Tailoring implementation strategies for scale-up: Preparing to take the Med-South Lifestyle program to scale statewide.

Background: Tailoring implementation strategies for scale-up involves engaging stakeholders, identifying implementation determinants, and designing implementation strategies to target those determinants. The purpose of this paper is to describe the multiphase process used to engage stakeholders in tailoring strategies to scale-up the Med-South Lifestyle Program, a research-supported lifestyle behavior change intervention that translates the Mediterranean dietary pattern for the southeastern US. Methods: Guided by Barker et al. framework, we tailored scale-up strategies over four-phases. In Phase 1, we engaged stakeholders from delivery systems that implement lifestyle interventions and from support systems that provide training and other support for statewide scale-up. In Phase 2, we partnered with delivery systems (community health centers and health departments) to design and pilot test implementation strategies (2014-2019). In Phase 3, we partnered with both delivery and support systems to tailor Phase 2 strategies for scale-up (2019-2021) and are now testing those tailored strategies in a type 3 hybrid study (2021-2023). This paper reports on the Phase 3 methods used to tailor implementation strategies for scale-up. To identify determinants of scale-up, we surveyed North Carolina delivery systems (n = 114 community health centers and health departments) and elicited input from delivery and support system stakeholders. We tailored strategies to address identified determinants by adapting the form of Phase 2 strategies while retaining their functions. We pilot tested strategies in three sites and collected data on intermediate, implementation, and effectiveness outcomes. Findings: Determinants of scale-up included limited staffing, competing priorities, and safety concerns during COVID-19, among others. Tailoring yielded two levels of implementation strategies. At the level of the delivery system, strategies included implementation teams, an implementation blueprint, and cyclical small tests of change. At the level of the support system, strategies included training, educational materials, quality monitoring, and technical assistance. Findings from the pilot study provide evidence for the implementation strategies' reach, acceptability, and feasibility, with mixed findings on fidelity. Strategies were only moderately successful at building delivery system capacity to implement Med-South. Conclusions: This paper describes the multiphase approach used to plan for Med-South scale-up, including the methods used to tailor two-levels of implementation strategies by identifying and targeting multilevel determinants.

A comparison of live counseling with a web-based lifestyle and medication intervention to reduce coronary heart disease risk: a randomized clinical trial.

IMPORTANCE: Most primary care clinicians lack the skills and resources to offer effective lifestyle and medication (L&M) counseling to reduce coronary heart disease (CHD) risk. Thus, effective and feasible CHD prevention programs are needed for typical practice settings. OBJECTIVE: To assess the effectiveness, acceptability, and cost-effectiveness of a combined L&M intervention to reduce CHD risk offered in counselor-delivered and web-based formats. DESIGN, SETTING, AND PARTICIPANTS: A comparative effectiveness trial in 5 diverse family medicine practices in North Carolina. Participants were established patients, aged 35 to 79 years, with no known cardiovascular disease, and at moderate to high risk for CHD (10-year Framingham Risk Score [FRS], ≥10%). INTERVENTIONS: Participants were randomized to counselor-delivered or web-based format, each including 4 intensive and 3 maintenance sessions. After randomization, both formats used a web-based decision aid showing potential CHD risk reduction associated with L&M risk-reducing strategies. Participants chose the risk-reducing strategies they wished to follow. MAIN OUTCOMES AND MEASURES: The primary outcome was within-group change in FRS at 4-month follow-up. Other measures included standardized assessments of blood pressure, blood lipid levels, lifestyle behaviors, and medication adherence. Acceptability and cost-effectiveness were also assessed. Outcomes were assessed at 4 and 12 months. RESULTS: Of 2274 screened patients, 385 were randomized (192 counselor; 193 web): mean age, 62 years; 24% African American; and mean FRS, 16.9%. Follow-up at 4 and 12 months included 91% and 87% of the randomized participants, respectively. There was a sustained reduction in FRS at both 4 months (primary outcome) and 12 months for both counselor-based (-2.3% [95% CI, -3.0% to -1.6%] and -1.9% [95% CI, -2.8% to -1.1%], respectively) and web-based groups (-1.5% [95% CI, -2.2% to -0.9%] and -1.7% [95% CI, -2.6% to -0.8%] respectively). At 4 months, the adjusted difference in FRS between groups was -1.0% (95% CI, -1.8% to -0.1%) (P = .03), and at 12 months, it was -0.6% (95% CI, -1.7% to 0.5%) (P = .30). The 12-month costs from the payer perspective were $207 and $110 per person for the counselor- and web-based interventions, respectively. CONCLUSIONS AND RELEVANCE: Both intervention formats reduced CHD risk through 12-month follow-up. The web format was less expensive. TRIAL REGISTRATION: clinicaltrials.gov Identifier: NCT01245686.

The effect of a decision aid intervention on decision making about coronary heart disease risk reduction: secondary analyses of a randomized trial.

