Quitline treatment dose predicts cessation outcomes among safety net patients linked with treatment via Ask-Advise-Connect

Conversational Chatbot for Cigarette Smoking Cessation: Report of the User-Centered Design Eleven Step Development Process

BACKGROUND

Conversational chatbots are an emerging digital intervention for smoking cessation. No studies have reported on the entire development process of a cessation chatbot.

OBJECTIVE

To describe the user-centered design development process for a novel and comprehensive quit smoking conversational chatbot called "QuitBot."

METHODS

The four years of formative research for developing QuitBot followed an eleven-step process: (1) specifying a conceptual model, (2) conducting content analysis of existing interventions (63 hours of intervention transcripts), (3) assessing user needs, (4) developing the chat's persona ("personality"), (5) prototyping content and persona, (6) developing full functionality, (7) programming the QuitBot, (8) conducting a diary study, (9) conducting a pilot randomized trial, (10) reviewing results of the trial, and (11) adding a free-form question and answer (QnA) function, based on user feedback from pilot trial results. The process of adding a QnA function itself involved a three-step process: (a) generating QnA pairs, (b) fine tuning Large Language Models (LLMs) on QnA pairs, and (c) evaluating the LLM model outputs.

RESULTS

A quit smoking program spanning 42 days of 2 to 3-minute conversations covering topics ranging from motivations to quit, setting a quit date, choosing FDA-approved cessation medications, coping with triggers, and recovering from lapses/relapses. In a pilot randomized trial with 96% three-month outcome data retention, QuitBot demonstrated high user engagement and promising cessation rates compared to the National Cancer Institute's SmokefreeTXT (SFT) text messaging program-particularly among those who viewed all 42 days of program content: 30-day complete-case, point prevalence abstinence (PPA) rates at three-month follow-up were 63% (39/62) for QuitBot vs. 38% (45/117) for SFT (OR = 2.58; 95% CI: 1.34, 4.99; P =.005). However, Facebook Messenger (FM) intermittently blocked participants' access to QuitBot so we transitioned from FM to a standalone smartphone app as the communication channel. Participants' frustration with QuitBot's inability to answer their open-ended questions lead to us develop a core conversational feature enabling users to ask open-ended questions about quitting cigarette smoking and for the QuitBot to respond with accurate and professional answers. To support this functionality, we developed a library of 11,000 QnA pairs on topics associated with quitting cigarette smoking. Model testing results showed that Microsoft's Azure-based QnA maker effectively handled questions that matched our library of 11,000 QnA pairs. A fine-tuned, contextualized GPT3.5 responds to questions that are not within our library of QnA pairs.

CONCLUSIONS

The development process yielded the first LLM-based quit smoking program delivered as a conversational chatbot. Iterative testing led to significant enhancements, including improvements to the delivery channel. A pivotal addition was the inclusion of a core LLM-supported conversational feature allowing users to ask open-ended questions.

CLINICALTRIAL

ClinicalTrials.gov Identifier, NCT03585231.

A Scoping Review and Meta-analysis of the Use of Remote Biochemical Verification Methods of Smoking Status in Tobacco Research

INTRODUCTION

Increasing digital delivery of smoking cessation interventions has resulted in the need to employ novel strategies for remote biochemical verification.

AIMS AND METHODS

This scoping review and meta-analysis aimed to investigate best practices for remote biochemical verification of smoking status. The scientific literature was searched for studies that reported remotely obtained (not in-person) biochemical confirmation of smoking status (ie, combustible tobacco). A meta-analysis of proportions was conducted to investigate key outcomes, which included rates of returned biological samples and the ratio of biochemically verified to self-reported abstinence rates.

