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Targeting primary care referrals to smoking cessation clinics does not improve quit rates: implementing evidence-based interventions into practice.

ABSTRACT: To evaluate the impact of a locally adapted evidence-based quality improvement (EBQI) approach to implementation of smoking cessation guidelines into routine practice.We used patient questionnaires, practice surveys, and administrative data in Veterans Health Administration (VA) primary care practices across five southwestern states.In a group-randomized trial of 18 VA facilities, matched on size and academic affiliation, we evaluated intervention practices' abilities to implement evidence-based smoking cessation care following structured evidence review, local priority setting, quality improvement plan development, practice facilitation, expert feedback, and monitoring. Control practices received mailed guidelines and VA audit-feedback reports as usual care.To represent the population of primary care-based smokers, we randomly sampled and screened 36,445 patients to identify and enroll eligible smokers at baseline (n=1,941) and follow-up at 12 months (n=1,080). We used computer-assisted telephone interviewing to collect smoking behavior, nicotine dependence, readiness to change, health status, and patient sociodemographics. We used practice surveys to measure structure and process changes, and administrative data to assess population utilization patterns.Intervention practices adopted multifaceted EBQI plans, but had difficulty implementing them, ultimately focusing on smoking cessation clinic referral strategies. While attendance rates increased (p<.0001), we found no intervention effect on smoking cessation.EBQI stimulated practices to increase smoking cessation clinic referrals and try other less evidence-based interventions that did not translate into improved quit rates at a population level.

SUBMITTER: Yano EM

PROVIDER: S-EPMC2653889 | biostudies-literature | 2008 Oct

REPOSITORIES: biostudies-literature

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Targeting primary care referrals to smoking cessation clinics does not improve quit rates: implementing evidence-based interventions into practice.

Yano Elizabeth M EM Rubenstein Lisa V LV Farmer Melissa M MM Chernof Bruce A BA Mittman Brian S BS Lanto Andrew B AB Simon Barbara F BF Lee Martin L ML Sherman Scott E SE

Health services research 20080603 5 Pt 1

<h4>Objective</h4>To evaluate the impact of a locally adapted evidence-based quality improvement (EBQI) approach to implementation of smoking cessation guidelines into routine practice.<h4>Data sources/study setting</h4>We used patient questionnaires, practice surveys, and administrative data in Veterans Health Administration (VA) primary care practices across five southwestern states.<h4>Study design</h4>In a group-randomized trial of 18 VA facilities, matched on size and academic affiliation, ...[more]

PMID: 18522670

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Project description:BACKGROUND AND AIMS:Millions of people world-wide use websites to help them quit smoking, but effectiveness trials have an average 34% follow-up data retention rate and an average 9% quit rate. We compared the quit rates of a website using a new behavioral approach called Acceptance and Commitment Therapy (ACT; WebQuit.org) with the current standard of the National Cancer Institute's (NCI) Smokefree.gov website. DESIGN:A two-arm stratified double-blind individually randomized trial (n = 1319 for WebQuit; n = 1318 for Smokefree.gov) with 12-month follow-up. SETTING:United States. PARTICIPANTS:Adults (n = 2637) who currently smoked at least five cigarettes per day were recruited from March 2014 to August 2015. At baseline, participants were mean [standard deviation (SD)] age 46.2 years (13.4), 79% women and 73% white. INTERVENTIONS:WebQuit.org website (experimental) provided ACT for smoking cessation; Smokefree.gov website (comparison) followed US Clinical Practice Guidelines for smoking cessation. MEASUREMENTS:The primary outcome was self-reported 30-day point prevalence abstinence at 12 months. FINDINGS:The 12-month follow-up data retention rate was 88% (2309 of 2637). The 30-day point prevalence abstinence rates at the 12-month follow-up were 24% (278 of 1141) for WebQuit.org and 26% (305 of 1168) for Smokefree.gov [odds ratio (OR) = 0.91; 95% confidence interval (CI) = 0.76, 1.10; P = 0.334] in the a priori complete case analysis. Abstinence rates were 21% (278 of 1319) for WebQuit.org and 23% (305 of 1318) for Smokefree.gov (OR = 0.89 (0.74, 1.07; P = 0.200) when missing cases were imputed as smokers. The Bayes factor comparing the primary abstinence outcome was 0.17, indicating 'substantial' evidence of no difference between groups. CONCLUSIONS:WebQuit.org and Smokefree.gov had similar 30-day point prevalence abstinence rates at 12 months that were descriptively higher than those of prior published website-delivered interventions and telephone counselor-delivered interventions.

