141st APHA Annual Meeting and Exposition

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An integrated clinical-public health informatics system for smoking cessation: Pragmatic clinical trial in 174 practices


Tuesday, November 5, 2013

Rajani S. Sadasivam, PhD, Department of Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA
Thomas K. Houston, MD, MPH, VA eHealth Quality Enhancement Research Initiative, Bedford VAMC, Bedford, MA
Midge N. Ray, RN, MSN, Department of Health Services Administration, University of Alabama at Birmingham, Birmingham, AL
Thomas English, PhD, Department of Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA
Arlene Ash, PhD, Department of Quantitative Health Sciences, UMass Medical School, Worcester, MA
Hua Feng, MS, Bedford VAMC, Bedford, MA, USA, Bedford, MA
Daniel Ford, MD, Departments of Epidemiology and Health Policy and Management, John Hopkins, BALTIMORE
Jeroan J. Allison, MD, MSc, Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA
Background: Increasing evidence supports web-assisted tobacco interventions, but few smokers take advantage of these tools. Objective: We evaluated an integrated clinical-public health informatics system where primary care providers “e-referred” patients to Decide2Quit.org, a web-assisted tobacco intervention. Methods: Practices (Internal Medicine and Family Practice) were randomized to one of two referral methods: 1) a paper brochure or 2) a point-of-care e-referral completed by entering smoker's email into the ReferASmoker.org web-based e-referral system. Smokers from e-referral practices received automated email links to Decide2Quit.org. All smokers who registered with Decide2Quit.org received access to interactive quit smoking calculators and decision tools. Using a within-practice fractional factorial design, smokers were further randomized to three conditions: (A), receiving only the calculators and tools above, or (B) “A” plus motivational emails tailored to their readiness to quit, or (C) “B” plus asynchronous communication with tobacco treatment specialist. At the practice-level, we evaluated number of referrals and subsequent smoker registrations. At the smoker-level, we compared self-reported smoking cessation at six months. Results: The 174 practices referred 4380 smokers to Decide2Quit.org, with a per-practice mean of 26.7(95% CI=21.0-32.3) among “brochure” practices, compared with 21.9 (range: 17.1-26.6) per e-referral practice (p = 0.3). The e-referral practices had a higher mean number of smokers registrations 6.7 (4.8-8.5) compared with 2.7 (2.0-3.4) in ”brochure” practices, yielding a statistically significant Incident Rate Ratio (IRR) of 2.5 (95% CI 1.8-3.5). At the smoker-level, the tools only (A) condition had a self-reported cessation rate of 17%, and the (B) condition was higher at 26%, as was the (C) condition 25%. Six-month cessation in the two groups that received motivational email messages (B and C) combined was significantly higher than the tools only (A) condition (Odds Ratio 1.6 (95% CI 1.02-2.8) p = 0.38). Conclusion: Clinical practices that used e-referrals had higher rates (more than double) of smokers using Decide2Quit.org, and augmented Decide2Quit.org tools increased patient quit rates.

Learning Areas:

Communication and informatics
Implementation of health education strategies, interventions and programs

Learning Objectives:
Demonstrate that electronic referrals by clinical practices double participation in a public health intervention than simply handing paper brochures. Demonstrate that sending motivation tailored emails to smokers improves quit rates

Keyword(s): Tobacco Control

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: A Computer Engineer, I have worked over the last 8 years with health services researchers to evaluate e-health systems for healthcare providers and patients, including the NCI funded Decide2Quit.org web-assisted tobacco intervention. I am currently the PI of an NCI R21 that is testing a suite of electronic chain referral approaches to test whether peer referrals will increase access to patient interventions
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.

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