RESULTS

A total of 82 studies were included. The most common samples were expired air (46%) and saliva (40% of studies), the most common biomarkers were carbon monoxide (48%) and cotinine (44%), and the most common verification methods were video confirmation (37%) and mail-in samples for lab analysis (26%). Mean sample return rates determined by random-effects meta-analysis were 70% for smoking cessation intervention studies without contingency management (CM), 77% for CM studies, and 65% for other studies (eg, feasibility and secondary analyses). Among smoking cessation intervention studies without CM, self-reported abstinence rates were 21%, biochemically verified abstinence rates were 10%, and 47% of individuals who self-reported abstinence were also biochemically confirmed as abstinent.

CONCLUSIONS

This scoping review suggests that improvements in sample return rates in remote biochemical verification studies of smoking status are needed. Recommendations for reporting standards are provided that may enhance confidence in the validity of reported abstinence rates in remote studies.

IMPLICATIONS

This scoping review and meta-analysis included studies using remote biochemical verification to determine smoking status. Challenges exist regarding implementation and ensuring high sample return rates. Higher self-reported compared to biochemically verified abstinence rates suggest the possibility that participants in remote studies may be misreporting abstinence or not returning samples for other reasons (eg, participant burden, inconvenience). Remote biochemical confirmation of self-reported smoking abstinence should be included in smoking cessation studies whenever feasible. However, findings should be considered in the context of challenges to sample return rates. Better reporting guidelines for future studies in this area are needed.

Associations in Cigarette Smoking and Health Conditions by Race/Ethnicity Among a Diverse Sample of Patients Receiving Treatment in a Federally Qualified Health Care Setting in Chicago

Purpose

To examine the association of cigarette use and smoking-related health conditions by race/ethnicity among diverse and low-income patients at a federally qualified health center (FQHC).

Methods

Demographics, smoking status, health conditions, death, and health service use were extracted from electronic medical data for patients seen between September 1, 2018, and August 31, 2020 (n=51,670). Smoking categories included everyday/heavy smoker, someday/light smoker, former smoker, or never smoker.

Results

Current and former smoking rates were 20.1% and 15.2%, respectively. Males, Black, White, non-partnered, older, and Medicaid/Medicare patients were more likely to smoke. Compared with never smokers, former and heavy smokers had higher odds for all health conditions except respiratory failure, and light smokers had higher odds of asthma, chronic obstructive pulmonary disease, emphysema, and peripheral vascular disease. All smoking categories had more emergency department visits and hospitalizations than never smokers. The associations between smoking status and health conditions differed by race/ethnicity. White patients who smoked had a greater increase in odds of stroke and other cardiovascular diseases compared with Hispanic and Black patients. Black patients who smoked had a greater increase in odds of emphysema and respiratory failure compared with Hispanic patients. Black and Hispanic patients who smoked had a greater increase in emergency care use compared with White patients.

Conclusion

Smoking was associated with disease burden and emergency care and differed by race/ethnicity.

Health Equity Implications

Resources to document smoking status and offer cessation services should be increased in FQHCs to promote health equity for lower income populations.

Ask-Advise-Connect: Differential Enrollment and Smoking Cessation Outcomes Between Primary Care Patients Who Received Quitline-Delivered Treatment in Spanish vs English

PURPOSE

This study examined differences in Quitline treatment enrollment, engagement, and smoking cessation outcomes among primary care patients preferring Spanish and English using the evidence-based tobacco treatment Ask-Advise-Connect.

METHODS

Ask-Advise-Connect was implemented April 2013 through February 2016 in a large safety-net health system to connect smokers with treatment via a link in the electronic health record. Rates of treatment enrollment, engagement, acceptance of nicotine replacement therapy, and smoking abstinence (self-reported and biochemically confirmed) were compared at 6 months among patients who received treatment in Spanish and English using χ ² tests. Logistic regression examined language and nicotine replacement therapy and their interaction as predictors of abstinence.

