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Representativeness of Electronic Referral to Smoking Treatment Trials in Adult Primary Care
Nayoung Kim1, Julie Kirsch2, Rosina Millevolte3
1University of Alabama College of Human Environmental Sciences, Department of Health Science, Tuscaloosa, AL, USA.
Introduction:
Some populations are underrepresented in smoking treatment research. Electronic health record (EHR)-enabled referral of patients who smoke, which may enhance the representativeness of clinical trial samples. This study assessed the representativeness of smoking treatment trial electronic referral (e-referral), exclusion, enrollment, and engagement in primary care.
Aims And Methods:
Eighteen adult primary care clinics in two healthcare systems offered patients who smoked e-referral to smoking reduction or cessation treatment trials. Extracted EHR data were analyzed to compare rates of e-referral and enrollment across patient groups defined by sex, age, race, ethnicity, and insurance status. Trial eligibility screening data were analyzed to identify differential exclusion of patient groups by sex, race, or neighborhood disadvantage.
Results:
Overall, 23.3% of eligible patients were e-referred, with elevated e-referral rates among women, African American, Medicaid-eligible, and middle-aged patients. Among e-referred patients, 20.5% were excluded at trial eligibility screening, with exclusions elevated for women, minoritized individuals, and individuals from disadvantaged neighborhoods. Overall, 7.0% of patients who smoked enrolled in a smoking treatment trial, with enrollment rates elevated among women, those over age 44, and, in one health system, African American patients. Most enrollees (>87%) initiated counseling and enrollees completed 52.4-79.9% of counseling sessions, with older, college-educated, and lower-income enrollees attending more sessions.
Conclusions:
Proactive e-referral in primary care may improve the representation of certain groups (eg African American and Medicaid-eligible patients) in smoking treatment trials, but differential exclusion at eligibility screening may reduce sample representativeness. Relaxing nonessential eligibility criteria may enhance the inclusion of minoritized and disadvantaged populations in smoking treatment research.
Implications:
Electronic referral of adult primary care patients who smoke to smoking cessation and reduction trials may enhance referral of high-priority populations (eg African American patients and those eligible for Medicaid) to tobacco treatment trials. Relaxing treatment trial inclusion criteria may enhance representation of minoritized and disadvantaged patients in treatment trials.
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