Project description:Tobacco use is still the leading preventable cause of death and morbidity in the U.S. Web-assisted tobacco interventions are an effective but underutilized tool in assisting smokers with quitting. The dental visit is an excellent opportunity to assist smokers in quitting by referring them to these tobacco-cessation online programs.The study purpose was to test two patient referral methods-paper referrals (information prescriptions) versus paper plus e-referrals-to a web-assisted smoking-cessation induction system.RCT that used implementation research methods.A total of 100 community-based dental practices were enrolled and 1814 smokers were referred to the web-assisted tobacco induction system.The study intervention was a proactive e-referral of smokers to a web-assisted tobacco induction system called Decide2Quit.org, and the control group used paper referrals (information prescriptions) to refer smokers to the Decide2Quit.org.The outcome measurements were the referral numbers, Decide2Quit registration numbers, and the smokers' quit rate. Data were collected in 2010-2011 and analyses were completed in 2012.Although total referrals from intervention practices was lower than control, subsequent proportions of registrations among smokers referred to Decide2Quit.org were nearly fourfold higher (adjusted mean percentages: 29.5% vs 7.6%, p<0.01) in intervention compared with control practices. Subsequent rates of cessation among referred smokers were threefold higher (adjusted mean percentages: 3.0% vs 0.8%, p=0.03) in intervention practices as compared with control.Intervention practices using the e-referral system had higher smoker registration numbers and higher quit smoking rates than the control practices. This study finds that e-referrals are effective in getting smokers to the web-assisted smoking-cessation induction system and in assisting with quitting that more than compensates for any additional effort that e-referrals require on the part of the practitioner.DPBRN Hygienists Internet Quality Improvement in Tobacco Cessation (HiQuit); NCT01108432.

Project description:IntroductionMost people who smoke cigarettes are not willing (ie, not ready) to make a quit attempt (QA) at any given time. Unfortunately, interventions intended to increase QAs and the success of QAs are only modestly effective. Identifying processes leading to QAs and quitting success could guide intervention development.Aims and methodsThis is a secondary analysis of a randomized factorial trial of 6 weeks of motivation-phase interventions among primary care patients (N = 517) who were initially unwilling to quit but were willing to reduce their smoking. Using logistic regression, we controlled for treatment condition and tested whether baseline or change in smoking-related constructs after 6 weeks of treatment predicted (1) making an at least 24 h QA between weeks 6 and 26 and (2) quitting success at week 26 (7-day point-prevalence abstinence among those who made a QA). Predictors included cigarettes/day, time to first cigarette, motivation to quit, quitting self-efficacy, anticipated urges to smoke if quit, positive affect, negative affect, and time spent around others who smoke.ResultsIn multivariable models that included all smoking-related constructs, changes in the following variables predicted initiating a QA above and beyond other variables: greater baseline time to first cigarette (odds ratio [OR] = 1.60), increases in time to first cigarette (OR = 1.27), and increases in quitting self-efficacy (OR = 1.14). Increased motivation to quit predicted conversion of a QA into quitting success at 26 weeks (OR = 1.36).ConclusionPredictors of making a QA differed from predictors of quitting success. Predictors of QAs and success could each serve as important treatment targets of motivation-phase interventions.ImplicationsMotivation-phase interventions for people initially unwilling to quit smoking cigarettes may be improved by striving to increase their (1) time to first cigarette and quitting self-efficacy to promote QAs and (2) motivation to quit to promote quit success. Future experimental tests of such interventions are needed to identify causal determinants of QAs and quitting success.

Project description:Considering the extreme shortage of smoking cessation services in China, and the acceptability, feasibility and efficacy of mobile phone-based text message interventions for quitting smoking in other countries, here we propose a study of "the efficacy of mobile phone-based text message interventions ('Happy Quit') for smoking cessation in China". The primary objective of this proposed project is to assess whether a program of widely accessed mobile phone-based text message interventions ('Happy Quit') will be effective at helping people in China who smoke, to quit. Based on the efficacy of previous studies in smoking cessation, we hypothesize that 'Happy Quit' will be an effective, feasible and affordable smoking cessation program in China.In this single-blind, randomized trial, undertaken in China, about 2000 smokers willing to make a quit attempt will be randomly allocated, using an independent telephone randomization system that includes a minimization algorithm balancing for sex (male, female), age (19-34 or >34 years), educational level (? or >12 years), and Fagerstrom score for nicotine addiction (?5, >5), to 'Happy Quit', comprising motivational messages and behavioral-change support, or to a control group that receives text messages unrelated to quitting. Messages will be developed to be suitable for Chinese. A pilot study will be conducted before the intervention to modify the library of messages and interventions. The primary outcome will be self-reported continuous smoking abstinence. A secondary outcome will be point prevalence of abstinence. Abstinence will be assessed at six time points (4, 8, 12, 16, 20 and 24 weeks post-intervention). A third outcome will be reductions in number of cigarettes smoked per day.The results will provide valuable insights into bridging the gap between need and services received for smoking cessation interventions and tobacco use prevention in China. It will also serve as mHealth model for extending the public health significance of other interventions, such as mental health interventions.NCT02693626 (Registration data April 11, 2016).