BACKGROUND: Decision aids offer promise as a practical solution to improve patient decision making about coronary heart disease (CHD) prevention medications and help patients choose medications to which they are likely to adhere. However, little data is available on decision aids designed to promote adherence. METHODS: In this paper, we report on secondary analyses of a randomized trial of a CHD adherence intervention (second generation decision aid plus tailored messages) versus usual care in an effort to understand how the decision aid facilitates adherence. We focus on data collected from the primary study visit, when intervention participants presented 45 minutes early to a previously scheduled provider visit; viewed the decision aid, indicating their intent for CHD risk reduction after each decision aid component (individualized risk assessment and education, values clarification, and coaching); and filled out a post-decision aid survey assessing their knowledge, perceived risk, decisional conflict, and intent for CHD risk reduction. Control participants did not present early and received usual care from their provider. Following the provider visit, participants in both groups completed post-visit surveys assessing the number and quality of CHD discussions with their provider, their intent for CHD risk reduction, and their feelings about the decision aid. RESULTS: We enrolled 160 patients into our study (81 intervention, 79 control). Within the decision aid group, the decision aid significantly increased knowledge of effective CHD prevention strategies (+21 percentage points; adjusted p<.0001) and the accuracy of perceived CHD risk (+33 percentage points; adjusted p<.0001), and significantly decreased decisional conflict (-0.63; adjusted p<.0001). Comparing between study groups, the decision aid also significantly increased CHD prevention discussions with providers (+31 percentage points; adjusted p<.0001) and improved perceptions of some features of patient-provider interactions. Further, it increased participants' intentions for any effective CHD risk reducing strategies (+21 percentage points; 95% CI 5 to 37 percentage points), with a majority of the effect from the educational component of the decision aid. Ninety-nine percent of participants found the decision aid easy to understand and 93% felt it easy to use. CONCLUSIONS: Decision aids can play an important role in improving decisions about CHD prevention and increasing patient-provider discussions and intent to reduce CHD risk.

Designing and implementing a comparative effectiveness study of two strategies for delivering high quality CHD prevention: methods and participant characteristics for the Heart to Health study.

BACKGROUND: Although lifestyle and medications are effective for coronary heart disease (CHD) risk reduction, few studies have examined the comparative effectiveness of various strategies for delivering high quality CHD risk reduction. In this paper, we report on the design and baseline characteristics of participants for just such a trial. METHODS: We conducted a randomized trial of the same lifestyle and medication intervention delivered in two alternate formats: counselor-delivered or web-based. The trial was conducted at 5 diverse practices in a family medicine research network and included men and women age 35-79 who were at high risk of CHD events based on 10-year predicted Framingham risk of ≥10% or a known history of cardiovascular disease. After individual-level randomization, participants in both arms received a decision aid plus four intensive intervention visits and 3 maintenance visits over 12 months. The primary outcome was change in 10-year predicted CHD risk among patients without prior cardiovascular disease. Secondary outcomes, measured among all participants, included changes in CHD risk factors, cost-effectiveness, and acceptability at 4 and 12-month follow-up. RESULTS: We randomized 489 eligible patients: 389 without and 100 with a known history of cardiovascular disease. Mean age was 62.3. 75% were white, 25% African-American. 45% had a college education. 88% had health insurance. Mean 10-year predicted CHD risk was 16.9%. CONCLUSION: We have successfully recruited a diverse sample of practices and patients that will provide a rich sample in which to test the comparative effectiveness of two strategies to implement high quality CHD prevention.

A randomized trial of an intervention to improve use and adherence to effective coronary heart disease prevention strategies.

BACKGROUND: Efficacious strategies for the primary prevention of coronary heart disease (CHD) are underused, and, when used, have low adherence. Existing efforts to improve use and adherence to these efficacious strategies have been so intensive that they are impractical for clinical practice. METHODS: We conducted a randomized trial of a CHD prevention intervention (including a computerized decision aid and automated tailored adherence messages) at one university general internal medicine practice. After obtaining informed consent and collecting baseline data, we randomized patients (men and women age 40-79 with no prior history of cardiovascular disease) to either the intervention or usual care. We then saw them for two additional study visits over 3 months. For intervention participants, we administered the decision aid at the primary study visit (1 week after baseline visit) and then mailed 3 tailored adherence reminders at 2, 4, and 6 weeks. We assessed our outcomes (including the predicted likelihood of angina, myocardial infarction, and CHD death over 10 years (CHD risk) and self-reported adherence) between groups at 3 month follow-up. Data collection occurred from June 2007 through December 2009. All study procedures were IRB approved. RESULTS: We randomized 160 eligible patients (81 intervention; 79 control) and followed 96% to study conclusion. Mean predicted CHD risk at baseline was 11.3%. The intervention increased self-reported adherence to chosen risk reducing strategies by 25 percentage points (95% CI 8% to 42%), with the biggest effect for aspirin. It also changed predicted CHD risk by -1.1% (95% CI -0.16% to -2%), with a larger effect in a pre-specified subgroup of high risk patients. CONCLUSION: A computerized intervention that involves patients in CHD decision making and supports adherence to effective prevention strategies can improve adherence and reduce predicted CHD risk.