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. 2024 Sep 23;8(1):e135.
doi: 10.1017/cts.2024.576. eCollection 2024.

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

Heath A Davis  1   2 , Asher A Hoberg  1   2 , Laura S Jacobus  1   3 , Kenneth Nepple  4   5 , Aaron T Seaman  6   5 , Jamie Sorensen  7 , George J Weiner  6   5 , Stephanie Gilbertson-White  6   8   5
Affiliations

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

Heath A Davis et al. J Clin Transl Sci. .

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.

Keywords: Cancer; informatics tools; rural health; subject recruitment; supportive oncology.

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Conflict of interest statement

G.J.W. is chairman of the ORIEN Steering Committee. G.J.W. and ORIEN were not involved in developing the research question, determining the research methodology, or conducting the analyses. ORIEN did not provide financial support for this study. H.A.D., A.A.H., L.S.J., K.N., A.T.S., J.S., and S.G.W. have no competing interests.

Figures

Figure 1.
Figure 1.
Step 1: The workflow used to identify potential participants for recruitment. Step 2: The workflow to contact, enroll, and collect data from potential participants. Enterprise Data Warehouse for Research (EDW4R); Patients Enhancing Research Collaborations at Holden (PERCH); Rural-Urban Commuting Area (RUCA).
Figure 2.
Figure 2.
CONSORT Diagram for both Care As Usual (CAU) and Intervention conditions from identification and screening to completion of follow-up questionnaires.
See this image and copyright information in PMC

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