BackgroundSmokers usually abstain from tobacco while hospitalized but relapse after discharge. Inpatient interventions may encourage sustained quitting. We previously demonstrated that a decision support tool embedded in an electronic health record (EHR) improved physicians’ treatment of hospitalized smokers. This report describes the effect on quit rates of this decision support tool and order set for hospitalized smokers.MethodsIn a single hospital system, 254 physicians were randomized 1:1 to receive a decision support tool and order set, embedded in the EHR. When an adult patient was admitted to a medical service, an electronic alert appeared if current smoking was recorded in the EHR. For physicians receiving the intervention, the alert linked to an order set for tobacco treatment medications and electronic referral to the state tobacco quitline. Additionally, “Tobacco Use Disorder” was added to the patient’s problem list, and a secure message was sent to the patient’s primary care provider (PCP). In the control arm, no alert appeared. Patients were contacted by phone at 1, 6, and 12 months; those reporting tobacco abstinence at 12 months were asked to return to measure exhaled carbon monoxide. Generalized estimating equations were used to model the data.ResultsFrom 2013 to 2016, the alert fired for 10,939 patients (5391 intervention, 5548 control). Compared to control physicians, intervention physicians were more likely to order tobacco treatment medication, populate the problem list with tobacco use disorder, refer to the quitline, and notify the patient’s PCP. In a subset of 1044 patients recruited for intensive follow-up, one-year quit rates for intervention and control patients were, respectively, 11.5% and 11.6%, (p = 0.94), after controlling for age, sex, race, ethnicity, and insurance. Similarly, there were no differences in 1- and 6-month quit rates.ConclusionsAlthough we were able to improve processes of care, long-term tobacco quit rates were unchanged. This likely reflects, in part, the need for sustained quitting interventions, and higher-than-expected quit rates in controls. Future enhancements should improve prescription of medications for smoking cessation at discharge, engagement of primary care providers, and perhaps direct engagement of patients in a more longitudinal approach.Trial registrationClinicalTrials.gov, NCT01691105. Registered on September 12, 2012

Background Tobacco dependence remains the leading preventable cause of death in the developed world. Smokers are disproportionately from lower socioeconomic groups, and may use the hospital emergency department (ED) as an important source of care. A recent clinical trial demonstrated the efficacy of a multicomponent intervention to help smokers quit, but the independent contributions of those components is unknown. Methods This is a full-factorial (16-arm) randomized trial in a busy hospital ED of 4 tobacco dependence interventions: brief motivational interviewing, nicotine replacement therapy, referral to a telephone quitline, and a texting program. The trial utilizes the Multiphase Optimization Strategy (MOST) and a novel mixed methods analytic design to assess clinical efficacy, cost effectiveness, and qualitative participant feedback. The primary endpoint is tobacco abstinence at 3 months, verified by participants’ exhaled carbon monoxide. Results Study enrollment began in February 2017. As of April 2017, 52 of 1056 planned participants (4.9%) were enrolled. Telephone-based semi-structured participant interviews and in-person biochemical verification of smoking abstinence are completed at the 3-month follow-up. Efficacy and cost effectiveness analyses will be conducted after follow-up is completed. Discussion The goal of this study is to identify a clinically efficacious, cost-effective intervention package for the initial treatment of tobacco dependence in ED patients. The efficacy of this combination can then be tested in a subsequent confirmatory trial. Our approach incorporates qualitative feedback from study participants in evaluating which intervention components will be tested in the future trial.

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The major themes identified included the program being a valued source of external support that provided useful strategies to reduce tobacco use. Subjects were satisfied with the frequency, timing, and number of texts. Texting was perceived as feasible, acceptable, and helpful in smokers' attempts to abstain from tobacco. Suggestions to improve the program primarily concerned increasing customizable options and using simple, declarative sentences.

Background: While stakeholder mapping is common in public policy, social sciences, and business management, this tool has not often been used in healthcare settings. We developed a new method of healthcare stakeholder mapping, which we call Contextual and Organizational Support Mapping of Stakeholders (COSMOS), to identify and assess key stakeholders in an implementation project. Stakeholder mapping allows the implementation team to assess and visually display all relevant stakeholders, their support for the project, and their ability to facilitate-or hinder-project implementation. Methods: The COSMOS model was developed to visualize the stakeholders involved in a hospital-based study conducted from 2013-2016. In this study, a new screen prompt and order set were embedded in the electronic health record to facilitate the identification and treatment of adult smokers admitted to the hospital. Physicians were the unit of randomization; physician behavior and tobacco quit rates among patients were followed for 1 year. Qualitative interviews with hospital administration, physicians, and information technology (IT) personnel (n= 24) were conducted to identify the components and characteristics of the COSMOS. Results: The COSMOS consists of an organizational chart identifying all key stakeholders, with manipulation of colors and borders of the component boxes to indicate stakeholder support for the implementation project, and degree of criticality to its success. The COSMOS visualization informed the team's subsequent work by identifying potential impediments that might require additional attention to garner and maintain support throughout the project. In addition, the approach has proved to be a useful tool to explain these concepts to trainees in implementation science. Conclusion: The COSMOS schematic provides a visually rich means of identifying stakeholders, understanding their relationships to each other, displaying their level of support for the proposed implementation, and noting their criticality to the effort. The COSMOS can support researchers, project teams, administrators, and others engaged with implementation science-related work in healthcare, as well as other fields such as education, government, and industry.