RESULTS

The smoking status of 218,915 patients was assessed and recorded in the electronic health record. Smoking prevalence was 8.4% among patients preferring Spanish and 27.0% among those preferring English. Spanish-preferring patients were less likely to enroll in treatment (10.7% vs 12.0%, χ ² = 12.06, P = .001) yet completed more counseling calls when enrolled (median = 2 vs 1, P <.001). Patients who received treatment in Spanish (vs English) were twice as likely to be abstinent at 6 months (self-reported: 25.1% vs 14.5%, odds ratio [OR] = 1.98, 95% CI, 1.62-2.40; biochemically confirmed: 7.6% vs 3.7%, OR = 2.13, 95% CI, 1.52-2.97). Receipt of nicotine replacement therapy increased abstinence for all patients and language did not interact with nicotine replacement therapy to predict abstinence.

CONCLUSIONS

Automated point-of-care approaches such as Ask-Advise-Connect have great potential to reach Spanish-preferring smokers. Those who received tobacco treatment in Spanish (vs English) demonstrated better engagement and cessation outcomes.

An EHR-automated and theory-based population health management intervention for smoking cessation in diverse low-income patients of safety-net health centers: a pilot randomized controlled trial

This study tested the preliminary effectiveness of an electronic health record (EHR)-automated population health management (PHM) intervention for smoking cessation among adult patients of a federally qualified health center in Chicago. Participants (N = 190; 64.7% women, 82.1% African American/Black, 8.4% Hispanic/Latino) were self-identified as smokers, as documented in the EHR, who completed the baseline survey of a longitudinal "needs assessment of health behaviors to strengthen health programs and services." Four weeks later, participants were randomly assigned to the PHM intervention (N = 97) or enhanced usual care (EUC; N = 93). PHM participants were mailed a single-page self-determination theory (SDT)-informed letter that encouraged smoking cessation or reduction as an initial step. The letter also addressed low health literacy and low income. PHM participants also received automated text messages on days 1, 5, 8, 11, and 20 after the mailed letter. Two weeks after mailing, participants were called by the Illinois Tobacco Quitline. EUC participants were e-referred following a usual practice. Participants reached by the quitline were offered behavioral counseling and nicotine replacement therapy. Outcome assessments were conducted at weeks 6, 14, and 28 after the mailed letter. Primary outcomes were treatment engagement, utilization, and self-reported smoking cessation. In the PHM arm, 25.8% of participants engaged in treatment, 21.6% used treatment, and 16.3% were abstinent at 28 weeks. This contrasts with no quitline engagement among EUC participants, and a 6.4% abstinence rate. A PHM approach that can reach all patients who smoke and address unique barriers for low-income individuals may be a critical supplement to clinic-based care.

Impact of a Rheumatology Clinic Protocol on Tobacco Cessation Quit Line Referrals

OBJECTIVE

Smoking increases cardiopulmonary and rheumatic disease risk, yet tobacco cessation intervention is rare in rheumatology clinics. This study aimed to implement a rheumatology staff-driven protocol, Quit Connect, to increase the rate of electronic referrals (e-referrals) to free, state-run tobacco quit lines.

METHODS

We conducted a quasi-experimental cohort study of Quit Connect at 3 rheumatology clinics comparing tobacco quit line referrals from 4 baseline years to referrals during a 6-month intervention period. Nurses and medical assistants were trained to use 2 standardized electronic health record (EHR) prompts to check readiness to quit smoking within 30 days, advise cessation, and connect patients using tobacco quit line e-referral orders. Our objective was to use EHR data to examine the primary outcome of tobacco quit line referrals using pre/post design.

RESULTS

Across 54,090 pre- and post-protocol rheumatology clinic visits, 4,601 were with current smokers. We compared outcomes between 4,078 eligible pre-implementation visits and 523 intervention period visits. Post-implementation, the odds of tobacco quit line referral were 26-fold higher compared to our pre-implementation rate (unadjusted odds ratio [OR] 26 [95% confidence interval (95% CI) 6-106]). Adjusted odds of checking readiness to quit in the next 30 days increased over 100-fold compared to pre-implementation (adjusted OR 132 [95% CI 99-177]). Intervention led to e-referrals for 71% of quit-ready patients in <90 seconds; 24% of referred patients reported a quit attempt.