Project description:Setting a target quit date (TQD) is often an important component in smoking cessation treatment, but ambiguity remains concerning the optimal timing (ie, quitting spontaneously versus delaying to prepare).We examined four questions about the timing of TQDs and smoking outcomes in secondary analyses of The iQUITT Study, a randomized trial of Internet and telephone treatment for cessation: (1) What are the characteristics of TQDs set using an online interactive quit date tool?, (2) What are the characteristics of individuals who use a quit date tool and do they differ from those who do not?, (3) Are there differences in smoker characteristics, treatment utilization, and cessation outcomes based TQD timing?, and (4) Is maintenance of an initial TQD predictive of abstinence or do changes to TQDs lead to cessation?A total of 825 adult current cigarette smokers were randomized to enhanced Internet or enhanced Internet plus telephone counseling. Latency to TQD in days was calculated as the date difference between the initial TQD and enhanced Internet registration; prospective TQD setters were stratified into four latency groups (0, 1-14, 15-28, 29+ days). Baseline variables, website utilization, and 3-month cessation outcomes were examined between prospective TQD groups. Desire and confidence to quit, number of TQDs, and website logins were tested as predictors of 30-day point prevalence abstinence (ppa) at 3 months (responder-only analyses). Classification and regression tree (CART) analysis explored interactions among baseline variables, website utilization, and latency to TQD as predictors of 30-day ppa.There were few baseline differences between individuals who used the quit date tool and those who did not. Prospective TQDs were set as follows: registration day was 17.1% (73/427), 1-14 days was 37.7% (161/427), 15-28 days was 18.5% (79/427), and 29+ days was 26.7% (114/427). Participants with a TQD within 2 weeks had higher baseline self-efficacy scores but did not differ on smoking variables. Individuals whose TQD was the same day as registration had the highest logins, page views, number of TQDs set using the tool, and messages sent to other members. Logistic regression revealed a significant interaction between number of TQDs and website logins for 30-day ppa (P=.005). Among those with high logins, 41.8% (33/79) with 1 TQD were abstinent versus 25.9% (35/135) with 2+TQDs. Logins and self-efficacy predicted 30-day ppa in the CART model.TQD timing did not predict cessation outcomes in standard or exploratory analyses. Self-efficacy and an apparent commitment to an initial TQD were the components most highly related to abstinence but only via interactions with website utilization. Findings highlight the importance of feeling efficacious about handling specific smoking situations and engaging with treatment. Additional research focused on increasing engagement in Web-based cessation studies is needed.ClinicalTrials.gov: NCT00282009; http://clinicaltrials.gov/show/NCT00282009 (Archived by WebCite at http://www.webcitation.org/6Kt7NrXDl).

Project description:BackgroundHealthcare professionals, including nurses, frequently advise people to improve their health by stopping smoking. Such advice may be brief, or part of more intensive interventions.ObjectivesTo determine the effectiveness of nursing-delivered smoking cessation interventions in adults. To establish whether nursing-delivered smoking cessation interventions are more effective than no intervention; are more effective if the intervention is more intensive; differ in effectiveness with health state and setting of the participants; are more effective if they include follow-ups; are more effective if they include aids that demonstrate the pathophysiological effect of smoking.Search methodsWe searched the Cochrane Tobacco Addiction Group Specialized Register and CINAHL in January 2017.Selection criteriaRandomized trials of smoking cessation interventions delivered by nurses or health visitors with follow-up of at least six months.Data collection and analysisTwo review authors extracted data independently. The main outcome measure was abstinence from smoking after at least six months of follow-up. We used the most rigorous definition of abstinence for each trial, and biochemically-validated rates if available. Where statistically and clinically appropriate, we pooled studies using a Mantel-Haenszel fixed-effect model and reported the outcome as a risk ratio (RR) with a 95% confidence interval (CI).Main resultsFifty-eight studies met the inclusion criteria, nine of which are new for this update. Pooling 44 studies (over 20,000 participants) comparing a nursing intervention to a control or to usual care, we found the intervention increased the likelihood of quitting (RR 1.29, 95% CI 1.21 to 1.38); however, statistical heterogeneity was moderate (I2 = 50%) and not explained by subgroup analysis. Because of this, we judged the quality of evidence to be moderate. Despite most studies being at unclear risk of bias in at least one domain, we did not downgrade the quality of evidence further, as restricting the main analysis to only those studies at low risk of bias did not significantly alter the effect estimate. Subgroup analyses found no evidence that high-intensity interventions, interventions with additional follow-up or interventions including aids that demonstrate the pathophysiological effect of smoking are more effective than lower intensity interventions, or interventions without additional follow-up or aids. There was no evidence that the effect of support differed by patient group or across healthcare settings.Authors' conclusionsThere is moderate quality evidence that behavioural support to motivate and sustain smoking cessation delivered by nurses can lead to a modest increase in the number of people who achieve prolonged abstinence. There is insufficient evidence to assess whether more intensive interventions, those incorporating additional follow-up, or those incorporating pathophysiological feedback are more effective than one-off support. There was no evidence that the effect of support differed by patient group or across healthcare settings.

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Targeting primary care referrals to smoking cessation clinics does not improve quit rates: implementing evidence-based interventions into practice.

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Targeting primary care referrals to smoking cessation clinics does not improve quit rates: implementing evidence-based interventions into practice.

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