Leveraging Implementation Science in the Treatment of Tobacco Use Disorder.

The tobacco use disorder field has an armamentarium of approaches to help people quit smoking: medication-based treatment for tobacco use, digital therapeutics for just-intime behavioral interventions, genetic and metabolic biomarkers to guide tobacco treatment, to name a few. Whether the treatment approach is old or new, an underlying truth remains: the benefit is only as great as the extent to which these treatment approaches reach individuals who need them most and prove effective and feasible to implement in real-world settings. Further, certain treatments tend to be used more robustly in practice, namely, those that address a great need yet are low in cost, burden, and risk of clinical harms. This is where implementation science comes in, providing guidance on how best to get effective treatments adopted and used in clinical and community settings. Implementation science holds the keys to the uptake and routine use of evidence-based treatments and should be more fully leveraged in the tobacco use disorder field. At the same time, disruptive technologies in treatment are breaking new ground, pushing the field of implementation science to build a bigger "toolbox" of ways to improve access and quality of treatment in an ever-evolving landscape. In this paper, we underscore this synergy between tobacco treatment and implementation science. We spotlight emerging trends in tobacco use, effective and emerging treatment approaches for tobacco use, and ways that implementation science intersects with the current and evolving landscape of tobacco use and substance use disorder more broadly.

Increased Reach and Effectiveness With a Low-Burden Point-of-Care Tobacco Treatment Program in Cancer Clinics.

BACKGROUND: Tobacco cessation after a cancer diagnosis can extend patient survival by improving outcomes for primary cancer and preventing secondary cancers. However, smoking is often unaddressed in cancer care, highlighting the need for strategies to increase treatment reach and cessation. This study examined a low-burden, point-of-care tobacco treatment program (ELEVATE) featuring an electronic health record-enabled smoking module and decision support tools to increase the reach and effectiveness of evidence-based smoking cessation treatment. METHODS: This study included adult outpatient tobacco smokers (n=13,651) in medical oncology, internal medicine, and surgical oncology clinics from a large midwestern healthcare system. We examined reach and effectiveness of ELEVATE with 2 comparisons: (1) preimplementation versus postimplementation of ELEVATE and (2) ELEVATE versus usual care. Data were evaluated during 2 time periods: preimplementation (January through May 2018) and postimplementation (June through December 2018), with smoking cessation assessed at the last follow-up outpatient encounter during the 6 months after these periods. RESULTS: The proportion of current tobacco smokers receiving cessation treatment increased from pre-ELEVATE to post-ELEVATE (1.6%-27.9%; difference, 26.3%; relative risk, 16.9 [95% CI, 9.8-29.2]; P<.001). Compared with 27.9% treatment reach with ELEVATE in the postimplementation time period, reach within usual care clinics ranged from 11.8% to 12.0% during this same period. The proportion of tobacco smokers who subsequently achieved cessation increased significantly from pre-ELEVATE to post-ELEVATE (12.0% vs 17.2%; difference, 5.2%; relative risk, 1.3 [95% CI, 1.1-1.5]; P=.002). Compared with 17.2% smoking cessation with ELEVATE in the postimplementation time period, achievement of cessation within usual care clinics ranged from 8.2% to 9.9% during this same period. CONCLUSIONS: A low-burden, point-of-care tobacco treatment strategy increased tobacco treatment and cessation, thereby improving access to and the impact of evidence-based cessation treatment. Using implementation strategies to embed tobacco treatment in every healthcare encounter promises to engage more smokers in evidence-based treatment and facilitate smoking cessation, thereby improving care cancer for patients who smoke.

A cascade of care for alcohol use disorder: Using 2015-2019 National Survey on Drug Use and Health data to identify gaps in past 12-month care.

