by funding bodies, which only approved funding when GS would inform diagnoses and management. Consequently, clinicians sought ways to "cheat the system" to access GS (eg, research testing) but acknowledged workarounds were burdensome, drove inequity, and undermined patient care. CONCLUSION Current governance structures undervalue real-world benefits of GS leading clinicians to adopt workarounds, which jeopardize patient care. These results support calls for the expansion of the definition of clinical utility and research to quantify the additional benefits.
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Affiliation(s)
- Salma Shickh
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada; Genomics Health Services and Policy Research Program, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada
| | - Chloe Mighton
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada; Genomics Health Services and Policy Research Program, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada
| | - Marc Clausen
- Genomics Health Services and Policy Research Program, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada
| | - Ella Adi-Wauran
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada; Genomics Health Services and Policy Research Program, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada
| | - Daena Hirjikaka
- Genomics Health Services and Policy Research Program, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada
| | - Rita Kodida
- Genomics Health Services and Policy Research Program, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada
| | - Suvetha Krishnapillai
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada; Genomics Health Services and Policy Research Program, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada
| | - Emma Reble
- Genomics Health Services and Policy Research Program, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada
| | - Jordan Sam
- Genomics Health Services and Policy Research Program, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada
| | - Angela Shaw
- Genomics Health Services and Policy Research Program, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada
| | - Jordan Lerner-Ellis
- Lunenfeld Tanenbaum Research Institute, Sinai Health, Toronto, Ontario, Canada; Pathology and Laboratory Medicine, Mount Sinai Hospital, Sinai Health, Toronto, Ontario, Canada; Department of Laboratory Medicine and Pathobiology, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Nancy N Baxter
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada; Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada; Department of Surgery, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada; Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Andreas Laupacis
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada; Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada
| | - Yvonne Bombard
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada; Genomics Health Services and Policy Research Program, Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada; Ontario Institute for Cancer Research, Toronto, Ontario, Canada.
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12
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Shickh S, Hirjikaka D, Clausen M, Kodida R, Mighton C, Reble E, Sam J, Panchal S, Aronson M, Graham T, Armel SR, Glogowski E, Elser C, Eisen A, Carroll JC, Shuman C, Seto E, Baxter NN, Scheer A, Shastri-Estrada S, Feldman G, Thorpe KE, Schrader KA, Lerner-Ellis J, Kim RH, Faghfoury H, Bombard Y. Genetics Adviser: a protocol for a mixed-methods randomised controlled trial evaluating a digital platform for genetics service delivery. BMJ Open 2022; 12:e060899. [PMID: 35487723 PMCID: PMC9058789 DOI: 10.1136/bmjopen-2022-060899] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
INTRODUCTION The high demand for genetic tests and limited supply of genetics professionals has created a need for alternative service delivery models. Digital tools are increasingly being used to support multiple points in the genetic testing journey; however, none are transferable across multiple clinical specialties and settings nor do they encompass the entire trajectory of the journey. We aim to evaluate the effectiveness of the Genetics Adviser, an interactive, patient-facing, online digital health tool that delivers pre-test counselling, provides support during the waiting period for results, and returns results with post-test counselling, encompassing the entire patient genetic testing journey. METHODS AND ANALYSIS We will compare the Genetics Adviser paired with a brief genetic counselling session to genetic counselling alone in a randomised controlled trial. One hundred and forty patients who previously received uninformative genetic test results for their personal and family history of cancer will be recruited from familial cancer clinics in Toronto and offered all clinically significant results from genomic sequencing. Participants randomised into the intervention arm will use the Genetics Adviser to learn about genomic sequencing, receive pre-test counselling, support during the waiting period and results, supplemented with brief counselling from a genetic counsellor. Participants in the control arm will receive standard pre-test and post-test counselling for genomic sequencing from a genetic counsellor. Our primary outcome is decisional conflict following pre-test counselling from the Genetics Adviser+genetic counsellor or counsellor alone. Secondary outcomes include: knowledge, satisfaction with decision-making, anxiety, quality of life, psychological impact of results, empowerment, acceptability and economic impact for patients and the health system. A subset of patients will be interviewed to assess user experience. ETHICS AND DISSEMINATION This study has been approved by Clinical Trials Ontario Streamlined Research Ethics Review System (REB#20-035). Results will be shared through stakeholder workshops, national and international conferences and peer-reviewed journals. TRIAL REGISTRATION NUMBER NCT04725565.
