Cardiovascular disease (CVD) causes 30% of deaths annually in Argentina and the evidence from high-income countries shows that this can reduced by half through effective screening, treatment, and control of risk factors. Despite the government providing universal health coverage, free health services, and essential medicines, less than 30% of eligible patients participate in the free chronic disease medication program and less than 10% are still participating one year after initiation. Gaps exist in the evidence for the effectiveness of proven interventions in the areas of comprehensive and cost-effective implementation strategies that engage multiple stakeholders, and interventions that include links between keys steps in the awareness, treatment, and control cascade. In prior work, we showed that community health workers (CHWs) improve screening and linkage to care using a validated mHealth screening tool and electronic scheduling apps but it did not lead to improved prescription or adherence to medications. We propose assessing if linking all steps in the care continuum will reduce absolute CVD risk through improvement of risk factor control. In order to fill three major gaps in evidence-based care we will assess implementation effectiveness through the following specific aims: (1) Use a Systems Level Framework to adapt and evaluate our multi-level intervention focusing on system structure, feedback loops, and key structural elements. We will engage all key stakeholders involved in the provision of primary care health services at the national, provincial, clinic, and community levels in a formative evaluation. The Comprehensive Framework for Implementation Research will identify adaptations prior to intervention implementation in a cluster randomized control trial (RCT) and to facilitate context-specific adaptations once the trial commences. (2) Assess the effectiveness and costs of a multicomponent strategy linking key aspects of the CVD care continuum, in a RCT with two arms across three provinces. The primary outcome is mean difference in absolute 10-year CVD risk. We will compare usual, paper based guidelines to the intervention, which is a global data management system linking digital mHealth screening tool for CHWs, electronic appointment scheduling, point of care testing (POCT) for lipids, clinical decision support for medication initiation, and a SMS reminder system for adherence to medications and life-style changes. (3) Assess the horizontal scaling of the mHealth tool, the sustainability, and reach of the intervention. After the RCT, the horizontal scaling and long-term sustainability of the intervention will be assessed using the REAIM framework. We will also evaluate the cost-effectiveness of the intervention using the Harvard CVD PREDICT Model calibrated to Argentina. Combined with the qualitative (formative evaluation) and quantitative (RCT), these results will provide a comprehensive understanding of the implementation of the intervention. All findings will be disseminated through a series of meetings with key stakeholders, publications in peer- reviewed journals, and key scientific meetings.
Control of hypertension, dyslipidemia, and smoking can reduce the high rates of cardiovascular disease (CVD) and related deaths by fifty percent with effective management of the treatment cascade involving screening, treatment initiation, and medication adherence. Despite the government of Argentina providing universal health care coverage, free health services, and free essential medications for the poorest segment of the population, very little improvement in overall CVD risk has resulted from these policies. Partnering with the Argentinian Ministry of Health, we will evaluate the effectiveness and cost-effectiveness of implementing a multi- component intervention that is global data management system linking digital mHealth screening tool for CHWs, electronic appointment scheduling, point of care testing (POCT) for lipids, clinical decision support for medication initiation, and a SMS reminder system for adherence to medications and life-style changes.