BACKGROUND: Although effective treatments exist, alcohol use disorder (AUD) is undertreated. We used a cascade of care framework to understand gaps in care for persons with AUD. METHODS: Using 2015-2019 National Survey on Drug Use and Health data, we evaluated the following steps in the cascade of care: (1) adult prevalence of AUD; (2) proportion of adults with AUD who utilized health care in the past 12 months; (3) proportion with AUD screened about their alcohol use; (4) proportion with AUD who received a brief intervention about their alcohol misuse; (5) proportion with AUD who received information about treatment for alcohol misuse; and (6) proportion with AUD who received treatment. Analyses were stratified by AUD severity. RESULTS: Of the 214,505 persons included in the sample, the weighted prevalence of AUD was 7.8% (95% CI 7.6-8.0%). Cascades of care showed the majority of individuals with AUD utilized health care in the past 12 months [81.4% (95% CI 80.7-82.1%)] and were screened about alcohol use [69.9% (95% CI 68.9-70.8%)]. However, only a minority of individuals received subsequent steps of care, including 11.6% (95% CI 11.0-12.2%) who reported receiving a brief intervention, 5.1% (95% CI 4.6-5.6%) who were referred to treatment, and 5.8% (95% CI 5.4-6.3%) who received treatment. Similar patterns were observed when cascades of care were stratified by AUD severity. CONCLUSIONS: Persons with AUD commonly utilize health care and are often screened about alcohol use, but few receive treatment. Healthcare settings-particularly primary care settings-represent a prime opportunity to implement AUD treatment to improve outcomes in this high-risk population.

Being Ostracized Versus Out of the Loop: Redundant or Unique Predictors of Variance in Workplace Outcomes?

Based on the existing research, being excluded from information (i.e., being out of the loop) produces similar consequences as being ignored or excluded from activities. Consequently, one might wonder whether it is necessary to measure or study different types of exclusion in the workplace context, rather than just assessing a single type of exclusion. The current research investigated the associations between two types of workplace exclusion (i.e., being ostracized and being left out of the loop) and various workplace outcomes, with the purpose of determining whether these different types of exclusion predict unique or redundant variance in these workplace outcomes. In Study 1, we obtained better model fit when we assigned items measuring out-of-the-loop experiences at work to a different factor than items assessing experiences with ostracism at work. In Study 2, we observed that measuring employees' experiences with being out of the loop predicted unique variance in workplace outcomes (e.g., job satisfaction), above and beyond experiences with ostracism at work. Relative weight analyses suggested that both ostracism and out-of-the-loop experiences were equally important predictors of these outcomes. Together, these studies indicate that being ostracized and being left out of the loop may be distinct exclusion experiences and better predictions about workplace outcomes can be made by assessing both types of exclusion. On a practical level, measuring different types of exclusion may prove useful, because organizations may need to implement different interventions for addressing distinct types of exclusion.

Delivering information about medication assisted treatment to individuals who misuse opioids through a mobile app: a pilot study.

BACKGROUND: Digital therapeutic tools (e.g. mobile applications) can be accessible, low-cost interventions that counter misconceptions about medication assisted treatment (MAT) and/or improve deficits in MAT knowledge that are common barriers to treatment entry among individuals with opioid dependence. The purpose of this pilot study was to examine the preliminary effectiveness of a mobile application, 'uMAT-R', that includes health information about OUD recovery supported by science and MAT benefits. METHODS: Twenty-six adult participants with OUD recruited via social media completed all modules and pre/post-assessments within uMAT-R. McNemar's test was used to compare interest in treatment before and after completing the app, and paired t tests were used to compare MAT attitude scores before and after completing the modules within uMAT-R. RESULTS: Before viewing uMAT-R, 32% agreed/strongly agreed that they were interested in starting treatment to recover from opioid misuse, compared to 48% after completing uMAT-R. The average scores on the MAT attitudes scale and its Aid to Behavior Change subscale improved from before to after viewing uMAT-R. Among the participants, 88% felt that uMAT-R would be useful to consult when making decisions about recovery. CONCLUSIONS: Our encouraging pilot findings support the use of uMAT-R to help address the current opioid epidemic.

Tobacco Use Prevalence and Smoking Cessation Pharmacotherapy Prescription Patterns Among Hospitalized Patients by Medical Specialty.

