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Effective treatments for smoking cessation exist but are underused. Proactive chronic care approaches may enhance the reach of cessation treatment and reduce the prevalence of smoking in healthcare systems. This pragmatic study evaluated a population-based Comprehensive Tobacco Intervention Program (CTIP) implemented in all (6) adult primary care clinics in a Madison, Wisconsin, USA healthcare cooperative, assessing treatment reach, reach equity, and effectiveness in promoting smoking cessation. CTIP launched in 3 waves of 2 clinics each in a multiple baseline design. Electronic health record (EHR) tools facilitated clinician-delivered pharmacotherapy and counseling; guiding tobacco care managers in phone outreach to all patients who smoke; and prompting multimethod bulk outreach to all patients on a smoking registry using an opt-out approach. EHR data were analyzed to assess CTIP reach and effectiveness among 6894 adult patients between January 2018 and February 2020. Cessation treatment reach increased significantly after CTIP launch in 5 of 6 clinics and was significantly higher when clinics were active vs. inactive in CTIP [Odds Ratio (OR) range = 2.0-3.0]. Rates of converting from current to former smoking status were also higher in active vs. inactive clinics (OR range = 2.2-10.5). Telephone treatment reach was particularly high in historically underserved groups, including African-American, Hispanic, and Medicaid-eligible patients. Implementation of a comprehensive, opt-out, chronic-care program aimed at all patients who smoke was associated with increases in the rates of pharmacotherapy and counseling delivery and quitting smoking. Proactive outreach may help reduce disparities in treatment access.
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Abandono do Hábito de Fumar , Tabagismo , Adulto , Humanos , Tabagismo/terapia , Registros Eletrônicos de Saúde , Abandono do Hábito de Fumar/métodos , Atenção Primária à Saúde , Fumar/epidemiologia , Fumar/terapiaRESUMO
Background: Although people who smoke cigarettes are overrepresented among hospital inpatients, few are connected with smoking cessation treatment during their hospitalization. Training, accountability for medication use, and monitoring of all patients position pharmacists well to deliver cessation interventions to all hospitalized patients who smoke. Methods: A large Midwestern University hospital implemented a pharmacist-led smoking cessation intervention. A delegation protocol for hospital pharmacy inpatients who smoked cigarettes gave hospital pharmacists the authority to order nicotine replacement therapy (NRT) during hospitalization and upon discharge, and for referral to the Wisconsin Tobacco Quit Line (WTQL) at discharge. Eligible patients received the smoking cessation intervention unless they actively refused (ie, "opt-out"). The program was pilot tested in phases, with pharmacist feedback between phases, and then implemented hospital-wide. Interviews, surveys, and informal mechanisms identified ways to improve implementation and workflows. Results: Feedback from pharmacists led to changes that improved workflow, training and patient education materials, and enhanced adoption and reach. Refining implementation strategies across pilot phases increased the percentage of eligible smokers offered pharmacist-delivered cessation support from 37% to 76%, prescribed NRT from 2% to 44%, and referred to the WTQL from 3% to 32%. Conclusion: Hospitalizations provide an ideal opportunity for patients to make a tobacco quit attempt, and pharmacists can capitalize on this opportunity by integrating smoking cessation treatment into existing inpatient medication reconciliation workflows. Pharmacist-led implementation strategies developed in this study may be applicable in other inpatient settings.
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PURPOSE: Hospitalization affords an opportunity to reduce smoking, but fewer than half of patients who smoke receive evidence-based cessation treatment during inpatient stays. This study evaluated a pharmacist-led, electronic health record (EHR)-facilitated opt-out smoking cessation intervention designed to address this need. METHODS: Analyses of EHR records for adult patients who smoked in the past 30 days admitted to an academic medical center in the upper Midwest were conducted using the Reach Effectiveness Adoption Implementation Maintenance (RE-AIM) framework. The reach of a pharmacist-led, EHR-facilitated protocol for smoking cessation treatment was assessed by comparing patients' receipt of nicotine replacement therapy (NRT) and tobacco quitline referral before and after implementation. χ2 tests, t tests, and multiple logistic regression models were used to compare reach across patient demographic groups to assess treatment disparities and the representativeness of reach. Adoption of the program by hospital services was also assessed. RESULTS: Of the 70 hospital services invited to implement the program, 88.6% adopted it and 78.6% had eligible admissions. Treatment reach increased as rates of delivering NRT rose from 43.6% of eligible patients before implementation to 50.4% after implementation (P < 0.0001) and quitline referral rates rose from 0.9% to 11.9% (P < 0.0001). Representativeness of reach by sex and ethnicity improved after implementation, although disparities by race and age persisted after adjustment for demographics, insurance, and primary diagnosis. Pharmacists addressed tobacco use for eligible patients in 62.5% of cases after protocol implementation. CONCLUSION: Smoking cessation treatment reach and representativeness of reach improved after implementation of a proactive, pharmacist-led, EHR-facilitated opt-out smoking cessation treatment protocol in adult inpatient services.
