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.

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.

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.

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.

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.

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.

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.

Care-paradigm shift promoting smoking cessation treatment among cancer center patients via a low-burden strategy, Electronic Health Record-Enabled Evidence-Based Smoking Cessation Treatment.

Tobacco smoking is an important risk factor for cancer incidence, an effect modifier for cancer treatment, and a negative prognostic factor for disease outcomes. Inadequate implementation of evidence-based smoking cessation treatment in cancer centers, a consequence of numerous patient-, provider-, and system-level barriers, contributes to tobacco-related morbidity and mortality. This study provides data for a paradigm shift from a frequently used specialist referral model to a point-of-care treatment model for tobacco use assessment and cessation treatment for outpatients at a large cancer center. The point-of-care model is enabled by a low-burden strategy, the Electronic Health Record-Enabled Evidence-Based Smoking Cessation Treatment program, which was implemented in the cancer center clinics on June 2, 2018. Five-month pre- and post-implementation data from the electronic health record (EHR) were analyzed. The percentage of cancer patients assessed for tobacco use significantly increased from 48% to 90% (z = 126.57, p < .001), the percentage of smokers referred for cessation counseling increased from 0.72% to 1.91% (z = 3.81, p < .001), and the percentage of smokers with cessation medication significantly increased from 3% to 17% (z = 17.20, p < .001). EHR functionalities may significantly address barriers to point-of-care treatment delivery, improving its consistent implementation and thereby increasing access to and quality of smoking cessation care for cancer center patients.

Blending Insights from Implementation Science and the Social Sciences to Mitigate Inequities in Screening for Hereditary Cancer Syndromes.

Genomic screening to identify people at high risk for adult-onset hereditary conditions has potential to improve population health. However, if not equitably accessible, genomics-informed screening programs will exacerbate existing health inequities or give rise to new ones. To realize the disease prevention potential of these screening tools, we need strategies to broaden their reach. We propose a conceptual framework that merges insights from implementation science and sociological research on health inequities. Our framework does three things: first, it broadens the arenas of action beyond those typically addressed in implementation science frameworks; second, it argues for recruiting more diverse partners to share the work of implementation and dissemination; and third, it shows how implementation activities can be coordinated more effectively among those partners. We use screening for hereditary breast and ovarian cancers (HBOC) as a case to illustrate how this enhanced framework could guide implementation science and distribute the benefits of genomic medicine more equitably. Although our example is specific to genomics, this approach is more broadly applicable to the field of implementation science. Coordinated action among multiple stakeholders could translate a host of new technologies from the bench to the trench without creating new inequities or exacerbating existing ones.

Leverage points to improve smoking cessation treatment in a large tertiary care hospital: a systems-based mixed methods study.

OBJECTIVES: To generate system insights on patient and provider levers and strategies that must be activated to improve hospital-based smoking cessation treatment. DESIGN: Mixed methods study including a series of in-depth group model building sessions, which informed the design of an online survey completed by healthcare providers and a structured interview protocol administered at the bedside to patients who smoke. SETTING: Large, tertiary care hospital in the Midwestern United States. PARTICIPANTS: Group model building: 28 healthcare providers and 22 previously-hospitalised patients; Online survey: 308 healthcare providers; Bedside interviews: 205 hospitalised patients. PRIMARY AND SECONDARY OUTCOME MEASURES: Hypothesis-generating, participatory qualitative methods informed the examination of the following quantitative outcomes: patient interest versus provider perception of patient interest in smoking cessation and treatment; patient-reported receipt versus provider-reported offering of inpatient smoking cessation interventions; and priority ratings of importance and feasibility of strategies to improve treatment. RESULTS: System insights included patients frequently leaving the floor to smoke, which created major workflow disruption. Leverage points included interventions to reduce withdrawal symptoms, and action ideas included nurse-driven protocols for timely administration of nicotine replacement therapy. Quantitative data corroborated system insights; for instance, 80% of providers reported that patients frequently leave the floor to smoke, leading to safety risks, missed assessments and inefficient use of staff time. Patients reported significantly lower rates of receiving any smoking cessation interventions, compared with provider reports (mean difference=17.4%-33.7%, p<0.001). Although 92% of providers cited patient interest as a key barrier, only 4% of patients indicated no interest in quitting or reducing smoking. CONCLUSIONS: Engaging hospital providers and patients in participatory approaches to develop an implementation strategy revealed discrepant perceptions of patient interest and frequency of hospital-based treatment for smoking. These findings spurred adoption of standardised point-of-care treatment for cigarette smoking, which remains highly prevalent yet undertreated among hospitalised patients.

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.