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Leveraging oncology collaborative networks and biomedical informatics data resources to rapidly recruit and enroll rural residents into oncology quality of life clinical trials
Journal article   Open access   Peer reviewed

Leveraging oncology collaborative networks and biomedical informatics data resources to rapidly recruit and enroll rural residents into oncology quality of life clinical trials

Heath Davis, Asher Hoberg, Laura Jacobus, Kenneth Nepple, Aaron Seaman, Jamie Sorensen, George Weiner and Stephanie Gilbertson-White
Journal of clinical and translational science, Vol.8(1), e135
09/23/2024
DOI: 10.1017/cts.2024.576
PMCID: PMC11428118
PMID: 39345703
Appears in  UI Libraries Support Open Access
url
https://doi.org/10.1017/cts.2024.576View
Published (Version of record) Open Access

Abstract

Purpose:This study assesses the feasibility of biomedical informatics resources for efficient recruitment of rural residents with cancer to a clinical trial of a quality-of-life (QOL) mobile app. These resources have the potential to reduce costly, time-consuming, in-person recruitment methods.Methods:A cohort was identified from the electronic health record data repository and cross-referenced with patients who consented to additional research contact. Rural–urban commuting area codes were computed to identify rurality. Potential participants were emailed study details, screening questions, and an e-consent link via REDCap. Consented individuals received baseline questionnaires automatically. A sample minimum of n = 80 [n = 40 care as usual (CAU) n = 40 mobile app intervention] was needed.Results:N = 1298 potential participants (n = 365 CAU; n = 833 intervention) were screened for eligibility. For CAU, 68 consented, 67 completed baseline questionnaires, and 54 completed follow-up questionnaires. For intervention, 100 consented, 97 completed baseline questionnaires, and 58 completed follow-up questionnaires. The CAU/intervention reached 82.5%/122.5% of the enrollment target within 2 days. Recruitment and retention rates were 15.3% and 57.5%, respectively. The mean age was 59.5 ± 13.5 years. The sample was 65% women, 20% racial/ethnic minority, and 35% resided in rural areas.Conclusion:These results demonstrate that biomedical informatics resources can be highly effective in recruiting for cancer QOL research. Precisely identifying individuals likely to meet inclusion criteria who previously indicated interest in research participation expedited recruitment. Participants completed the consent and baseline questionnaires with zero follow-up contacts from the research team. This low-touch, repeatable process may be highly effective for multisite clinical trials research seeking to include rural residents.
 Bioinformatics Clinical Trials Feasibility Studies Informatics Infrastructure Oncology Quality of Life Tumors Urogenital System Cancer therapies Codes Collaboration Consent Data models Electronic medical records Information literacy Intervention Medical records Medical research Participation Patients Rural areas Rural populations UIOWA OA Agreement

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