INTRODUCTION: Effective smoking cessation medications are readily available but may be underutilized in hospital settings. In our large, tertiary care hospital, we aimed to (1) characterize patient tobacco use prevalence across medical specialties, (2) determine smoking cessation pharmacotherapy prescription variation across specialties, and (3) identify opportunities for improvement in practice. METHODS: Using electronic health records at Barnes Jewish Hospital, we gathered demographic data, admitting service, admission route, length of stay, self-reported tobacco use, and smoking cessation prescriptions over a 6-year period, from 2010 to 2016. We then compared tobacco use prevalence and smoking cessation prescriptions across medical specialties using a cross-sectional, retrospective design. RESULTS: Past 12-month tobacco use was reported by patients in 27.9% of inpatient admissions; prescriptions for smoking cessation pharmacotherapy were provided during 21.5% of these hospitalizations. The proportion of patients reporting tobacco use was highest in psychiatry (55.3%) and lowest in orthopedic surgery (17.1%). Psychiatric patients who reported tobacco use were most likely to receive pharmacotherapy (71.8% of admissions), and plastic surgery patients were least likely (4.7% of admissions). Compared with Caucasian tobacco users, African American patients who used tobacco products were less likely to receive smoking cessation medications (adjusted odds ratio [aOR] = 0.65; 95% confidence interval [CI] = 0.62 to 0.68). CONCLUSIONS: Among hospitalized tobacco users, safe and cost-effective pharmacotherapies are under-prescribed. We identified substantial variation in prescribing practices across different medical specialties and demographic groups, suggesting the need for an electronic medical record protocol that facilitates consistent tobacco use cessation pharmacotherapy treatment. IMPLICATIONS: Tobacco use cessation pharmacotherapy is underutilized during hospitalization, and prescription rates vary greatly across medical specialties and patient characteristics. Hospitals may benefit from implementing policies and practices that standardize and automate the offer of smoking pharmacotherapy for all hospitalized patients who use tobacco.

E-cigarette Usage Is Associated With Increased Past-12-Month Quit Attempts and Successful Smoking Cessation in Two US Population-Based Surveys.

INTRODUCTION: We examined past-12-month quit attempts and smoking cessation from 2006 to 2016 while accounting for demographic shifts in the US population. In addition, we sought to understand whether the current use of electronic cigarettes was associated with a change in past-12-month quit attempts and successful smoking cessation at the population level. METHODS: We analyzed data from 25- to 44-year-olds from the National Health Interview Survey (NHIS) from 2006 to 2016 (N = 26,354) and the Tobacco Use Supplement to the Current Population Survey (TUS-CPS) in 2006-2007, 2010-2011, and 2014-2015 (N = 33,627). Data on e-cigarette use were available in the 2014-2016 NHIS and 2014-2015 TUS-CPS surveys. RESULTS: Past-12-month quit attempts and smoking cessation increased in recent years compared with 2006. Current e-cigarette use was associated with higher quit attempts (adjusted odds ratio [aOR] = 2.29, 95% confidence interval [CI] = 1.87 to 2.81, p < .001) and greater smoking cessation (aOR = 1.64, 95% CI = 1.21 to 2.21, p = .001) in the NHIS. Multivariable logistic regression of the TUS-CPS data showed that current e-cigarette use was similarly significantly associated with increased past-12-month quit attempts and smoking cessation. Significant interactions were found for smoking frequency (everyday and some-day smoking) and current e-cigarette use for both outcomes (p < .0001) with the strongest positive effects seen in everyday smokers. CONCLUSIONS: Compared with 2006, past-12-month quit attempts and smoking cessation increased among adults aged 25-44 in recent years. Current e-cigarette use was associated with increased past-12-month quit attempts and successful smoking cessation among established smokers. These findings are relevant to future tobacco policy decisions. IMPLICATIONS: E-cigarettes were introduced into the US market over the past decade. During this period, past-12-month quit attempts and smoking cessation have increased among US adults aged 25-44. These trends are inconsistent with the hypothesis that e-cigarette use is delaying quit attempts and leading to decreased smoking cessation. In contrast, current e-cigarette use was associated with significantly higher past-12-month quit attempts and past-12-month cessation. These findings suggest that e-cigarette use contributes to a reduction in combustible cigarette use among established smokers.

Technology-Based Alcohol Interventions in Primary Care: Systematic Review.

