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

Lung cancer and tobacco use pose significant global health challenges and require a comprehensive translational roadmap for improved prevention strategies. We propose the GREAT care paradigm ( G enomic Informed Care for Motivating High R isk Individuals E ligible for Evidence-b a sed Prevention), which employs polygenic risk scores (PRSs) to stratify disease risk and personalize interventions, such as lung cancer screening and tobacco treatment. We developed PRSs using large-scale multi-ancestry genome-wide association studies and adjusted for genetic ancestry for standardized risk stratification across diverse populations. We applied our PRSs to over 340,000 individuals of diverse ethnic background and found significant odds ratios for lung cancer and difficulty quitting smoking. These findings enable the evaluation of PRS-based interventions in ongoing trials aimed at motivating health behavior changes in high-risk patients. This pioneering approach enhances primary care with genomic insights, promising improved outcomes in cancer prevention and tobacco treatment, and is currently under assessment in clinical trials.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Mining Electronic Health Records to Promote the Reach of Digital Interventions for Cancer Prevention Through Proactive Electronic Outreach: Protocol for the Mixed Methods OptiMine Study.

BACKGROUND: Digital behavior change interventions have demonstrated effectiveness for smoking cessation and reducing alcohol intake, which ultimately reduce cancer risk. Leveraging electronic health records (EHR) to identify at-risk patients and increasing the reach of digital interventions through proactive electronic outreach provide a novel approach that may increase the number of individuals who engage with evidence-based treatment. OBJECTIVE: This study aims to increase the reach of digital behavior change interventions by implementing a proactive electronic message system for smoking cessation and alcohol reduction among a large, at-risk population identified through an acute hospital EHR. METHODS: This protocol describes a 3-phase, mixed-methods implementation study to assess the acceptability, feasibility, and reach of a proactive electronic message system to digital interventions using a hospital's EHR system to identify eligible patients. In Phase 1, we will conduct focus group discussions with patients and hospital staff to assess the overall acceptability of the electronic message system. In Phase 2, we will conduct a descriptive analysis of the patient population in the hospital EHR regarding target risk behaviors and other person-level characteristics to determine the project's feasibility and potential reach. In Phase 3, we will send proactive messages to patients identified as smokers or risky drinkers. Messages will encourage and provide access to behavior change mobile apps via an embedded link; the primary outcome will be the proportion of participants who click on the link to access information about the apps. RESULTS: At the time of initial protocol submission, data collection was complete, but analysis had not begun. This study was funded by Cancer Research UK from April 2019 to March 2020. Health Research Authority approval was granted in June 2019. CONCLUSIONS: Increasing the reach of digital behavior change interventions can improve population health by reducing the burden of preventable death and disease. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/23669.

A Cascade of Care for Alcohol Use Disorder: Using 2015-2018 National Survey on Drug Use and Health Data to Identify Gaps in Care.

BACKGROUND: Although effective treatments exist, alcohol use disorder (AUD) is undertreated. We used a cascade of care framework to understand gaps in care between diagnosis and treatment for persons with AUD. METHODS: Using 2015-2018 National Survey on Drug Use and Health data, we evaluated the following steps in the cascade of care: 1) prevalence of adults with AUD; 2) proportion of adults who utilized health care in the past 12 months; 3) were screened about alcohol use; 4) received a brief intervention about alcohol misuse; 5) received information about treatment for alcohol misuse; and 6) proportion of persons with AUD who received treatment. Analyses were stratified by AUD severity. RESULTS: Of the 171,766 persons included in the sample, weighted prevalence of AUD was 7.9% (95% CI 7.7-8.0%). Persons with AUD utilized health care settings at similar rates as those without AUD. Cascades of care showed the majority of individuals with AUD utilized health care and were screened about alcohol use, but the percent who received the subsequent steps of care decreased substantially. For those with severe AUD, 83.5% (CI: 78.3%-88.7%) utilized health care in the past 12 months, 73.5% (CI: 68.1%-78.9%) were screened for alcohol use, 22.7% (CI: 19.4%-26.0%) received a brief intervention, 12.4% (CI: 10%-14.7%) received information about treatment, and 20.5% (CI: 18%-23.1%) were treated for AUD. The greatest decrease in the care continuum occurred from screening to brief intervention and referral to treatment. More persons with severe AUD received treatment than were referred, indicating other pathways to treatment outside of the healthcare system. CONCLUSIONS: Persons with AUD utilize health care at high rates and are frequently screened about alcohol use, but few receive treatment. Health care settings-particularly primary care settings-represent a prime opportunity to implement pharmacologic treatment for AUD to improve outcomes in this high-risk population.

