Community-based screening for cardiovascular risk using a novel mHealth tool in rural Kenya

Abstract

BackgroundAn increasing burden of cardiovascular disease (CVD) in low-resource settings demands innovative public health approaches.ObjectivesTo design and test a novel mobile health (mHealth) tool for use by community health workers (CHWs) to identify individuals at high CVD risk who would benefit from education and/or pharmacologic interventions.MethodsWe designed and implemented a novel two-way mobile phone application, ‘AFYACHAT’, to rapidly screen for the CVD risk in rural Kenya. AFYACHAT collects and stores a short message system (SMS) text message data entered by a CHW on a subject’s age, sex, smoking, diabetes and systolic blood pressure, and returns as SMS text message the category of 10-year CVD risk: ‘GREEN’ (<10% 10 year risk of cardiovascular event), ‘YELLOW’ (from 10% to <20%), ‘ORANGE’ (from 20% to <30%), or ‘RED’ (≥30%). CHWs were equipped and trained to use an automated blood pressure device and the mHealth tool.ResultsFive CHWs screened 2865 subjects in remote rural communities in Kenya over a 22-month period (2015–2017). The median age of subjects was 50 (interquartile range 43–60) and 1581 (55%) were female. The point prevalence of hypertension (systolic blood pressure > 140 mmHg), diabetes and tobacco use were 23%, 3.2% and 22%, respectively. Overall, the 10-year risk of CVD among patients was <10% in 2778 (97%) patients, from 10% to <20% in 65 (2.3%), from 20% to <30% in 12 (0.4%) and ≥30% in 10 (0.2%).ConclusionsWe have developed a mHealth tool that can be used by CHWs to screen for CVD risk factors, demonstrating the proof of concept in rural Kenya.

Digital Solutions for Community and Primary Health Workers: Lessons From Implementations in Africa

“…One of the key challenges includes sporadic power supply and lack of power outlets ( 7 , 9 – 11 , 14 – 16 , 18 , 29 , 30 ). This impacted the ability to power devices, use applications on mobile phones, central database systems interruption, and server downtime during power interruptions ( 20 , 23 , 31 , 32 ). Another notable impact was variation in data reporting, delayed responses, and duplicative work ( 24 , 32 ).…”

“…Studies conducted in Zambia, Tanzania, Uganda, Nigeria and Ethiopia reported use of solar lamps/chargers and power banks to recharge the smart phones ( 2 , 3 , 7 , 8 , 23 , 26 ). In some other settings like Kenya, community health workers used paper to record values, and later sent them when power was restored ( 24 , 31 ). In some studies, it was reported that there were insurgent attacks and cases of phone theft.…”

“…Poor network connectivity was another common challenge which was managed by using alternative network providers or use of design changes to the user interface that had an offline functionality design to ensure operation during network downtime and the ability to save forms for later ( 13 , 20 , 23 , 27 , 31 , 40 , 43 – 46 ).…”

“…Also in West Nile, Uganda, a pilot mHealth intervention designed to increase coverage of Intermittent Preventive Treatment of Malaria in pregnancy, integrated an SMS platform into an already existing platform ( 68 ). Sometimes, the integration encompassed leveraging on the services of the community health workers, themselves, in rural settings ( 31 ). It was also necessary to ensure that these digital initiatives were in line with existing policies and tailored to fit local contexts ( 23 , 33 , 51 , 56 ).…”

Digital disparities, complexity and patient safety: in this issue

“…In a month when Public Health England has launched its online tool to predict your heart age,12 we publish an article by Mannik et al .,13 about how community health workers in rural Kenya have used a mobile app to screen for cardiovascular disease and risk.…”