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Affiliation(s)
- Salma Shickh
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
- Li Ka Shing Knowledge Institute, St Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada
| | - Daena Hirjikaka
- Li Ka Shing Knowledge Institute, St Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada
| | - Marc Clausen
- Li Ka Shing Knowledge Institute, St Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada
| | - Rita Kodida
- Li Ka Shing Knowledge Institute, St Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada
| | - Chloe Mighton
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
- Li Ka Shing Knowledge Institute, St Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada
| | - Emma Reble
- Li Ka Shing Knowledge Institute, St Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada
| | - Jordan Sam
- Li Ka Shing Knowledge Institute, St Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada
| | - Seema Panchal
- Marvelle Koffler Breast Centre, Mount Sinai Hospital, Sinai Health System, Toronto, Ontario, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
| | - Melyssa Aronson
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
- Zane Cohen Centre, Mount Sinai Hospital, Sinai Health System, Toronto, Ontario, Canada
- The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Tracy Graham
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
- Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Susan Randall Armel
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
- Princess Margaret Cancer Centre, Toronto, Ontario, Canada
| | | | - Christine Elser
- Marvelle Koffler Breast Centre, Mount Sinai Hospital, Sinai Health System, Toronto, Ontario, Canada
- University Health Network, Toronto, Ontario, Canada
- Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Andrea Eisen
- Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - June C Carroll
- Ray D Wolfe Department of Family Medicine, Mount Sinai Hospital, Sinai Health System, Toronto, Ontario, Canada
- Department of Family and Community Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Cheryl Shuman
- Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
| | - Emily Seto
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
- Centre for Global eHealth Innovation, Techna Institute, University Health Network, Toronto, Ontario, Canada
| | - Nancy N Baxter
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
- Li Ka Shing Knowledge Institute, St Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada
- Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
- Department of Surgery, University of Toronto, Toronto, Ontario, Canada
| | - Adena Scheer
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
- Li Ka Shing Knowledge Institute, St Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada
- Department of Surgery, University of Toronto, Toronto, Ontario, Canada
| | | | - Geoff Feldman
- Ontario Disability Coalition, Toronto, Ontario, Canada
| | - Kevin E Thorpe
- Applied Health Research Centre (AHRC), Li Ka Shing Knowledge Institute of St Michael's Hospital, Toronto, Ontario, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - Kasmintan A Schrader
- BC Cancer, Vancouver, British Columbia, Canada
- Department of Medical Genetics, The University of British Columbia, Vancouver, British Columbia, Canada
| | - Jordan Lerner-Ellis
- Pathology and Laboratory Medicine, Mount Sinai Hospital, Sinai Health System, Toronto, Ontario, Canada
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada
- Lunenfeld Tanenbaum Research Institute, Sinai Health System, Toronto, Ontario, Canada
| | - Raymond H Kim
- The Hospital for Sick Children, Toronto, Ontario, Canada
- University Health Network, Toronto, Ontario, Canada
- Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Hanna Faghfoury
- Fred A Litwin and Family Centre in Genetic Medicine, University Health Network, Toronto, Ontario, Canada
| | - Yvonne Bombard
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada
- Li Ka Shing Knowledge Institute, St Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada
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13
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Bangash H, Makkawy A, Gundelach JH, Miller AA, Jacobson KA, Kullo IJ. Web-Based Tool (FH Family Share) to Increase Uptake of Cascade Testing for Familial Hypercholesterolemia: Development and Evaluation. JMIR Hum Factors 2022; 9:e32568. [PMID: 35166678 PMCID: PMC8889478 DOI: 10.2196/32568] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Revised: 10/29/2021] [Accepted: 11/07/2021] [Indexed: 11/18/2022] Open
Abstract
Background Familial hypercholesterolemia, a prevalent genetic disorder, remains significantly underdiagnosed in the United States. Cascade testing, wherein individuals diagnosed with familial hypercholesterolemia— probands—contact their family members to inform them of their risk for familial hypercholesterolemia, has low uptake in the United States. Digital tools are needed to facilitate communication between familial hypercholesterolemia probands and their family members and to promote sharing of familial hypercholesterolemia–related risk information. Objective We aimed to create and evaluate a web-based tool designed to enhance familial communication and promote cascade testing for familial hypercholesterolemia. Methods A hybrid type 1 implementation science framework and a user-centered design process were used to develop an interactive web-based tool—FH Family Share—that enables familial hypercholesterolemia probands to communicate information about their familial hypercholesterolemia diagnosis with at-risk