BACKGROUND: Primary care settings are uniquely positioned to reach individuals at risk of alcohol use disorder through technology-delivered behavioral health interventions. Despite emerging effectiveness data, few efforts have been made to summarize the collective findings from these delivery approaches. OBJECTIVE: The aim of this study was to review recent literature on the use of technology to deliver, enhance, or support the implementation of alcohol-related interventions in primary care. We focused on addressing questions related to (1) categorization or target of the intervention, (2) descriptive characteristics and context of delivery, (3) reported efficacy, and (4) factors influencing efficacy. METHODS: We conducted a comprehensive search and systematic review of completed studies at the intersection of primary care, technology, and alcohol-related problems published from January 2000 to December 2018 within EBSCO databases, ProQuest Dissertations, and Cochrane Reviews. Of 2307 initial records, 42 were included and coded independently by 2 investigators. RESULTS: Compared with the years of 2000 to 2009, published studies on technology-based alcohol interventions in primary care nearly tripled during the years of 2010 to 2018. Of the 42 included studies, 28 (64%) were randomized controlled trials. Furthermore, studies were rated on risk of bias and found to be predominantly low risk (n=18), followed by moderate risk (n=16), and high risk (n=8). Of the 24 studies with primary or secondary efficacy outcomes related to drinking and drinking-related harms, 17 (71%) reported reduced drinking or harm in all primary and secondary efficacy outcomes. Furthermore, of the 31 studies with direct comparisons with treatment as usual (TAU), 13 (42%) reported that at least half of the primary and secondary efficacy outcomes of the technology-based interventions were superior to TAU. High efficacy was associated with provider involvement and the reported use of an implementation strategy to deliver the technology-based intervention. CONCLUSIONS: Our systematic review has highlighted a pattern of growth in the number of studies evaluating technology-based alcohol interventions in primary care. Although these interventions appear to be largely beneficial in primary care, outcomes may be enhanced by provider involvement and implementation strategy use. This review enables better understanding of the typologies and efficacy of these interventions and informs recommendations for those developing and implementing technology-based alcohol interventions in primary care settings.

Minding the interpersonal gap: mindfulness-based interventions in the prevention of ostracism.

Ostracism is a ubiquitous phenomenon, occurring across a broad range of social contexts and detrimentally impacting personal outcomes. Through enhanced present-moment attention and awareness, mindfulness-based interventions may help prevent this harmful behavior. The current research examined the role of state mindfulness in reducing the propensity to commit ostracism. This relationship was investigated in two studies: a field-based quasi-experiment (Study 1, n=51) and a laboratory-based experiment (Study 2, n=100). Both studies supported the utility of brief mindfulness-based interventions in reducing the propensity to ostracize others. The current studies support the relevance of mindfulness in addressing the substantial problem of ostracism. Among other benefits, fostering mindfulness in a variety of contexts may help reduce personal and social costs associated with this type of incivility. This research represents the first known attempt to utilize a personal resource (mindfulness) to decrease the degree to which individuals ostracize others.

Technology-based interventions in social work practice: a systematic review of mental health interventions.

Despite concerns around the use of technology-based interventions, they are increasingly being employed by social workers as a direct practice methodology to address the mental health needs of vulnerable clients. Researchers have highlighted the importance of using innovative technologies within social work practice, yet little has been done to summarize the evidence and collectively assess findings. In this systematic review, we describe accounts of technology-based mental health interventions delivered by social workers over the past 10 years. Results highlight the impacts of these tools and summarize advantages and disadvantages to utilizing technologies as a method for delivering or facilitating interventions.

Implementation of Health IT for Cancer Screening in US Primary Care: Scoping Review.