CONCLUSION

Implementing Quit Connect in rheumatology clinics was feasible and improved referrals to a state-run tobacco quit line. Given the importance of smoking cessation to reduce cardiopulmonary and rheumatic disease risk, future studies should investigate disseminating cessation protocols like Quit Connect that leverage tobacco quit lines.

A Study Protocol for Increasing Access to Smoking Cessation Treatments for Low-Income Minority Smokers

Background: Smoking rates among low-income patients are double those of the general population. Access to health care is an essential social determinant of health. Federally qualified health care centers (FQHC) are government-supported and community-based centers to increase access to health care for non-insured and underinsured patients. However, barriers to implementation impact adherence and sustainability of evidence-based smoking cessation within FQHC settings. To address this implementation barrier, our multi-disciplinary team proposes Mi QUIT CARE (Mile Square QUIT Community-Access-Referral-Expansion) to establish the acceptability, feasibility, and capacity of an FQHC system to deliver an evidence-based and multi-level intervention to increase patient engagement with a state tobacco quitline. Methods: A mixed-method approach, rooted in an implementation science framework of RE-AIM (Reach, Effectiveness, Adoption, Implementation, and Maintenance), will be used in this hybrid effectiveness-implementation design. We aim to evaluate the efficacy of a novel delivery system (patient portal) for increasing access to smoking cessation treatment. In preparation for a future randomized clinical trial of Mi QUIT CARE, we will conduct the following developmental research: (1) Examine the burden of tobacco among patient populations served by our partner FQHC, (2) Evaluate among FQHC patients and health care providers, knowledge, attitudes, barriers, and facilitators related to smoking cessation and our intervention components, (3) Evaluate the use of tailored communication strategies and patient navigation to increase patient portal uptake among patients, and (4) To test the acceptability, feasibility, and capacity of the partner FQHC to deliver Mi QUIT CARE. Discussion: This study provides a model for developing and implementing smoking and other health promotion interventions for low-income patients delivered via patient health portals. If successful, the intervention has important implications for addressing a critical social determinant of cancer and other tobacco-related morbidities. Trial Registration: U.S. National Institutes of Health Clinical Trials, NCT04827420, https://clinicaltrials.gov/ct2/show/NCT04827420.

Characteristics of Patients Engaging in Quitline Counseling After an Electronic Referral

INTRODUCTION

Proactive, electronic referral of primary care patients to quitlines has great potential to provide evidence-based tobacco-cessation assistance to tobacco users. However, the quitline contact rates and engagement of individuals beyond 1 counseling call are poor. This study examines the characteristics of electronically referred patients who engage with the quitline.

METHODS

This cross-sectional study included 2,407 primary care patients who reported using tobacco and accepted an electronic referral to the quitline. Outcomes included contact, enrollment, and receipt of ≥2 counseling sessions from the quitline. All measures were assessed from the electronic health record. The association of patient characteristics and outcomes was evaluated using logistic regression modeling with generalized estimating equation methods. Data were collected in 2016‒2018 and were analyzed in 2020.

RESULTS

Among 2,407 referred patients, 794 (33.0%) were contacted; of those, 571 enrolled (71.9%); and of those, 240 (42.0%) engaged in ≥2 quitline counseling sessions. In multivariable analyses, older adults (aged 50-64 and ≥65 years) were significantly more likely to be contacted (OR=2.32, 95% CI=1.6, 3.4) and to receive ≥2 counseling sessions (OR=2.34, 95% CI=1.2, 4.7) than those aged 18-34 years. Those with both Medicare and Medicaid insurance coverage were more likely than those with Medicaid only to be contacted (OR=1.71, 95% CI=1.4, 2.2), to enroll (OR=1.84, 95% CI=1.2, 2.9), and to receive ≥2 counseling sessions (OR=1.83, 95% CI=1.2, 2.9).

