Sustainability of an Opt-Out Electronic-Health Record-Based Tobacco Treatment Consult Service at a Large Safety-Net Hospital: A 6-Year Analysis.

INTRODUCTION: Our safety-net hospital implemented a hospital-based tobacco treatment intervention in 2016. We previously showed the intervention, an "opt-out" Electronic Health Record (EHR)-based Best Practice Alert (BPA)+ order-set that triggers consultation to an inpatient Tobacco Treatment Consult (TTC) service for all patients who smoke, improves smoking abstinence. We now report on sustainability, 6 years after inception. AIMS AND METHODS: We analyzed data collected between July 2016-June 2022 of patients documented as "currently smoking" in the EHR. Across the 6 years, we used Pearson's correlation analysis to compare Adoption (clinician acceptance of the BPA+ order-set, thus generating consultation to the TTC service); Reach (number of consultations completed by the TTC service); and Effectiveness (receipt of pharmacotherapy orders between patients receiving and not receiving consultations). RESULTS: Among 39 558 adult admissions (July 2016-June 2022) with "currently smoking" status in the EHR for whom the BPA triggered, clinicians accepted the TTC order set on 50.4% (19 932/39 558), though acceptance varied across services (eg, Cardiology [71%] and Obstetrics-Gynecology 12%]). The TTC service consulted on 17% (6779/39 558) of patients due to staffing constraints. Consultations ordered (r = -0.28, p = .59) and completed (r = 0.45, p = .37) remained stable over 6-years. Compared to patients not receiving consultations, patients receiving consultations were more likely to receive pharmacotherapy orders overall (inpatient: 50.8% vs. 35.1%, p < .0001; at discharge: 27.1% vs. 10%, p < .0001) and in each year. CONCLUSIONS: The "opt-out" EHR-based TTC service is sustainable, though many did not receive consultations due to resource constraints. Health care systems should elevate the priority of hospital-based tobacco treatment programs to increase reach to underserved populations. IMPLICATIONS: Our study shows that opt-out approaches that utilize the EHR are a sustainable approach to providing evidence-based tobacco treatment to all hospitalized individuals who smoke, regardless of readiness to stop smoking and clinical condition.

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

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.