BACKGROUND: A substantial percentage of the US population is not up to date on guideline-recommended cancer screenings. Identifying interventions that effectively improve screening rates would enhance the delivery of such screening. Interventions involving health IT (HIT) show promise, but much remains unknown about how HIT is optimized to support cancer screening in primary care. OBJECTIVE: This scoping review aims to identify (1) HIT-based interventions that effectively support guideline concordance in breast, cervical, and colorectal cancer screening provision and follow-up in the primary care setting and (2) barriers or facilitators to the implementation of effective HIT in this setting. METHODS: Following scoping review guidelines, we searched MEDLINE, CINAHL Plus, Web of Science, and IEEE Xplore databases for US-based studies from 2015 to 2021 that featured HIT targeting breast, colorectal, and cervical cancer screening in primary care. Studies were dual screened using a review criteria checklist. Data extraction was guided by the following implementation science frameworks: the Reach, Effectiveness, Adoption, Implementation, and Maintenance framework; the Expert Recommendations for Implementing Change taxonomy; and implementation strategy reporting domains. It was also guided by the Integrated Technology Implementation Model that incorporates theories of both implementation science and technology adoption. Reporting was guided by PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews). RESULTS: A total of 101 studies met the inclusion criteria. Most studies (85/101, 84.2%) involved electronic health record-based HIT interventions. The most common HIT function was clinical decision support, primarily used for panel management or at the point of care. Most studies related to HIT targeting colorectal cancer screening (83/101, 82.2%), followed by studies related to breast cancer screening (28/101, 27.7%), and cervical cancer screening (19/101, 18.8%). Improvements in cancer screening were associated with HIT-based interventions in most studies (36/54, 67% of colorectal cancer-relevant studies; 9/14, 64% of breast cancer-relevant studies; and 7/10, 70% of cervical cancer-relevant studies). Most studies (79/101, 78.2%) reported on the reach of certain interventions, while 17.8% (18/101) of the included studies reported on the adoption or maintenance. Reported barriers and facilitators to HIT adoption primarily related to inner context factors of primary care settings (eg, staffing and organizational policies that support or hinder HIT adoption). Implementation strategies for HIT adoption were reported in 23.8% (24/101) of the included studies. CONCLUSIONS: There are substantial evidence gaps regarding the effectiveness of HIT-based interventions, especially those targeting guideline-concordant breast and colorectal cancer screening in primary care. Even less is known about how to enhance the adoption of technologies that have been proven effective in supporting breast, colorectal, or cervical cancer screening. Research is needed to ensure that the potential benefits of effective HIT-based interventions equitably reach diverse primary care populations.

Genomic Insights for Personalized Care: Motivating At-Risk Individuals Toward Evidence-Based Health Practices.

Background: Lung cancer and tobacco use pose significant global health challenges, necessitating a comprehensive translational roadmap for improved prevention strategies. Polygenic risk scores (PRSs) are powerful tools for patient risk stratification but have not yet been widely used in primary care for lung cancer, particularly in diverse patient populations. Methods: We propose the GREAT care paradigm, which employs PRSs to stratify disease risk and personalize interventions. We developed PRSs using large-scale multi-ancestry genome-wide association studies and standardized PRS distributions across all ancestries. We applied our PRSs to 796 individuals from the GISC Trial, 350,154 from UK Biobank (UKBB), and 210,826 from All of Us Research Program (AoU), totaling 561,776 individuals of diverse ancestry. Results: Significant odds ratios (ORs) for lung cancer and difficulty quitting smoking were observed in both UKBB and AoU. For lung cancer, the ORs for individuals in the highest risk group (top 20% versus bottom 20%) were 1.85 (95% CI: 1.58 - 2.18) in UKBB and 2.39 (95% CI: 1.93 - 2.97) in AoU. For difficulty quitting smoking, the ORs (top 33% versus bottom 33%) were 1.36 (95% CI: 1.32 - 1.41) in UKBB and 1.32 (95% CI: 1.28 - 1.36) in AoU. Conclusion: Our PRS-based intervention model leverages large-scale genetic data for robust risk assessment across populations. This model will be evaluated in two cluster-randomized clinical trials aimed at motivating health behavior changes in high-risk patients of diverse ancestry. This pioneering approach integrates genomic insights into primary care, promising improved outcomes in cancer prevention and tobacco treatment.

Integrating Tobacco Treatment Into Oncology Care: Reach and Effectiveness of Evidence-Based Tobacco Treatment Across National Cancer Institute-Designated Cancer Centers.

