Increasing the reach of evidence-based interventions for weight management and diabetes prevention among Medicaid patients: study protocol for a pilot Sequential Multiple Assignment Randomised Trial.

INTRODUCTION: Over 40% of US adults meet criteria for obesity, a major risk factor for chronic disease. Obesity disproportionately impacts populations that have been historically marginalised (eg, low socioeconomic status, rural, some racial/ethnic minority groups). Evidence-based interventions (EBIs) for weight management exist but reach less than 3% of eligible individuals. The aims of this pilot randomised controlled trial are to evaluate feasibility and acceptability of dissemination strategies designed to increase reach of EBIs for weight management. METHODS AND ANALYSIS: This study is a two-phase, Sequential Multiple Assignment Randomized Trial, conducted with 200 Medicaid patients. In phase 1, patients will be individually randomised to single text message (TM1) or multiple text messages (TM+). Phase 2 is based on treatment response. Patients who enrol in the EBI within 12 weeks of exposure to phase 1 (ie, responders) receive no further interventions. Patients in TM1 who do not enrol in the EBI within 12 weeks of exposure (ie, TM1 non-responders) will be randomised to either TM1-Continued (ie, no further TM) or TM1 & MAPS (ie, no further TM, up to 2 Motivation And Problem Solving (MAPS) navigation calls) over the next 12 weeks. Patients in TM+ who do not enrol in the EBI (ie, TM+ non-responders) will be randomised to either TM+Continued (ie, monthly text messages) or TM+ & MAPS (ie, monthly text messages, plus up to 2 MAPS calls) over the next 12 weeks. Descriptive statistics will be used to characterise feasibility (eg, proportion of patients eligible, contacted and enrolled in the trial) and acceptability (eg, participant opt-out, participant engagement with dissemination strategies, EBI reach (ie, the proportion of participants who enrol in EBI), adherence, effectiveness). ETHICS AND DISSEMINATION: Study protocol was approved by the University of Utah Institutional Review Board (#00139694). Results will be disseminated through study partners and peer-reviewed publications. TRIAL REGISTRATION NUMBER: clinicaltrials.gov; NCT05666323.

Application of community - engaged dissemination and implementation science to improve health equity.

Community engagement is critical to accelerate and improve implementation of evidence-based interventions to reduce health inequities. Community-engaged dissemination and implementation research (CEDI) emphasizes engaging stakeholders (e.g., community members, practitioners, community organizations, etc.) with diverse perspectives, experience, and expertise to provide tacit community knowledge regarding the local context, priorities, needs, and assets. Importantly, CEDI can help improve health inequities through incorporating unique perspectives from communities experiencing health inequities that have historically been left out of the research process. The community-engagement process that exists in practice can be highly variable, and characteristics of the process are often underreported, making it difficult to discern how engagement of community partners was used to improve implementation. This paper describes the community-engagement process for a multilevel, pragmatic randomized trial to increase the reach and impact of evidence-based tobacco cessation treatment among Community Health Center patients; describes how engagement activities and the resulting partnership informed the development of implementation strategies and improved the research process; and presents lessons learned to inform future CEDI research.

QuitSMART Utah: an implementation study protocol for a cluster-randomized, multi-level Sequential Multiple Assignment Randomized Trial to increase Reach and Impact of tobacco cessation treatment in Community Health Centers.

BACKGROUND: Tobacco use remains the leading cause of death and disability in the USA and is disproportionately concentrated among low socioeconomic status (SES) populations. Community Health Centers (CHCs) are a key venue for reaching low SES populations with evidence-based tobacco cessation treatment such as Quitlines. Electronic health record (EHR)-based interventions at the point-of-care, text messaging (TM), and phone counseling have the potential to increase Quitline reach and are feasible to implement within CHCs. However, there is a lack of data to inform how, when, and in what combination these strategies should be implemented. The aims of this cluster-randomized trial are to evaluate multi-level implementation strategies to increase the Reach (i.e., proportion of tobacco-using patients who enroll in the Quitline) and Impact (i.e., Reach × Efficacy [efficacy is defined as the proportion of tobacco-using patients who enroll in Quitline treatment that successfully quit]) and to evaluate characteristics of healthcare system, providers, and patients that may influence tobacco-use outcomes. METHODS: This study is a multilevel, three-phase, Sequential Multiple Assignment Randomized Trial (SMART), conducted in CHCs (N = 33 clinics; N = 6000 patients). In the first phase, clinics will be randomized to two different EHR conditions. The second and third phases are patient-level randomizations based on prior treatment response. Patients who enroll in the Quitline receive no further interventions. In phase two, patients who are non-responders (i.e., patients who do not enroll in Quitline) will be randomized to receive either TM or continued-EHR. In phase three, patients in the TM condition who are non-responders will be randomized to receive either continued-TM or TM + phone coaching. DISCUSSION: This project will evaluate scalable, multi-level interventions to directly address strategic national priorities for reducing tobacco use and related disparities by increasing the Reach and Impact of evidence-based tobacco cessation interventions in low SES populations. TRIAL REGISTRATION: This trial was registered at ClinicalTrials.gov (NCT03900767) on April 4th, 2019.