A Smartphone-Based Technique to Detect Dynamic User Preferences for Tailoring Behavioral Interventions: Observational Utility Study of Ecological Daily Needs Assessment.

BACKGROUND: Mobile health apps are promising vehicles for delivering scalable health behavior change interventions to populations that are otherwise difficult to reach and engage, such as young adults with psychiatric conditions. To improve uptake and sustain consumer engagement, mobile health interventions need to be responsive to individuals' needs and preferences, which may change over time. We previously created an ecological daily needs assessment to capture microprocesses influencing user needs and preferences for mobile health treatment adaptation. OBJECTIVE: The objective of our study was to test the utility of a needs assessment anchored within a mobile app to capture individualized, contextually relevant user needs and preferences within the framework of a weight management mobile health app. METHODS: Participants with an iOS device could download the study app via the study website or links from social media. In this fully remote study, we screened, obtained informed consent from, and enrolled participants through the mobile app. The mobile health framework included daily health goal setting and self-monitoring, with up to 6 daily prompts to determine in-the-moment needs and preferences for mobile health-assisted health behavior change. RESULTS: A total of 24 participants downloaded the app and provided e-consent (22 female; 2 male), with 23 participants responding to at least one prompt over 2 weeks. The mean length of engagement was 5.6 (SD 4.7) days, with a mean of 2.8 (1.1) responses per day. We observed individually dynamic needs and preferences, illustrating daily variability within and between individuals. Qualitative feedback indicated preferences for self-adapting features, simplified self-monitoring, and the ability to personalize app-generated message timing and content. CONCLUSIONS: The technique provided an individually dynamic and contextually relevant alternative and complement to traditional needs assessment for assessing individually dynamic user needs and preferences during treatment development or adaptation. The results of this utility study suggest the importance of personalization and learning algorithms for sustaining app engagement in young adults with psychiatric conditions. Further study in broader user populations is needed.

Pragmatic Application of the RE-AIM Framework to Evaluate the Implementation of Tobacco Cessation Programs Within NCI-Designated Cancer Centers.

Tobacco cessation after cancer diagnosis leads to better patient outcomes. However, tobacco treatment services are frequently unavailable in cancer care settings, and multilevel implementation challenges can impede uptake of new programs. The National Cancer Institute (NCI) dedicated Cancer Moonshot funding through the Cancer Center Cessation Initiative (C3I) for NCI-Designated Cancer Centers to implement or enhance the implementation of tobacco treatment services. We examined a pragmatic application of the RE-AIM framework (reach, effectiveness, adoption, implementation, and maintenance) to evaluate tobacco treatment programs implemented within Cancer Centers funded through C3I. Using three C3I-funded Centers as examples, we describe how each RE-AIM construct was operationalized to evaluate the implementation of a wide range of cessation services (e.g., tobacco use screening, counseling, Quitline referral, pharmacotherapy) in this heterogeneous group of cancer care settings. We discuss the practical challenges encountered in assessing RE-AIM constructs in real world situations, including using the electronic health record (EHR) to aid in assessment. Reach and effectiveness evaluation required that Centers define the setting(s) where cessation services were implemented (to determine the "denominator"), enumerate the patient population, report current patient tobacco use, patient engagement in tobacco treatment, and 6-month cessation outcomes. To reduce site heterogeneity, increase data accuracy, and reduce burden, reach was frequently captured via standardized EHR enhancements that improved the identification of current smokers and tobacco treatment referrals. Effectiveness was determined by cessation outcomes (30-day point prevalence abstinence at 6-months post-engagement) assessed through a variety of data collection approaches. Adoption was measured by the characteristics and proportion of targeted cancer care settings and clinicians engaged in cessation service delivery. Implementation was assessed by examining the delivery of tobacco screening assessments and intervention components across sites, and provider-level implementation consistency. Maintenance assessments identified whether tobacco treatment services continued in the setting after implementation and documented the sustainability plan and organizational commitment to continued delivery. In sum, this paper demonstrates a pragmatic approach to using RE-AIM as an evaluation framework that yields relevant outcomes on common implementation metrics across widely differing tobacco treatment approaches and settings.

