Rapid-cycle designs to adapt interventions for COVID-19 in safety-net healthcare systems.

Racial/ethnic minority, low socioeconomic status, and rural populations are disproportionately affected by COVID-19. Developing and evaluating interventions to address COVID-19 testing and vaccination among these populations are crucial to improving health inequities. The purpose of this paper is to describe the application of a rapid-cycle design and adaptation process from an ongoing trial to address COVID-19 among safety-net healthcare system patients. The rapid-cycle design and adaptation process included: (a) assessing context and determining relevant models/frameworks; (b) determining core and modifiable components of interventions; and (c) conducting iterative adaptations using Plan-Do-Study-Act (PDSA) cycles. PDSA cycles included: Plan. Gather information from potential adopters/implementers (e.g., Community Health Center [CHC] staff/patients) and design initial interventions; Do. Implement interventions in single CHC or patient cohort; Study. Examine process, outcome, and context data (e.g., infection rates); and, Act. If necessary, refine interventions based on process and outcome data, then disseminate interventions to other CHCs and patient cohorts. Seven CHC systems with 26 clinics participated in the trial. Rapid-cycle, PDSA-based adaptations were made to adapt to evolving COVID-19-related needs. Near real-time data used for adaptation included data on infection hot spots, CHC capacity, stakeholder priorities, local/national policies, and testing/vaccine availability. Adaptations included those to study design, intervention content, and intervention cohorts. Decision-making included multiple stakeholders (e.g., State Department of Health, Primary Care Association, CHCs, patients, researchers). Rapid-cycle designs may improve the relevance and timeliness of interventions for CHCs and other settings that provide care to populations experiencing health inequities, and for rapidly evolving healthcare challenges such as COVID-19.

Racial/ethnic minority, low socioeconomic status, and rural populations experience a disproportionate burden of COVID-19. Finding ways to address COVID-19 among these populations is crucial to improving health inequities. The purpose of this paper is to describe the rapid-cycle design process for a research project to address COVID-19 testing and vaccination among safety-net healthcare system patients. The project used real-time information on changes in COVID-19 policy (e.g., vaccination authorization), local case rates, and the capacity of safety-net healthcare systems to iteratively change interventions to ensure interventions were relevant and timely for patients. Key changes that were made to interventions included a change to the study design to include vaccination as a focus of the interventions after the vaccine was authorized; change in intervention content according to the capacity of local Community Health Centers to provide testing to patients; and changes to intervention cohorts such that priority groups of patients were selected for intervention based on characteristics including age, residency in an infection "hot spot," or race/ethnicity. Iteratively improving interventions based on real-time data collection may increase intervention relevance and timeliness, and rapid-cycle adaptions can be successfully implemented in resource constrained settings like safety-net healthcare systems.

Mindfulness-Based Smoking Cessation Delivered Through Telehealth and Text Messaging for Low-Income Smokers: Protocol for a Randomized Controlled Trial.

BACKGROUND: Tobacco use is the leading cause of preventable morbidity and mortality. Adults with low income and members of certain racial and ethnic minority groups are less likely to quit, and therefore, they experience profound tobacco-related health disparities. Mindfulness training can increase the rates of smoking cessation and lapse recovery, and telehealth and SMS text messaging have the potential to provide more accessible treatment. OBJECTIVE: This study aims to test the efficacy of delivering mindfulness-based smoking cessation treatment through text messaging (iQuit Mindfully) and telehealth (group videoconferencing), both as stand-alone interventions and in combination. In addition, it aims to examine the underlying mechanisms of mindfulness treatment. METHODS: In this 2×2 randomized controlled trial, participants are randomized into 1 of 4 groups based on assignment to iQuit Mindfully text messages (yes or no) and mindfulness videoconference groups (yes or no). The primary outcomes are biochemically verified smoking abstinence at 8, 12, and 24 weeks after the start of treatment. Secondary outcomes include the frequency of home mindfulness practice and self-reported levels of mindfulness, emotions, craving, withdrawal, dependence, self-efficacy, and social support. RESULTS: Recruitment, treatment, and assessment began in spring and summer 2021, and data collection is expected to continue through spring 2024. CONCLUSIONS: This project aims to improve smoking cessation outcomes for low-income, racially and ethnically diverse smokers through mindfulness-based telehealth group counseling and text messaging support. We also aim to advance the scientific study of the mechanisms of action of mindfulness treatment, which could inform the development of more efficacious and efficient treatments to reduce tobacco disparities. TRIAL REGISTRATION: Clinicaltrials.gov NCT04965181; https://clinicaltrials.gov/ct2/show/NCT04965181. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/35688.

Inaccuracies in electronic health records smoking data and a potential approach to address resulting underestimation in determining lung cancer screening eligibility.

OBJECTIVE: The US Preventive Services Task Force (USPSTF) requires the estimation of lifetime pack-years to determine lung cancer screening eligibility. Leading electronic health record (EHR) vendors calculate pack-years using only the most recently recorded smoking data. The objective was to characterize EHR smoking data issues and to propose an approach to addressing these issues using longitudinal smoking data. MATERIALS AND METHODS: In this cross-sectional study, we evaluated 16 874 current or former smokers who met USPSTF age criteria for screening (50-80 years old), had no prior lung cancer diagnosis, and were seen in 2020 at an academic health system using the Epic® EHR. We described and quantified issues in the smoking data. We then estimated how many additional potentially eligible patients could be identified using longitudinal data. The approach was verified through manual review of records from 100 subjects. RESULTS: Over 80% of evaluated records had inaccuracies, including missing packs-per-day or years-smoked (42.7%), outdated data (25.1%), missing years-quit (17.4%), and a recent change in packs-per-day resulting in inaccurate lifetime pack-years estimation (16.9%). Addressing these issues by using longitudinal data enabled the identification of 49.4% more patients potentially eligible for lung cancer screening (P < .001). DISCUSSION: Missing, outdated, and inaccurate smoking data in the EHR are important barriers to effective lung cancer screening. Data collection and analysis strategies that reflect changes in smoking habits over time could improve the identification of patients eligible for screening. CONCLUSION: The use of longitudinal EHR smoking data could improve lung cancer screening.

Transition to telehealth: Challenges and benefits of conducting group-based smoking and alcohol treatment virtually.

In the midst of the COVID-19 pandemic, many research and clinical teams have transitioned their projects to a remote-based format, weighing the pros and cons of making such a potentially disruptive decision. One key aspect of this decision is related to the patient population, with underserved populations possibly benefiting from the increased reach of telehealth, while also encountering technology barriers that may limit accessibility. Early in the pandemic, our team shifted a group-based, smoking cessation and alcohol modification treatment trial to a remote-based format. Our population included individuals who concurrently wanted to quit smoking and modify their alcohol use. This paper describes technical and logistical considerations of transitioning from in-person to remote-based delivery for group-based treatment, including the impact upon study staff, group facilitators, participants, and the institution. Remotely-delivered group treatment may be valuable not only in response to pandemic-related restrictions, but it may also offer an alternative treatment-delivery modality with independent benefits in terms of population reach, costs, and pragmatics for clients, staff, and institutions.