CONCLUSIONS

The current quitline phone-based approach is less likely to engage younger adults and those with Medicaid coverage; however, there is a need to improve quitline engagement across all patients. Identification and testing of alternative engagement approaches are needed.

12-Month Evaluation of an EHR-Supported Staff Role Change for Provision of Tobacco Cessation Care in 8 Primary Care Safety-Net Clinics

SIGNIFICANCE

Guidelines urge primary care practices to routinely provide tobacco cessation care (i.e., assess tobacco use, provide brief cessation advice, and refer to cessation support). This study evaluates the impact of a systems-based strategy to provide tobacco cessation care in eight primary care clinics serving low-income patients.

METHODS

A non-randomized stepped wedge study design was used to implement an intervention consisting of (1) changes to the electronic health record (EHR) referral functionality and (2) expansion of staff roles to provide brief advice to quit; assess readiness to quit; offer a referral to tobacco cessation counseling; and sign the referral order. Outcomes assessed from the EHR include performance of tobacco cessation care tasks, referral contact, and enrollment rates for the quitline (QL) and in-house Freedom from Smoking (FFS) program. Generalized estimating equations (GEE) methods were used to compute odds ratios contrasting the pre-implementation vs. 1-, 3-, 6-, and 12-month post-implementation periods.

RESULTS

Of the 176,061 visits, 26.1% were by identified tobacco users. All indicators significantly increased at each time period evaluated post-implementation. In comparison with the pre-intervention period, assessing smoking status (26.6% vs. 55.7%; OR = 3.7, CI = 3.6-3.9), providing advice (44.8% vs. 88.7%; OR = 7.8, CI = 6.6-9.1), assessing readiness to quit (15.8% vs. 55.0%; OR = 6.2, CI = 5.4-7.0), and acceptance of a referral to tobacco cessation counseling (0.5% vs. 30.9%; OR = 81.0, CI = 11.4-575.8) remained significantly higher 12 months post-intervention. For the QL and FFS, respectively, there were 1223 and 532 referrals; 324 (31.1%) and 103 (24.7%) were contacted; 241 (74.4%) and 72 (69.6%) enrolled; and 195 (80.9%) and 14 (19.4%) received at least one counseling session.

CONCLUSIONS

This system change intervention that includes an EHR-supported role expansion substantially increased the provision of tobacco cessation care and improvements were sustained beyond 1 year. This approach has the potential to greatly increase the number of individuals referred for tobacco cessation counseling.

Quitting the quitline: a qualitative study of patient experience of electronic referrals to quitlines

BACKGROUND

The use of electronic referrals (eReferrals) to state quitlines (QLs) for tobacco-using patients is a promising approach for addressing smoking cessation on a large scale. However, QL contact, enrollment, and completion rates are low. The purpose of this study was to examine the eReferral to QL process from the patient's perspective in order to inform strategies for improving QL engagement.

METHODS

We conducted interviews with 55 patients who agreed to an eReferral at a primary care visit to 1 of 8 safety-net community health centers in Cuyahoga County, Ohio (September 2017-August 2018). Interviews were designed to explore the experiences of three subgroups of patients who subsequently: 1) declined participation in the QL; 2) were unreachable by the QL; or 3) were enrolled in or had completed the QL program. Analysis was guided by a phenomenological approach designed to identify emergent themes.

RESULTS

Reasons for QL program non-completion included changing life circumstances and events making cessation unviable; misunderstandings about the QL; discomfort with telephonic counseling; perceived lack of time for counseling; cell phone barriers; and having already quit smoking. We found that some individuals who were no longer engaged with the QL still desired continued support from the QL.

CONCLUSIONS

Participants intentionally and unintentionally disengage from the QL for a wide variety of reasons, several of which are mediated by low socioeconomic status. Integrating QL care with community-based resources that address these mediators could be a promising strategy.