High Prevalence of Medication Discrepancies Between Home Health Referrals and Centers for Medicare and Medicaid Services Home Health Certification and Plan of Care and Their Potential to Affect Safety of Vulnerable Elderly Adults.

OBJECTIVES: To describe the prevalence of discrepancies between medication lists that referring providers and home healthcare (HH) nurses create. DESIGN: The active medication list from the hospital at time of HH initiation was compared with the HH agency's plan of care medication list. An electronic algorithm was developed to compare the two lists for discrepancies. SETTING: Single large hospital and HH agency in the western United States. PARTICIPANTS: Individuals referred for HH from the hospital in 2012 (N = 770, 96.3% male, median age 71). MEASUREMENTS: Prevalence was calculated for discrepancies, including medications missing from one list or the other and differences in dose, frequency, or route for medications contained on both lists. RESULTS: Participants had multiple medical problems (median 16 active problems) and were taking a median of 15 medications (range 1-93). Every participant had at least one discrepancy; 90.1% of HH lists were missing at least one medication that the referring provider had prescribed, 92.1% of HH lists contained medications not on the referring provider's list, 89.8% contained medication naming errors. 71.0% contained dosing discrepancies, and 76.3% contained frequency discrepancies. CONCLUSION: Discrepancies between HH and referring provider lists are common. Future work is needed to address possible safety and care coordination implications of discrepancies in this highly complex population.

Efficacy of a computerized simulation in promoting walking in individuals with diabetes.

BACKGROUND: Regular walking is a recommended but underused self-management strategy for individuals with type 2 diabetes mellitus (T2DM). OBJECTIVE: To test the impact of a simulation-based intervention on the beliefs, intentions, knowledge, and walking behavior of individuals with T2DM. We compared two versions of a brief narrated simulation. The experimental manipulation included two components: the presentation of the expected effect of walking on the glucose curve; and the completion of an action plan for walking over the next week. Primary hypotheses were (1) intervention participants' walking (minutes/week) would increase more than control participants' walking, and (2) change in outcome expectancies (beliefs) would be a function of the discrepancy between prior beliefs and those presented in the simulation. Secondary hypotheses were that, overall, behavioral intentions to walk in the coming week and diabetes-related knowledge would increase in both groups. METHODS: Individuals were randomly assigned to condition. Preintervention measures included self-reported physical activity (International Physical Activity Questionnaire [IPAQ] 7-day), theory of planned behavior-related beliefs, and knowledge (Diabetes Knowledge Test). During the narrated simulation we measured individuals' outcome expectancies regarding the effect of exercise on glucose with a novel drawing task. Postsimulation measures included theory of planned behavior beliefs, knowledge, and qualitative impressions of the narrated simulation. The IPAQ 7-day was readministered by phone 1 week later. We used a linear model that accounted for baseline walking to test the main hypothesis regarding walking. Discrepancy scores were calculated between the presented outcome and individuals' prior expectations (measured by the drawing task). A linear model with an interaction between intervention status and the discrepancy score was used to test the hypothesis regarding change in outcome expectancy. Pre-post changes in intention and knowledge were tested using paired t tests. RESULTS: Of 65 participants, 33 were in the intervention group and 32 in the control group. We excluded 2 participants from analysis due to being extreme outliers in baseline walking. After adjustment for baseline difference in age and intentions between groups, intervention participants increased walking by 61.0 minutes/week (SE 30.5, t(58 = 1.9, )P = .05) more than controls. The proposed interaction between the presented outcome and the individual's prior beliefs was supported: after adjustment for baseline differences in age and intentions between groups, the coefficient for the interaction was -.25, (SE 0.07, t(57 = -3.2, )P < .01). On average participants in both groups improved significantly from baseline in intentions (mean difference 0.66, t(62 = 4.5, )P < .001) and knowledge (mean difference 0.38, t(62 = 2.4, )P = .02). CONCLUSIONS: This study suggests that a brief, Internet-ready, simulation-based intervention can improve knowledge, beliefs, intentions, and short-term behavior in individuals with T2DM.