Low Burden Strategies Are Needed to Reduce Smoking in Rural Healthcare Settings: A Lesson from Cancer Clinics.

Rural populations face significant smoking-related health disparities, such as a higher prevalence of lung cancer and cancer mortality, higher prevalence of smoking, and lower likelihood of receiving cessation treatment than urban counterparts. A significant proportion of health disparities in rural populations could be eliminated with low-barrier, easy-access treatment delivery methods for smoking cessation. In this study, we assessed treatment engagement among patients in rural and urban settings. Then, we examined the effect of an electronic health record-based smoking cessation module on patient receipt of evidence-based cessation care. As part of a quality improvement project, we retrospectively observed 479,798 unique patients accounting for 1,426,089 outpatient clinical encounters from June 2018-March 2019 across 766 clinics in the greater St. Louis, southern Illinois, and mid-Missouri regions. Smoking prevalence was higher in rural versus urban clinics (20.7% vs. 13.9%, 6.7% [6.3, 7.1], odds ratio = 1.6 [1.6, 1.6], p < 0.0001), and yet rural smokers were nearly three times less likely than their urban counterparts to receive any smoking cessation treatment after adjusting for patients clustering within clinics (9.6% vs. 25.8%, -16.2% [-16.9, -15.5], odds ratio = 0.304 [0.28, 0.33], p < 0.0001). Although not yet scaled up in the rural setting, we examined the effects of a low-burden, point-of-care smoking module currently implemented in cancer clinics. After adjusting for patient clustering within clinics, patients were more likely to receive smoking treatment in clinics that implemented the module versus clinics that did not implement the module (31.2% vs. 17.5%, 13.7% [10.8, 16.6], odds ratio = 2.1 [1.8, 2.6], p < 0.0001). The point-of-care treatment approach offers a promising solution for rural settings, both in and outside the context of cancer care.

Participatory Design of a Personalized Genetic Risk Tool to Promote Behavioral Health.

Despite major advancements in genomic medicine, research to optimize the design and communication of genetically informed interventions in behavioral health has lagged. The goal of this study was to engage potential end users in participatory codesign of a personalized genetically informed risk tool to intervene on high-risk health behaviors. We used structured interviews to examine end-user attitudes and interest in personalized genetics, qualitative interviews to guide iterative design of a genetically informed tool, and questionnaires to assess acceptability and potential utility of the tool. Participants expressed strong demand for using personal genetics to inform smoking and alcohol-related disease risk and guide treatment (78%-95% agreed). Via iterative design feedback, we cocreated a genetically informed risk profile featuring (i) explanation of genetic and phenotypic markers used to construct a risk algorithm, (ii) personalized risks and benefits of healthy behavior change, and (iii) recommended actions with referral to freely available resources. Participants demonstrated sufficient understanding and cited motivating behavior change as the most useful purpose of the tool. In three phases, we confirmed strong desire for personalized genetics on high-risk health behaviors; codesigned a genetically informed profile with potential end users; and found high acceptability, comprehensibility, and perceived usefulness of the profile. As scientific discovery of genomic medicine advances in behavioral health, we must develop the tools to communicate these discoveries to consumers who stand to benefit. The potential of genomic medicine to engage populations and personalize behavioral health treatment depends, in part, on preparatory studies to design for the future implementation of genetically informed interventions.