Dataset Information

Challenges in returning results in a genomic medicine implementation study: the Return of Actionable Variants Empirical (RAVE) study.

ABSTRACT: To inform the process of returning results in genome sequencing studies, we conducted a quantitative and qualitative assessment of challenges encountered during the Return of Actionable Variants Empiric (RAVE) study conducted at Mayo Clinic. Participants (n?=?2535, mean age 63?±?7, 57% female) were sequenced for 68 clinically actionable genes and 14 single nucleotide variants. Of 122 actionable results detected, 118 were returnable; results were returned by a genetic counselor-86 in-person and 12 by phone. Challenges in returning actionable results were encountered in a significant proportion (38%) of the cohort and were related to sequencing and participant contact. Sequencing related challenges (n?=?14), affecting 13 participants, included reports revised based on clinical presentation (n?=?3); reports requiring corrections (n?=?2); mosaicism requiring alternative DNA samples for confirmation (n?=?3); and variant re-interpretation due to updated informatics pipelines (n?=?6). Participant contact related challenges (n?=?44), affecting 38 participants, included nonresponders (n?=?20), decedents (n?=?1), and previously known results (n?=?23). These results should be helpful to investigators preparing for return of results in large-scale genomic sequencing projects.

SUBMITTER: Kochan DC

PROVIDER: S-EPMC7198538 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Challenges in returning results in a genomic medicine implementation study: the Return of Actionable Variants Empirical (RAVE) study.

Kochan David C DC Winkler Erin E Lindor Noralane N Shaibi Gabriel Q GQ Olson Janet J Caraballo Pedro J PJ Freimuth Robert R Pacyna Joel E JE Breitkopf Carmen Radecki CR Sharp Richard R RR Kullo Iftikhar J IJ

NPJ genomic medicine 20200504

To inform the process of returning results in genome sequencing studies, we conducted a quantitative and qualitative assessment of challenges encountered during the Return of Actionable Variants Empiric (RAVE) study conducted at Mayo Clinic. Participants (<i>n</i> = 2535, mean age 63 ± 7, 57% female) were sequenced for 68 clinically actionable genes and 14 single nucleotide variants. Of 122 actionable results detected, 118 were returnable; results were returned by a genetic counselor-86 in-perso ...[more]

PMID: 32377377

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Project description:BackgroundThe field of digital medicine has seen rapid growth over the past decade. With this unfettered growth, challenges surrounding interoperability have emerged as a critical barrier to translating digital medicine into practice. In order to understand how to mitigate challenges in digital medicine research and practice, this community must understand the landscape of digital medicine professionals, which digital medicine tools are being used and how, and user perspectives on current challenges in the field of digital medicine.ObjectiveThe primary objective of this study is to provide information to the digital medicine community that is working to establish frameworks and best practices for interoperability in digital medicine. We sought to learn about the background of digital medicine professionals and determine which sensors and file types are being used most commonly in digital medicine research. We also sought to understand perspectives on digital medicine interoperability.MethodsWe used a web-based survey to query a total of 56 digital medicine professionals from May 1, 2020, to July 10, 2020, on their educational and work experience, the sensors, file types, and toolkits they use professionally, and their perspectives on interoperability in digital medicine.ResultsWe determined that the digital medicine community comes from diverse educational backgrounds and uses a variety of sensors and file types. Sensors measuring physical activity and the cardiovascular system are the most frequently used, and smartphones continue to be the dominant source of digital health information collection in the digital medicine community. We show that there is not a general consensus on file types in digital medicine, and data are currently handled in multiple ways. There is consensus that interoperability is a critical impediment in digital medicine, with 93% (52) of survey respondents in agreement. However, only 36% (20) of respondents currently use tools for interoperability in digital medicine. We identified three key interoperability needs to be met: integration with electronic health records, implementation of standard data schemas, and standard and verifiable methods for digital medicine research. We show that digital medicine professionals are eager to adopt new tools to solve interoperability problems, and we suggest tools to support digital medicine interoperability.ConclusionsUnderstanding the digital medicine community, the sensors and file types they use, and their perspectives on interoperability will enable the development and implementation of solutions that fill critical interoperability gaps in digital medicine. The challenges to interoperability outlined by this study will drive the next steps in creating an interoperable digital medicine community. Establishing best practices to address these challenges and employing platforms for digital medicine interoperability will be essential to furthering the field of digital medicine.

Dataset Information

Challenges in returning results in a genomic medicine implementation study: the Return of Actionable Variants Empirical (RAVE) study.

Publications

Challenges in returning results in a genomic medicine implementation study: the Return of Actionable Variants Empirical (RAVE) study.

Similar Datasets

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