relatives. Probands can also use the tool to draw a family pedigree and learn more about familial hypercholesterolemia through education modules and curated knowledge resources. Usability guidelines and standards were taken into account during the design and development of the tool. The initial prototype underwent a cognitive walkthrough, which was followed by usability testing with key stakeholders including genetic counselors and patients with familial hypercholesterolemia. Participants navigated the prototype using the think-aloud technique, and their feedback was used to refine features of the tool. Results Key themes that emerged from the cognitive walkthrough were design, format, navigation, terminology, instructions, and learnability. Expert feedback from the cognitive walkthrough resulted in a rebuild of the web-based tool to align it with institutional standards. Usability testing with genetic counselors and patients with familial hypercholesterolemia provided insights on user experience, satisfaction and interface design and highlighted specific modifications that were made to refine the features of FH Family Share. Genetic counselors and patients with familial hypercholesterolemia suggested inclusion of the following features in the web-based tool: (1) a letter-to-family-member email template, (2) education modules, and (3) knowledge resources. Surveys revealed that 6 of 9 (67%) genetic counselors found information within FH Family Share very easy to find, and 5 of 9 (56%) genetic counselors found information very easy to understand; 5 of 9 (56%) patients found information very easy to find within the website, and 7 of 9 (78%) patients found information very easy to understand. All genetic counselors and patients indicated that FH Family Share was a resource worth returning to. Conclusions FH Family Share facilitates communication between probands and their relatives. Once informed, at-risk family members have the option to seek testing and treatment for familial hypercholesterolemia.
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Affiliation(s)
| | - Ahmed Makkawy
- Saharafox Creative Agency, Rochester, MN, United States
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14
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Shickh S, Mighton C, Uleryk E, Pechlivanoglou P, Bombard Y. The clinical utility of exome and genome sequencing across clinical indications: a systematic review. Hum Genet 2021; 140:1403-1416. [PMID: 34368901 DOI: 10.1007/s00439-021-02331-x] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Accepted: 07/31/2021] [Indexed: 12/15/2022]
Abstract
Exome sequencing and genome sequencing have the potential to improve clinical utility for patients undergoing genetic investigations. However, evidence of clinical utility is limited to pediatric populations; we aimed to fill this gap by conducting a systematic review of the literature on the clinical utility of exome/genome sequencing across disease indications in pediatric and adult populations. MEDLINE, EMBASE and Cochrane Library were searched between 2016 and 2020. Quantitative studies evaluating diagnostic yield were included; other measures of clinical utility such as changes to clinical management were documented if reported. Two reviewers screened, extracted data, and appraised risk of bias. Fifty studies met our inclusion criteria. All studies reported diagnostic yield, which ranged from 3 to 70%, with higher range of yields reported for neurological indications and acute illness ranging from 22 to 68% and 37-70%, respectively. Diagnoses triggered a range of clinical management changes including surveillance, reproductive-risk counseling, and identifying at-risk relatives in 4-100% of patients, with higher frequencies reported for acute illness ranging from 67 to 95%. The frequency of variants of uncertain significance ranged from 5 to 85% across studies with a potential trend of decreasing frequency over time and higher rates identified in patients of non-European ancestry. This review provides evidence for a higher range of diagnostic yield of exome/genome sequencing compared to standard genetic tests, particularly in neurological and acute indications. However, we identified significant heterogeneity in study procedures and outcomes, precluding a meaningful meta-analysis and certainty in the evidence available for decision-making. Future research that incorporates a comprehensive and consistent approach in capturing clinical utility of exome/genome sequencing across broader ancestral groups is necessary to improve diagnostic accuracy and yield and allow for analysis of trends over time.Prospero registration CRD42019094101.
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Affiliation(s)
- Salma Shickh
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada.,Genomics Health Services Research Program, Li Ka Shing Knowledge Institute, Unity Health Toronto, Toronto, ON, Canada
| | - Chloe Mighton
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada.,Genomics Health Services Research Program, Li Ka Shing Knowledge Institute, Unity Health Toronto, Toronto, ON, Canada
| | | | - Petros Pechlivanoglou
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada.,The Hospital for Sick Children, Toronto, ON, Canada
| | - Yvonne Bombard
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada. .,Genomics Health Services Research Program, Li Ka Shing Knowledge Institute, Unity Health Toronto, Toronto, ON, Canada. .,Li Ka Shing Knowledge Institute of St. Michael's Hospital, University of Toronto, 30 Bond Street, Toronto, ON, M5B 1W8, Canada.
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