PURPOSE: Quitting smoking improves patients' clinical outcomes, yet smoking is not commonly addressed as part of cancer care. The Cancer Center Cessation Initiative (C3I) supports National Cancer Institute-designated cancer centers to integrate tobacco treatment programs (TTPs) into routine cancer care. C3I centers vary in size, implementation strategies used, and treatment approaches. We examined associations of these contextual factors with treatment reach and smoking cessation effectiveness. METHODS: This cross-sectional study used survey data from 28 C3I centers that reported tobacco treatment data during the first 6 months of 2021. Primary outcomes of interest were treatment reach (reach)-the proportion of patients identified as currently smoking who received at least one evidence-based tobacco treatment component (eg, counseling and pharmacotherapy)-and smoking cessation effectiveness (effectiveness)-the proportion of patients reporting 7-day point prevalence abstinence at 6-month follow-up. Center-level differences in reach and effectiveness were examined by center characteristics, implementation strategies, and tobacco treatment components. RESULTS: Of the total 692,662 unique patients seen, 44,437 reported current smoking. Across centers, a median of 96% of patients were screened for tobacco use, median smoking prevalence was 7.4%, median reach was 15.4%, and median effectiveness was 18.4%. Center-level characteristics associated with higher reach included higher smoking prevalence, use of center-wide TTP, and lower patient-to-tobacco treatment specialist ratio. Higher effectiveness was observed at centers that served a larger overall population and population of patients who smoke, reported a higher smoking prevalence, and/or offered electronic health record referrals via a closed-loop system. CONCLUSION: Whole-center TTP implementation among inpatients and outpatients, and increasing staff-to-patient ratios may improve TTP reach. Designating personnel with tobacco treatment expertise and resources to increase tobacco treatment dose or intensity may improve smoking cessation effectiveness.

FAST: A Framework to Assess Speed of Translation of Health Innovations to Practice and Policy.

The 17-year time span between discovery and application of evidence in practice has become a unifying challenge for implementation science and translational science more broadly. Further, global pandemics and social crises demand timely implementation of rapidly accruing evidence to reduce morbidity and mortality. Yet speed remains an understudied metric in implementation science. Prevailing evaluations of implementation lack a temporal aspect, and current approaches have not yielded rapid implementation. In this paper, we address speed as an important conceptual and methodological gap in implementation science. We aim to untangle the complexities of studying implementation speed, offer a framework to assess speed of translation (FAST), and provide guidance to measure speed in evaluating implementation. To facilitate specification and reporting on metrics of speed, we encourage consideration of stakeholder perspectives (e.g., comparison of varying priorities), referents (e.g., speed in attaining outcomes, transitioning between implementation phases), and observation windows (e.g., time from intervention development to first patient treated) in its measurement. The FAST framework identifies factors that may influence speed of implementation and potential effects of implementation speed. We propose a research agenda to advance understanding of the pace of implementation, including identifying accelerators and inhibitors to speed.

Bridges to Sobriety: Testing the Feasibility and Acceptability of a Mobile App Designed to Supplement an Adolescent Substance Use Disorder Treatment Program.

Adolescent substance use is a growing problem that causes a myriad of negative outcomes. Using substances during adolescence can lead to decreased executive functioning and is correlated with the top three causes of deaths for adolescents. Treatment options vary and the impact on outcomes are mixed, with engagement being of the most important indicators. Gaming is a popular activity among adolescents, and yet smartphone applications are relatively unexplored within substance use disorder treatment programs. This paper explores the feasibility and acceptability of implementing a mobile application as a supplement to existing adolescent substance use disorder treatment in a behavioral health agency in eastern Missouri. Feedback was received from staff and clients to assess feasibility and acceptability of implementation with barriers discussed. Results indicate there is promise with incorporation of smartphone-based applications into existing interventions and act as recommendations for other providers.

Point of care tobacco treatment sustains during COVID-19, a global pandemic.

