Efficacy of Digital Outreach Strategies for Collecting Smoking Data: Pragmatic Randomized Trial

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Background Tobacco smoking is an important risk factor for disease, but inaccurate smoking history data in the electronic medical record (EMR) limits the reach of lung cancer screening (LCS) and tobacco cessation interventions. Patient-generated health data is a novel approach to documenting smoking history; however, the comparative effectiveness of different approaches is unclear. Objective We designed a quality improvement intervention to evaluate the effectiveness of portal questionnaires compared to SMS text message–based surveys, to compare message frames, and to evaluate the completeness of patient-generated smoking histories. Methods We randomly assigned patients aged between 50 and 80 years with a history of tobacco use who identified English as a preferred language and have never undergone LCS to receive an EMR portal questionnaire or a text survey. The portal questionnaire used a “helpfulness” message, while the text survey tested frame types informed by behavior economics (“gain,” “loss,” and “helpfulness”) and nudge messaging. The primary outcome was the response rate for each modality and framing type. Completeness and consistency with documented structured smoking data were also evaluated. Results Participants were more likely to respond to the text survey (191/1000, 19.1%) compared to the portal questionnaire (35/504, 6.9%). Across all text survey rounds, patients were less responsive to the “helpfulness” frame compared with the “gain” frame (odds ratio [OR] 0.29, 95% CI 0.09-0.91; P<.05) and “loss” frame (OR 0.32, 95% CI 11.8-99.4; P<.05). Compared to the structured data in the EMR, the patient-generated data were significantly more likely to be complete enough to determine LCS eligibility both compared to the portal questionnaire (OR 34.2, 95% CI 3.8-11.1; P<.05) and to the text survey (OR 6.8, 95% CI 3.8-11.1; P<.05). Conclusions We found that an approach using patient-generated data is a feasible way to engage patients and collect complete smoking histories. Patients are likely to respond to a text survey using “gain” or “loss” framing to report detailed smoking histories. Optimizing an SMS text message approach to collect medical information has implications for preventative and follow-up clinical care beyond smoking histories, LCS, and smoking cessation therapy.

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