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Abandono do Hábito de Fumar , Adulto , Hospitais , Humanos , Pacientes Internados , Farmacêuticos , Abandono do Hábito de Fumar/métodos , Dispositivos para o Abandono do Uso de TabacoRESUMO
BACKGROUND: Health system change can increase the reach of evidence-based smoking cessation treatments. Proactive electronic health record (EHR)-enabled, closed-loop referral ("eReferral") to state tobacco quitlines increases the rates at which patients who smoke accept cessation treatment. Implementing such system change poses many challenges, however, and adaptations to system contexts are often required, but are understudied. This retrospective case study identified adaptations to eReferral EHR tools and implementation strategies in two healthcare systems. METHODS: In a large clustered randomized controlled trial (C-RCT; NCT02735382) conducted in 2016-2017, 11 primary care clinics in two healthcare systems implemented quitline eReferral, starting with 1 pilot clinic per system followed by 2 phases of implementation (an experimental phase in 5-6 test clinics per system and then a system-wide dissemination phase in both systems). Adaptations were informed by stakeholder input from live trainings, follow-up calls and meetings in the first month after eReferral launch, emails, direct observation by researchers, and clinic staff survey responses. Retrospective, descriptive analysis characterized implementation strategy modifications and adaptations using the Framework for Reporting Adaptations and Modifications to Evidence-based Implementation Strategies (FRAME-IS). A pre- and post-implementation survey assessed staff ratings of eReferral acceptability and implementation barriers and facilitators. FINDINGS: Major modifications to closed-loop eReferral implementation strategies included aligning the eReferral initiative with other high-priority health system objectives, modifying eReferral user interfaces and training in their use, modifying eReferral workflows and associated training, and maintaining and enhancing interoperability and clinician feedback functions. The two health systems both used Epic EHRs but used different approaches to interfacing with the quitline vendor and integrating eReferral into clinician workflows. Both health systems engaged in iterative refinement of the EHR alert prompting eReferral, the eReferral order, trainings, and workflows. Staff survey comments suggested moderate acceptability of eReferral processes and identified possible targets for future modifications in eReferral, including reducing clinician burden related to EHR documentation and addressing clinicians' negative beliefs about patient receptivity to cessation treatment. CONCLUSIONS: System-wide implementation of tobacco quitline eReferral in primary care outpatient clinics is feasible but requires extensive coordination across stakeholders, tailoring to local health system EHR configurations, and sensitivity to system- and clinic-specific workflows. TRIAL REGISTRATION: www. CLINICALTRIALS: gov, NCT02735382 . Registered on 12 August 2016.
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INTRODUCTION: Patients who use tobacco are too rarely connected with tobacco use treatment during healthcare visits. Electronic health record enhancements may increase such referrals in primary care settings. This project used the Reach, Effectiveness, Adoption, Implementation, and Maintenance framework to assess the implementation of a healthcare system change carried out in an externally valid manner (executed by the healthcare system). METHODS: The healthcare system used their standard, computer-based training approach to implement the electronic health record and clinic workflow changes for electronic referral in 30 primary care clinics that previously used faxed quitline referral. Electronic health record data captured rates of assessment of readiness to quit and quitline referral 4 months before implementation and 8 months (May-December 2017) after implementation. Data, analyzed from October 2018 to June 2019, also reflected intervention reach, adoption, and maintenance. RESULTS: For reach and effectiveness, from before to after implementation for electronic referral, among adult patients who smoked, assessment of readiness to quit increased from 24.8% (2,126 of 8,569) to 93.2% (11,163 of 11,977), quitline referrals increased from 1.7% (143 of 8,569) to 11.3% (1,351 of 11,977), and 3.6% were connected with the quitline after implementation. For representativeness of reach, electronic referral rates were especially high for women, African Americans, and Medicaid patients. For adoption, 52.6% of staff who roomed at least 1 patient who smoked referred to the quitline. For maintenance, electronic referral rates fell by approximately 60% over 8 months but remained higher than pre-implementation rates. CONCLUSIONS: Real-world implementation of an electronic health record-based electronic referral system markedly increased readiness to quit assessment and quitline referral rates in primary care patients. Future research should focus on implementation methods that produce more consistent implementation and better maintenance of electronic referral.
