Adapting Clinical Systems to Enable Adolescents' Genomic Choices

Abstract

Background We offered adolescents personalized choices about the type of genetic results they wanted to learn during a research study and created a workflow to filter and transfer the results to the electronic health record (EHR).

Methods We describe adaptations needed to ensure that adolescents' results documented in the EHR and returned to adolescent/parent dyads matched their choices. A web application enabled manual modification of the underlying laboratory report data based on adolescents' choices. The final PDF format of the laboratory reports was not viewable through the EHR patient portal, so an EHR form was created to support the manual entry of discrete results that could be viewed in the portal.

Results Enabling adolescents' choices about genetic results was a labor-intensive process. More than 350 hours was required for development of the application and EHR form, as well as over 50 hours of a study professional's time to enter choices into the application and EHR. Adolescents and their parents who learned genetic results through the patient portal indicated that they were satisfied with the method of return and would make their choices again if given the option.

Conclusion Although future EHR upgrades are expected to enable patient portal access to PDFs, additional improvements are needed to allow the results to be partitioned and filtered based on patient preferences. Furthermore, separating these results into more discrete components will allow them to be stored separately in the EHR, supporting the use of these data in clinical decision support or artificial intelligence applications.

Keywords

clinical information systems - implementation and deployment - general aspects - facilitators and barriers - electronic health records and systems - patient records - specific types

Protection of Human and Animal Subjects

The study was reviewed and approved by Cincinnati Children's Hospital Medical Center's Institutional Review Board.

Authors' Contributions

C.A.P., member of application and abstract form development team, developed initial manuscript and drafts. K.M., a co-inventor and consultant for Hive Networks, Inc, led application development team, critical review, and edits to all manuscript drafts. K.M. also reports research support from Amgen and consulting support from Novartis. J.N., member of application development team, led critical review and edits to manuscript drafts. M.M. led genomic implementation study for which clinical adaptations were needed, critical review, and edits to manuscript drafts. E.H. oversight of systems developed for genomic implementation study and critical review of manuscript drafts.

Publication History

Received: 18 March 2020

Accepted: 15 September 2020

Article published online:
13 November 2020

• References

• 1 Adams DR, Eng CM. Next-generation sequencing to diagnose suspected genetic disorders. N Engl J Med 2018; 379 (14) 1353-1362
• 2 Farnaes L, Hildreth A, Sweeney NM. et al. Rapid whole-genome sequencing decreases infant morbidity and cost of hospitalization. NPJ Genom Med 2018; 3: 10
• 3 O'Daniel JM, McLaughlin HM, Amendola LM. et al. A survey of current practices for genomic sequencing test interpretation and reporting processes in US laboratories. Genet Med 2017; 19 (05) 575-582
• 4 Kalia SS, Adelman K, Bale SJ. et al. Recommendations for reporting of secondary findings in clinical exome and genome sequencing, 2016 update (ACMG SF v2.0): a policy statement of the American College of Medical Genetics and Genomics. Genet Med 2017; 19 (02) 249-255
• 5 Bush LW, Bartoshesky LE, David KL, Wilfond B, Williams JL, Holm IA. ACMG SELI committee. Pediatric clinical exome/genome sequencing and the engagement process: encouraging active conversation with the older child and adolescent: points to consider-a statement of the American College of Medical Genetics and Genomics (ACMG). Genet Med 2018; 20 (07) 692-694
• 6 Masys DR, Jarvik GP, Abernethy NF. et al. Technical desiderata for the integration of genomic data into electronic health records. J Biomed Inform 2012; 45 (03) 419-422
• 7 eMERGE Consortium. Electronic address: [e-mail], eMERGE Consortium. Harmonizing clinical sequencing and interpretation for the eMERGE III network. Am J Hum Genet 2019; 105 (03) 588-605
• 8 Myers MF, Martin LJ, Prows CA. Adolescents' and parents' genomic testing decisions: associations with age, race, and sex. J Adolesc Health 2020; 66 (03) 288-295
• 9 Pervola J, Myers MF, McGowan ML, Prows CA. Giving adolescents a voice: the types of genetic information adolescents choose to learn and why. Genet Med 2019; 21 (04) 965-971
• 10 Raghuram Pillai P, Prows CA, Martin LJ, Myers MF. Decisional conflict among adolescents and parents making decisions about genomic sequencing results. Clin Genet 2020; 97 (02) 312-320
• 11 Hoell C, Wynn J, Rasmussen LV. et al. Participant choices for return of genomic results in the eMERGE Network. Genet Med 2020; DOI: 10.1038/s41436-020-0905-3.
• 12 Bishop CL, Strong KA, Dimmock DP. Choices of incidental findings of individuals undergoing genome wide sequencing, a single center's experience. Clin Genet 2017; 91 (01) 137-140
• 13 Ackerman SL, Koenig BA. Understanding variations in secondary findings reporting practices across U.S. genome sequencing laboratories. AJOB Empir Bioeth 2018; 9 (01) 48-57
• 14 Williams MS, Taylor CO, Walton NA. et al. Genomic information for clinicians in the electronic health record: lessons learned from the clinical genome resource project and the electronic medical records and genomics network. Front Genet 2019; 10: 1059
• 15 Welch BM, Eilbeck K, Del Fiol G, Meyer LJ, Kawamoto K. Technical desiderata for the integration of genomic data with clinical decision support. J Biomed Inform 2014; 51: 3-7
• 16 Suter SM. GINA at 10 years: the battle over 'genetic information' continues in court. J Law Biosci 2019; 5 (03) 495-526