BACKGROUND: Tobacco cessation treatment for cancer patients is essential to providing comprehensive oncologic care. We have implemented a point of care tobacco treatment care model enabled by electronic health record (EHR) modifications in a comprehensive cancer center. Data are needed on the sustainability of both reach of treatment and effectiveness over time, including the COVID-19 pandemic. METHODS: Using EHR data from the pre-implementation (P: 5 months) and post-implementation periods (6 month-blocks, T1-T5 for a total of 30 months), we compared two primary outcomes: 1) reach of treatment among those smoking and 2) effectiveness assessed by smoking cessation among those smoking in the subsequent 6 month period. We analyzed the data using generalized estimation equation regression models. RESULTS: With the point of care tobacco treatment care model, reach of treatment increased from pre to post T5 (3.2 % vs. 48.4 %, RR 15.50, 95 % CI 10.56-22.74, p < 0.0001). Reach of treatment in all post periods (T1-T5 including the COVID-19 pandemic time) remained significantly higher than the pre period. Effectiveness, defined by smoking cessation among those smoking, increased from pre to post T2 before the pandemic (12.4 % vs. 21.4 %, RR 1.57, 95 % CI 1.31-1.87, p < 0.0001). However, effectiveness, while higher in later post periods (T3, T4), was no longer significantly increased compared with the pre period. CONCLUSION: A point of care EHR-enabled tobacco treatment care model demonstrates sustained reach up to 30 months following implementation, even during the COVID-19 pandemic and changes in healthcare prioritization. Effectiveness was sustained for 12 months, but did not sustain through the subsequent 12 months.

Novel Implementation Strategy to Electronically Screen and Signpost Patients to Health Behavior Apps: Mixed Methods Implementation Study (OptiMine Study).

BACKGROUND: Behavior change apps have the potential to provide individual support on a population scale at low cost, but they face numerous barriers to implementation. Electronic health records (EHRs) in acute care hospitals provide a valuable resource for identifying patients at risk, who may benefit from behavior change apps. A novel, emerging implementation strategy is to use digital technologies not only for providing support to help-seeking individuals but also for signposting patients at risk to support services (also called proactive referral in the United States). OBJECTIVE: The OptiMine study aimed to increase the reach of behavior change apps by implementing electronic signposting for smoking cessation and alcohol reduction in a large, at-risk population that was identified through an acute care hospital EHR. METHODS: This 3-phase, mixed methods implementation study assessed the acceptability, feasibility, and reach of electronic signposting to behavior change apps by using a hospital's EHR system to identify patients who are at risk. Phase 1 explored the acceptability of the implementation strategy among the patients and staff through focus groups. Phase 2 investigated the feasibility of using the hospital EHR to identify patients with target risk behaviors and contact them via SMS text message, email, or patient portal. Phase 3 assessed the impact of SMS text messages sent to patients who were identified as smokers or risky drinkers, which signposted them to behavior change apps. The primary outcome was the proportion of participants who clicked on the embedded link in the SMS text message to access information about the apps. The acceptability of the SMS text messages among the patients who had received them was also explored in a web-based survey. RESULTS: Our electronic signposting strategy-using SMS text messages to promote health behavior change apps to patients at risk-was found to be acceptable and feasible and had good reach. The hospital sent 1526 SMS text messages, signposting patients to either the National Health Service Smokefree or Drink Free Days apps. A total of 13.56% (207/1526) of the patients clicked on the embedded link to the apps, which exceeded our 5% a priori success criterion. Patients and staff contributed to the SMS text message content and delivery approach, which were perceived as acceptable before and after the delivery of the SMS text messages. The feasibility of the SMS text message format was determined and the target population was identified by mining the EHR. CONCLUSIONS: The OptiMine study demonstrated the proof of concept for this novel implementation strategy, which used SMS text messages to signpost at-risk individuals to behavior change apps at scale. The level of reach exceeded our a priori success criterion in a non-help-seeking population of patients receiving unsolicited SMS text messages, disconnected from hospital visits. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/23669.

In-vivo design feedback and perceived utility of a genetically-informed smoking risk tool among current smokers in the community.