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Encaminhamento e Consulta , Abandono do Hábito de Fumar , Abandono do Uso de Tabaco , Adulto , Idoso , Eletrônica , Feminino , Linhas Diretas , Humanos , Masculino , Medicare , Atenção Primária à Saúde , Estados UnidosRESUMO
Too few smokers who present for outpatient healthcare receive evidence-based interventions to stop smoking. Referral to nationally available smoking cessation support may enhance tobacco intervention reach during healthcare visits. This study evaluated the feasibility of outpatient electronic health record (EHR)-enabled, closed-loop referral (eReferral) to SmokefreeTXT, a National Cancer Institute text message smoking cessation program. SmokefreeTXT eReferral for adult patients who smoke was implemented in a family medicine clinic and an allergy and asthma clinic in an integrated Midwestern healthcare system. Interoperable, HIPAA-compliant eReferral returned referral outcomes to the EHR. In Phase 1 of implementation, clinicians were responsible for eReferral; in Phase 2 this responsibility shifted to Medical Assistants and/or nurses. EHR data were extracted to compute eReferral rates among adult smokers and compare demographics among those eReferred versus not referred. SmokefreeTXT data were used to compute SmokefreeTXT enrollment rates among those eReferred. Descriptive analyses of clinic staff surveys assessed implementation context and staff attitudes toward and adaptations of eReferral processes. During clinician implementation, 43 of 299 adult smokers (14.4%) were eReferred. During medical assistant (MA) implementation, 36 of 401 adult smokers (9.0%) were eReferred. Overall, among those eReferred, 25.7% completed SmokefreeTXT enrollment (3.1% of patients eligible for eReferral). Staff survey responses indicated that eReferral was efficient and easy. eReferral rates and relevant attitudes varied meaningfully by clinic. Thus, interoperable eReferral via outpatient EHR to SmokefreeTXT is feasible and acceptable to clinic staff and enrolls roughly 3.0% of smokers. Clinic context and implementation approach may influence reach.
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Abandono do Hábito de Fumar , Adulto , Assistência Ambulatorial , Eletrônica , Humanos , Cooperação do Paciente , Encaminhamento e ConsultaRESUMO
OBJECTIVE: The study sought to determine whether interoperable, electronic health record-based referral (eReferral) produces higher rates of referral and connection to a state tobacco quitline than does fax-based referral, thus addressing low rates of smoking treatment delivery in health care. MATERIALS AND METHODS: Twenty-three primary care clinics from 2 healthcare systems (A and B) in Wisconsin were randomized, unblinded, over 2016-2017, to 2 smoking treatment referral methods: paper-based fax-to-quit (system A =6, system B = 6) or electronic (eReferral; system A = 5, system B = 6). Both methods referred adult patients who smoked to the Wisconsin Tobacco Quitline. A total of 14 636 smokers were seen in the 2 systems (system A: 54.5% women, mean age 48.2 years; system B: 53.8% women, mean age 50.2 years). RESULTS: Clinics with eReferral, vs fax-to-quit, referred a higher percentage of adult smokers to the quitline: system A clinic referral rate = 17.9% (95% confidence interval [CI], 17.2%-18.5%) vs 3.8% (95% CI, 3.5%-4.2%) (P < .001); system B clinic referral rate = 18.9% (95% CI, 18.3%-19.6%) vs 5.2% (95% CI, 4.9%-5.6%) (P < .001). Average rates of quitline connection were higher in eReferral than F2Q clinics: system A = 5.4% (95% CI, 5.0%-5.8%) vs 1.3% (95% CI, 1.1%-1.5%) (P < .001); system B = 5.3% (95% CI, 5.0%-5.7%) vs 2.0% (95% CI, 1.8%-2.2%) (P < .001). DISCUSSION: Electronic health record-based eReferral provided an effective, closed-loop, interoperable means of referring patients who smoke to telephone quitline services, producing referral rates 3-4 times higher than the current standard of care (fax referral), including especially high rates of referral of underserved individuals. CONCLUSIONS: eReferral may help address the challenge of providing smokers with treatment for tobacco use during busy primary care visits.ClinicalTrials.gov; No. NCT02735382.
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Registros Eletrônicos de Saúde , Atenção Primária à Saúde , Encaminhamento e Consulta/organização & administração , Abandono do Hábito de Fumar , Adulto , Instituições de Assistência Ambulatorial , Feminino , Humanos , Masculino , Medicaid , Pessoa de Meia-Idade , Encaminhamento e Consulta/estatística & dados numéricos , Fumar/epidemiologia , Abandono do Hábito de Fumar/métodos , Estados Unidos , Fluxo de TrabalhoRESUMO
Few smokers receive evidence-based tobacco treatment during healthcare visits. Electronic health records (EHRs) present an opportunity to efficiently identify and refer smokers to state tobacco quitlines. The purpose of this case study is to develop and evaluate a secure, closed-loop EHR referral system linking patients visiting healthcare clinics with a state tobacco quitline. A regional health system, EHR vendor, tobacco cessation telephone quitline vendor, and university research center collaborated to modify a health system's EHR to create an eReferral system. Modifications included the following: clinic workflow adjustments, EHR prompts, and return of treatment delivery information from the quitline to the patient's EHR. A markedly higher percentage of adult tobacco users were referred to the quitline using eReferral than using the previous paper fax referral (14 vs. 0.3 %). The eReferral system increased the referral of tobacco users to quitline treatment. This case study suggests the feasibility and effectiveness of a secure, closed-loop EHR-based eReferral system.