Key drivers of family-level utility of pediatric genomic sequencing: a qualitative analysis to support preference research
Open Access
- 25 November 2022
- journal article
- research article
- Published by Springer Nature in European Journal of Human Genetics
- Vol. 31 (4) , 445-452
Abstract
Given that pediatric genomic sequencing (GS) may have implications for the health and well-being of both the child and family, a clearer understanding of the key drivers of the utility of GS from the family perspective is needed. The purpose of this study is to explore what is important to caregivers of pediatric patients regarding clinical GS, with a focus on family-level considerations. We conducted semi-structured interviews with caregivers (n = 41) of pediatric patients who had been recommended for or completed GS that explored the scope of factors caregivers considered when deciding whether to pursue GS for their child. We analyzed the qualitative data in multiple rounds of coding using thematic analysis. Caregivers raised important family-level considerations, in addition to those specifically for their child, which included wanting the best chance at good quality of life for the family, the ability to learn about family health, the impact on the caregiver’s well-being, privacy concerns among family members, and the cost of testing to the family. We developed a framework of key drivers of utility consisting of four domains that influenced caregivers’ decision making: underlying values, perceived benefits, perceived risks, and other pragmatic considerations regarding GS. These findings can inform measurement approaches that better capture the utility of pediatric GS for families and improve assessments of the value of clinical GS.Keywords
All Related Versions
Funding Information
- U.S. Department of Health & Human Services | NIH | National Human Genome Research Institute (K99HG011491)
This publication has 30 references indexed in Scilit:
- The Role of Qualitative Research Methods in Discrete Choice ExperimentsMedical Decision Making, 2017
- Choice Experiments to Quantify Preferences for Health and Healthcare: State of the PracticeApplied Health Economics and Health Policy, 2016
- Designing a Stated Choice Experiment: The Value of a Qualitative ProcessJournal of Choice Modelling, 2012
- Thematic analysis.2012
- Using qualitative methods for attribute development for discrete choice experiments: issues and recommendationsHealth Economics, 2011
- Research electronic data capture (REDCap)—A metadata-driven methodology and workflow process for providing translational research informatics supportJournal of Biomedical Informatics, 2009
- Consolidated criteria for reporting qualitative research (COREQ): a 32-item checklist for interviews and focus groupsInternational Journal for Quality in Health Care, 2007
- Developing attributes and levels for discrete choice experiments using qualitative methodsJournal of Health Services Research & Policy, 2007
- Preference-Based Measures in Economic Evaluation in Health CareAnnual Review of Public Health, 2000
- The MOS Short-form General Health SurveyMedical Care, 1988