Use of Human-Centered Design Methodology to Develop a Digital Toolkit to Optimize Heart Failure Guideline-Directed Medical Therapy.

BACKGROUND: Guideline-directed medical therapies (GDMTs) improve quality of life and health outcomes for patients with heart failure (HF). However, GDMT utilization is suboptimal among patients with HF. OBJECTIVE: The aims of this study were to engage key stakeholders in semistructured, virtual human-centered design sessions to identify challenges in GDMT optimization posthospitalization and inform the development of a digital toolkit aimed at optimizing HF GDMTs. METHODS: For the human-centered design sessions, we recruited (a) clinicians who care for patients with HF across 3 hospital systems, (b) patients with HF with reduced ejection fraction (ejection fraction ≤ 40%) discharged from the hospital within 30 days of enrollment, and (c) caregivers. All participants were 18 years or older, English speaking, with Internet access. RESULTS: A total of 10 clinicians (median age, 37 years [interquartile range, 35-41], 12 years [interquartile range, 10-14] of experience caring for patients with HF, 80% women, 50% White, 50% nurse practitioners) and three patients and one caregiver (median age 57 years [IQR: 53-60], 75% men, 50% Black, 75% married) were included. Five themes emerged from the clinician sessions on challenges to GDMT optimization (eg, barriers to patient buy-in). Six themes on challenges (eg, managing medications), 4 themes on motivators (eg, regaining independence), and 3 themes on facilitators (eg, social support) to HF management arose from the patient and caregiver sessions. CONCLUSIONS: The clinician, patient, and caregiver insights identified through human-centered design will inform a digital toolkit aimed at optimizing HF GDMTs, including a patient-facing smartphone application and clinician dashboard. This digital toolkit will be evaluated in a multicenter, clinical trial.

The Virtual Inclusive Digital Health Intervention Design to Promote Health Equity (iDesign) Framework for Atrial Fibrillation: Co-design and Development Study.

BACKGROUND: Smartphone ownership and mobile app use are steadily increasing in individuals of diverse racial and ethnic backgrounds living in the United States. Growing adoption of technology creates a perfect opportunity for digital health interventions to increase access to health care. To successfully implement digital health interventions and engage users, intervention development should be guided by user input, which is best achieved by the process of co-design. Digital health interventions co-designed with the active engagement of users have the potential to increase the uptake of guideline recommendations, which can reduce morbidity and mortality and advance health equity. OBJECTIVE: We aimed to co-design a digital health intervention for patients with atrial fibrillation, the most common cardiac arrhythmia, with patient, caregiver, and clinician feedback and to describe our approach to human-centered design for building digital health interventions. METHODS: We conducted virtual meetings with patients with atrial fibrillation (n=8), their caregivers, and clinicians (n=8). We used the following 7 steps in our co-design process: step 1, a virtual meeting focused on defining challenges and empathizing with problems that are faced in daily life by individuals with atrial fibrillation and clinicians; step 2, a virtual meeting focused on ideation and brainstorming the top challenges identified during the first meeting; step 3, individualized onboarding of patients with an existing minimally viable version of the atrial fibrillation app; step 4, virtual prototyping of the top 3 ideas generated during ideation; step 5, further ranking by the study investigators and engineers of the ideas that were generated during ideation but were not chosen as top-3 solutions to be prototyped in step 4; step 6, ongoing engineering work to incorporate top-priority features in the app; and step 7, obtaining further feedback from patients and testing the atrial fibrillation digital health intervention in a pilot clinical study. RESULTS: The top challenges identified by patients and caregivers included addressing risk factor modification, medication adherence, and guidance during atrial fibrillation episodes. Challenges identified by clinicians were complementary and included patient education, addressing modifiable atrial fibrillation risk factors, and remote atrial fibrillation episode management. Patients brainstormed more than 30 ideas to address the top challenges, and the clinicians generated more than 20 ideas. Ranking of the ideas informed several novel or modified features aligned with the Theory of Health Behavior Change, features that were geared toward risk factor modification; patient education; rhythm, symptom, and trigger correlation for remote atrial fibrillation management; and social support. CONCLUSIONS: We co-designed an atrial fibrillation digital health intervention in partnership with patients, caregivers, and clinicians by virtually engaging in collaborative creation through the design process. We summarize our experience and describe a flexible approach to human-centered design for digital health intervention development that can guide innovative clinical investigators.

