An Integrated, Scalable, Electronic Video Consent Process to Power Precision Health Research: Large, Population-Based, Cohort Implementation and Scalability Study
- PMID: 34889741
- PMCID: PMC8701720
- DOI: 10.2196/31121
An Integrated, Scalable, Electronic Video Consent Process to Power Precision Health Research: Large, Population-Based, Cohort Implementation and Scalability Study
Abstract
Background: Obtaining explicit consent from patients to use their remnant biological samples and deidentified clinical data for research is essential for advancing precision medicine.
Objective: We aimed to describe the operational implementation and scalability of an electronic universal consent process that was used to power an institutional precision health biobank across a large academic health system.
Methods: The University of California, Los Angeles, implemented the use of innovative electronic consent videos as the primary recruitment tool for precision health research. The consent videos targeted patients aged ≥18 years across ambulatory clinical laboratories, perioperative settings, and hospital settings. Each of these major areas had slightly different workflows and patient populations. Sociodemographic information, comorbidity data, health utilization data (ambulatory visits, emergency room visits, and hospital admissions), and consent decision data were collected.
Results: The consenting approach proved scalable across 22 clinical sites (hospital and ambulatory settings). Over 40,000 participants completed the consent process at a rate of 800 to 1000 patients per week over a 2-year time period. Participants were representative of the adult University of California, Los Angeles, Health population. The opt-in rates in the perioperative (16,500/22,519, 73.3%) and ambulatory clinics (2308/3390, 68.1%) were higher than those in clinical laboratories (7506/14,235, 52.7%; P<.001). Patients with higher medical acuity were more likely to opt in. The multivariate analyses showed that African American (odds ratio [OR] 0.53, 95% CI 0.49-0.58; P<.001), Asian (OR 0.72, 95% CI 0.68-0.77; P<.001), and multiple-race populations (OR 0.73, 95% CI 0.69-0.77; P<.001) were less likely to participate than White individuals.
Conclusions: This is one of the few large-scale, electronic video-based consent implementation programs that reports a 65.5% (26,314/40,144) average overall opt-in rate across a large academic health system. This rate is higher than those previously reported for email (3.6%) and electronic biobank (50%) informed consent rates. This study demonstrates a scalable recruitment approach for population health research.
Keywords: biobanking; clinical data; consent; data collection; eHealth; electronic consent; patient privacy; population health; precision medicine; privacy; recruitment; research; research methods; scalability; validation; video.
©Clara Lajonchere, Arash Naeim, Sarah Dry, Neil Wenger, David Elashoff, Sitaram Vangala, Antonia Petruse, Maryam Ariannejad, Clara Magyar, Liliana Johansen, Gabriela Werre, Maxwell Kroloff, Daniel Geschwind. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 08.12.2021.
Conflict of interest statement
Conflicts of Interest: None declared.
Figures
Similar articles
-
Electronic Video Consent to Power Precision Health Research: A Pilot Cohort Study.JMIR Form Res. 2021 Sep 8;5(9):e29123. doi: 10.2196/29123. JMIR Form Res. 2021. PMID: 34313247 Free PMC article.
-
Educational video while "waiting-to-be-seen" in a cardiology outpatient clinic promotes opt-in self-consent for biobanking of remnant clinical biospecimens: A randomized-controlled trial.J Clin Transl Sci. 2023 Apr 11;7(1):e103. doi: 10.1017/cts.2023.518. eCollection 2023. J Clin Transl Sci. 2023. PMID: 37250987 Free PMC article.
-
Email-Based Recruitment Into the Health eHeart Study: Cohort Analysis of Invited Eligible Patients.J Med Internet Res. 2023 Dec 22;25:e51238. doi: 10.2196/51238. J Med Internet Res. 2023. PMID: 38133910 Free PMC article. Clinical Trial.
-
Opt-In and Opt-Out Consent Procedures for the Reuse of Routinely Recorded Health Data in Scientific Research and Their Consequences for Consent Rate and Consent Bias: Systematic Review.J Med Internet Res. 2023 Feb 28;25:e42131. doi: 10.2196/42131. J Med Internet Res. 2023. PMID: 36853745 Free PMC article.
-
Implementation of Electronic Informed Consent in Biomedical Research and Stakeholders' Perspectives: Systematic Review.J Med Internet Res. 2020 Oct 8;22(10):e19129. doi: 10.2196/19129. J Med Internet Res. 2020. PMID: 33030440 Free PMC article.
Cited by
-
Disease risk and healthcare utilization among ancestrally diverse groups in the Los Angeles region.Nat Med. 2023 Jul;29(7):1845-1856. doi: 10.1038/s41591-023-02425-1. Epub 2023 Jul 18. Nat Med. 2023. PMID: 37464048 Free PMC article.
-
Inclusion bias affects common variant discovery and replication in a health-system linked biobank.medRxiv [Preprint]. 2025 Apr 6:2025.04.04.25325131. doi: 10.1101/2025.04.04.25325131. medRxiv. 2025. PMID: 40236437 Free PMC article. Preprint.
-
The use of large language models to enhance cancer clinical trial educational materials.JNCI Cancer Spectr. 2025 Mar 3;9(2):pkaf021. doi: 10.1093/jncics/pkaf021. JNCI Cancer Spectr. 2025. PMID: 39921887 Free PMC article.
-
Polygenic scores for tobacco use provide insights into systemic health risks in a diverse EHR-linked biobank in Los Angeles.Transl Psychiatry. 2024 Jan 18;14(1):38. doi: 10.1038/s41398-024-02743-z. Transl Psychiatry. 2024. PMID: 38238290 Free PMC article.
-
A large meta-analysis identifies genes associated with anterior uveitis.Nat Commun. 2023 Nov 11;14(1):7300. doi: 10.1038/s41467-023-43036-1. Nat Commun. 2023. PMID: 37949852 Free PMC article.
References
-
- Ginsburg GS, Phillips KA. Precision medicine: From science to value. Health Aff (Millwood) 2018 May;37(5):694–701. doi: 10.1377/hlthaff.2017.1624. http://europepmc.org/abstract/MED/29733705 - DOI - PMC - PubMed
-
- Greely HT. Breaking the stalemate: a prospective regulatory framework for unforseen research uses of human tissue samples and health information. Wake Forest Law Rev. 1999;34(3):737–766. - PubMed
-
- Federal policy for the protection of human subjects ('Common Rule') U.S. Department of Health and Human Services, Office for Human Research Protections. [2020-10-29]. https://www.hhs.gov/ohrp/regulations-and-policy/regulations/common-rule/... .
-
- NIH genomic data sharing policy. National Institutes of Health. [2020-10-29]. https://grants.nih.gov/grants/guide/notice-files/NOT-OD-14-124.html .
Publication types
MeSH terms
Grants and funding
LinkOut - more resources
Full Text Sources