BACKGROUND: The use of genetically-informed personalized risk information for behavioral disorders, namely smoking and smoking-related behaviors, is a promising yet understudied area. The Genetics and Smoking Risk Profile, or RiskProfile, leverages genetic and environmental information to communicate one's risk for smoking-related diseases. Although prior studies have examined attitudes toward genetic results, little research has investigated these perceptions through a lens of in-vivo testing; that is, user-centered design feedback in response to personalized genetic results being returned contemporaneously. This qualitative study engaged current smokers in usability testing of the RiskProfile within the context of concurrently receiving this personalized, genetically-informed smoking cessation intervention. METHODS: Eighty-nine participants who were current smokers responded to open-ended interview questions on perceptions of smoking-related genetic information and the content and format of the RiskProfile intervention that they had received moments before. Data were analyzed via the conventional content analysis approach in which themes were allowed to emerge throughout the analysis. RESULTS: Participants were able to reference and offer design input on specific elements of the RiskProfile. Overall, current smokers perceived the RiskProfile to have high potential utility. Constructive feedback that current smokers offered about the tool centered around suggested improvements to optimize its usability and technical content. CONCLUSIONS: The detailed and constructive feedback from participants highlights that in-vivo feedback offers a useful design approach that addresses concerns of rigor and relevance when returning genetic results. This unique method demonstrated perceived utility and constructive design feedback for the RiskProfile among current smokers and can play an important role in optimizing the design and implementation of personalized genetic risk interventions moving forward.

Proof of Concept of a Personalized Genetic Risk Tool to Promote Smoking Cessation: High Acceptability and Reduced Cigarette Smoking.

Relatively little is known about the possible effects of personalized genetic risk information on smoking, the leading preventable cause of morbidity and mortality. We examined the acceptability and potential behavior change associated with a personalized genetically informed risk tool (RiskProfile) among current smokers. Current smokers (n = 108) were enrolled in a pre-post study with three visits. At visit 1, participants completed a baseline assessment and genetic testing via 23andMe. Participants' raw genetic data (CHRNA5 variants) and smoking heaviness were used to create a tailored RiskProfile tool that communicated personalized risks of smoking-related diseases and evidence-based recommendations to promote cessation. Participants received their personalized RiskProfile intervention at visit 2, approximately 6 weeks later. Visit 3 involved a telephone-based follow-up assessment 30 days after intervention. Of enrolled participants, 83% were retained across the three visits. Immediately following intervention, acceptability of RiskProfile was high (M = 4.4; SD = 0.6 on scale of 1 to 5); at 30-day follow-up, 89% of participants demonstrated accurate recall of key intervention messages. In the full analysis set of this single-arm trial, cigarettes smoked per day decreased from intervention to 30-day follow-up [11.3 vs. 9.8; difference = 1.5; 95% confidence interval (0.6-2.4); P = 0.001]. A personalized genetically informed risk tool was found to be highly acceptable and associated with a reduction in smoking, although the absence of a control group must be addressed in future research. This study demonstrates proof of concept for translating key basic science findings into a genetically informed risk tool that was used to promote progress toward smoking cessation.Prevention Relevance: This study demonstrates that personal genetic information can be incorporated into a risk feedback tool that was highly acceptable to current smokers and associated with reductions in smoking. These findings may pave the way for effectiveness and implementation research on genetically-informed behavior change interventions to enhance cancer prevention efforts.

Tobacco Treatment Program Models in US Hospitals and Outpatient Centers on Behalf of the SRNT Treatment Network.

Because tobacco use remains one of the leading causes of disease, disability, and mortality, tobacco treatment programs should be integrated into medical systems such as hospitals and outpatient centers. Medical providers have a unique, high-impact opportunity to initiate smoking cessation treatment with patients. However, there are several barriers that may hinder the development and implementation of these programs. The purpose of this review was to address such barriers by illustrating several examples of successful tobacco treatment programs in US health-care systems that were contributed by the authors. This includes describing treatment models, billing procedures, and implementation considerations. Using an illustrative review of vignettes from existing programs, various models are outlined, emphasizing commonalities and unique features, strengths and limitations, resources necessary, and other relevant considerations. In addition, clinical research and dissemination trials from each program are described to provide evidence of feasibility and efficacy from these programs. This overview of example treatment models designed for hospitals and outpatient centers provides guidelines for any emerging tobacco cessation services within these contexts. For existing treatment programs, this review provides additional insight and ideas about improving these programs within their respective medical systems.