Forming Cardi-OH: A Statewide Collaborative to Improve Cardiovascular Health in Ohio.

Background Cardiovascular risk factor control is challenging, especially in disadvantaged populations. However, few statewide efforts exist to tackle this challenge. Therefore, our objective is to describe the formation of a unique statewide cardiovascular health collaborative so others may learn from this approach. Methodology With funding from the Ohio Department of Medicaid's Ohio Medicaid Technical Assistance and Policy Program, we used a collective impact model to link the seven medical schools in Ohio, primary care clinics across the state, the Ohio Department of Medicaid, and Ohio's Medicaid Managed Care Plans in a statewide health improvement collaborative for expanding primary care capacity to improve cardiovascular health in Ohio. Results Initial dissemination activities for primary care teams included a virtual case-based learning series focused on hypertension and social determinants of health, website resources, a monthly newsletter with clinical tips, webinars, and in-person conferences. The collaborative is aligned with a separately funded hypertension quality improvement project for paired implementation. Conclusions The collective impact model is a useful framework for developing a statewide collaborative focused on the dissemination and implementation of evidence-based best practices for cardiovascular health improvement and disparity reduction. Statewide collaboratives bringing payers, clinicians, and academic partners together have the potential to substantially impact cardiovascular health.

Quantifying the contribution of lipoprotein(a) to all apoB containing particles.

BACKGROUND: Elevated lipoprotein (a) [Lp(a)] is an independent risk factor for atherosclerotic cardiovascular disease (ASCVD). As clinical LDL cholesterol [LDL-C] incorporates cholesterol from Lp(a) [Lp(a)-C], there is interest in quantifying the contribution of Lp(a)-C to LDL-C given implications for risk assessment, diagnosis, and treatment. Estimating Lp(a)-C is subject to inaccuracies; measuring Lp(a) particle number [Lp(a)-P] is more accurate. OBJECTIVE: To capture how Lp(a) contributes to the concentration of atherogenic particles, we demonstrate a particle-based approach using readily available measures of Lp(a)-P and apolipoprotein B (apoB). METHODS: Using the Very Large Database of Lipids (VLDbL), we compared Lp(a)-P (nmol/L) with all apoB containing particles ("apoB-P"). apoB-P was calculated by converting apoB mass to molar concentration using the preserved molecular weight of apoB100 (512 kg/mol). We calculated the percentage of Lp(a)-P relative to apoB-P by Lp(a)-P deciles and stratified by triglycerides, LDL-C, and non-HDL-C. RESULTS: 158,260 patients from the VLDbL were included. The fraction Lp(a)-P/apoB-P increased with rising Lp(a)-P. Lp(a)-P comprised on average 3% of apoB containing particles among the study population and 15% at the highest Lp(a)-P decile. Lp(a)-P/apoB-P decreased at higher levels of triglycerides and LDL-C owing to larger contributions from VLDL and LDL. CONCLUSIONS: We demonstrate a particle-based approach to quantify the contribution of Lp(a) to all apoB-containing particles using validated and widely available clinical assays. This approach keeps in line with recommendations to move away from mass-based measurements of Lp(a) and prioritize more accurate particle-based measurements. Future research applying this method could define clinically meaningful thresholds and inform use in risk assessment and management.

Supervised exercise therapy for patients with peripheral artery disease: Clinical update and pathways forward.

Peripheral artery disease (PAD) is an atherosclerotic vascular disease resulting in pervasive morbidity and mortality, particularly among older adults. One first-line therapy to improve symptoms, function, and clinical outcomes in PAD is supervised exercise therapy (SET), which is based primarily on a structured, start-and-stop walking protocol and is often implemented in cardiac rehabilitation programs. SET is supported by a Class IA guideline for patients with symptomatic PAD; however, despite the effectiveness of SET and the 2017 CMS decision to cover SET for PAD, challenges of awareness, access, and implementation of SET persist. Recent efforts to address these challenges include digital health and hybrid approaches to SET that may minimize barriers to care by delivering SET in more innovative, flexible formats. Further study is needed to understand barriers, improve awareness, and implement SET in more equitable and accessible ways.