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San Jose Health IT Summit
2017-04-13 - 2017-04-14    
All Day
About Health IT Summits U.S. healthcare is at an inflection point right now, as policy mandates and internal healthcare system reform begin to take hold, [...]
Annual IHI Summit
2017-04-20 - 2017-04-22    
All Day
The Office Practice & Community Improvement Conference ​​​​​​The 18th Annual Summit on Improving Patient Care in the Office Practice and the Community taking place April 20–22, 2017, in Orlando, FL, brings together 1,000 health improvers from around the globe, in [...]
Stanford Medicine X | ED
2017-04-22 - 2017-04-23    
All Day
Stanford Medicine X | ED is a conference on the future of medical education at the intersections of people, technology and design. As an Everyone [...]
2017 Health Datapalooza
2017-04-27 - 2017-04-28    
All Day
Health Datapalooza brings together a diverse audience of over 1,600 people from the public and private sectors to learn how health and health care can [...]
The 14th Annual World Health Care Congress
2017-04-30 - 2017-05-03    
All Day
The 14th Annual World Health Care Congress April 30 - May 3, 2017 • Washington, DC • The Marriott Wardman Park Hotel Connecting and Preparing [...]
Events on 2017-04-13
San Jose Health IT Summit
13 Apr 17
San Jose
Events on 2017-04-20
Annual IHI Summit
20 Apr 17
Orlando
Events on 2017-04-22
Events on 2017-04-27
2017 Health Datapalooza
27 Apr 17
Washington, D.C
Events on 2017-04-30
Research Papers

Reactions to EHR-Based Clinical Study Invitations

ehr-patient-records - EMR industry

Introduction
Recruiting representative populations for clinical trials remains a persistent challenge.¹ ² Electronic health records (EHRs) and patient portals offer new opportunities to streamline recruitment by securely messaging potentially eligible participants. However, the demographic factors influencing engagement with this digital recruitment approach are not yet well understood.

Methods
Since 2022, the University of Texas Southwestern (UTSW), a quaternary academic medical center, has leveraged its EHR system—MyChart (Epic Systems Co)—to identify and invite potential research participants. Adult patients with an active MyChart account (614,110 individuals, representing 65% of the active patient population) are eligible to receive research invitations unless they have opted out. The centralized recruitment office sends bulk messages to these patients, informing them about the study, noting their potential eligibility, and prompting them to click a button if they wish to be contacted by the study team. Notifications via email or phone alert patients to new research opportunities available in their portal.

This quality improvement study examined characteristics of individuals who viewed recruitment messages, expressed interest, and ultimately enrolled in clinical studies that used portal-based messaging between January 2022 and December 2024. Enrollment data were sourced from the institutional clinical trial management system, excluding three studies with unavailable data. The analysis relied on de-identified data collected as part of routine recruitment quality monitoring and was deemed not to involve human subjects research by the UTSW Institutional Review Board.

To assess associations between demographic factors and recruitment outcomes, participant-level multivariable mixed-effects logistic regression models were used. Variables included age, sex, race, and ethnicity (as recorded in the EHR), and a random effect was included to account for variability across studies. Statistical significance was defined as a two-sided P value < 0.05. Results Across 23 clinical studies, recruitment messages were sent to 84,062 individuals (43.0% female [36,109]; 3.7% Asian [3,068], 19.0% Black [15,947], 9.5% Hispanic [7,990], and 62.6% White [52,640]; median age 62.5 years [IQR, 55.5–70.6]). Overall, 29,231 individuals (34.8%) viewed the recruitment message. Of those, 6,237 (21.3%) expressed interest in participation, representing 7.4% of all individuals who were sent a message. For studies with available enrollment data, 1,213 participants were ultimately enrolled—equating to 19.7% of those who expressed interest (1,213 of 6,168) and 1.2% of the total individuals initially contacted (1,213 of 82,066). Significant differences in message view rates, interest in participation, and enrollment were observed across sex, age, race, and ethnicity (Figure). In multivariable analyses:

  • Lower odds of viewing the message were associated with:

    • Male sex
    • Younger age
    • Hispanic ethnicity
    • Black race
    • Asian race
  • Lower odds of expressing interest, among those who viewed the message, were associated with:

    • Asian race
    • Older age

    Note: Black race and Hispanic ethnicity were not significantly associated with interest at this stage.

  • Lower odds of enrollment, among those who expressed interest, were associated with:

    • Male sex
    • Black race

When considering the entire recruitment funnel (from message receipt to enrollment), male sex, Hispanic ethnicity, and Black race were each associated with reduced odds of eventual enrollment.