There is growing evidence of the value of digital technologies in promoting access to healthcare. The World Health Organisation (WHO) defines digital health as ‘a discrete functionality of digital technology that is applied to achieve health objectives’ [1]. The growing benefits of digital health are evident in patient management, research, and support to low cadre health workers, including community health volunteers, data collection and analysis, disease surveillance, among other uses. This is particularly important in low resource settings [2]. The value of digital technologies is appreciated for its ability to transcend geographical barriers while allowing real-time access to vital health services [3, 4].
There are national, regional and global guidelines and strategies towards utilisation of digital health to promote the achievement of universal health coverage. The WHO recently released the first set of guidelines [5], to this end, noting that digital health cannot replace non-functional health systems. Electronic health (e-health) readiness, is defined as ‘preparedness of healthcare institutions or communities for the anticipated change brought by programs related to information and communications technology’ [6]. Without e-readiness, implementation of programs is challenging. The current East African Community (EAC) Health Sector Investment Priority Framework (2018–2028) [7], in all the nine priority areas, stresses the regional block’s commitment to harness the potential of e-health on the road to universal health coverage. The EAC is composed of six partner states: Burundi, Kenya, Rwanda, United Republic of Tanzania, South Sudan and Uganda. The EAC health secretariat, through the ministers’ of health has called on countries to implement e-health strategies, with a recommendation that the East African Science and Technology Commission conduct a regional e- health readiness assessment [8].
Kenya launched its first National e-health Strategy in 2011(2011–2017) [9] with a rallying call to strengthen the health system and subsequently extend equity in health care to the poor and marginalized population. Five key areas were identified: telemedicine; electronic health records (health information systems); information for citizens; m-health (mobile technologies in health); and eLearning or distance education for health professionals. The strategy was followed by the National e-Health Policy (2016–2030) reiterating the creation of an enabling environment that promotes adoption, implementation and use of e-Health at all levels of service delivery. The e- Health strategy and policy were supported by the Kenya Health Policy (2014–2030) that in one of its objectives aims to “plan, design and install ICT infrastructure and software for the management and delivery of essential healthcare”. Although Kenya, and a few other countries in the EAC have implemented their national e-health strategies, lack of scientific evidence on the benefits of e-health interventions, how they work under different conditions within health systems remain major limitations to evidence-based policy and programming.
Kenya, is a leading economic and technology hub in the East African Community, contributing to 40% of the region’s Gross Domestic Product [10]. The country has one of the highest mobile phone penetration rates, worldwide [11]. Kenya’s growth in ICT has enabled the implementation of various digital innovations for the wellbeing of Kenyans. Such include mobile money--a vital financial solution to Kenyans across socio-economic groups. The health system has attempted to unlock the potential of technology in health. Numerous e-health innovations have been developed and implemented in the country but very few, if any, have gone to scale due to numerous challenges [11, 12]. There is need to identify and address the gaps in order to have clear directions on where to focus investment, in a coordinated manner. With limited research on technological innovations, the “quiet revolution” being experienced in Kenya faces the risk of wasted resources and potential creation of a digital health divide in health care.
Lately, Kenya has started to include ICT in national policy and planning for human resources for health. A broad range of legislation, regulations, and guidelines now exist that define the requirements of employment, and development of the health workforce as regards ICT. For instance, the National eHealth policy (2016–2030) recognizes the importance of ICT training and capacity building for health care workers as one of the key policy orientations. This policy orientation stipulates the integration of ICT into existing education and training at different levels; continuous education, sensitization and technical support to eHealth users. It also promotes continuous professional development (CPD) through e-learning [13]. Further, the scheme of service stipulates a certificate in computer application skills from a recognized institution as one of the minimum employment qualification for community health service personnel such as community health assistants and health care worker like clinical officers and nursing personnel [14,15,16]. To enforce this, National Continuing Professional Development Regulatory Framework, which provides a harmonized mechanism to address on-going professional development for Kenyan health care workers, outlines ICT as among other cross cadre CPD course that shall account to 10% of the required CPD points This provides healthcare workers who many not have had the opportunity to attain ICT knowledge and skill during the preservice education a platform to do so in relation to their profession duties.
Several digital pilot projects, involving low cadre health workers such as community health volunteers (CHVs) have demonstrated improvement in health service access and utilisation as a result of interventions focussing on CHVs. Within the WHO African region, the majority of implementation projects have mostly shown improvements in maternal and child health care as a result of better service delivery by CHVs, [17, 18]. In spite of the many pilot digital health projects implemented in SSA and in Kenya in particular, there is limited data on lessons learned especially in urban poor settings.
Building on lessons learned across SSA and with the aim of strengthen community health information and referral system at the community level in Kenya. We therefore developed an innovative digital application [19] that was also in response to a specific call for innovations to improve maternal and newborn wellbeing and survival in six counties identified as having the worst maternal and newborn health indicators; Bungoma, Garissa, Homa Bay, Kakamega, Turkana and Nairobi City [20]. Within Nairobi, informal settlements (slums) were identified as an area of focus given that they, compared to other areas of the city, have the very high maternal, newborn and child mortality rates [21]. The work was further informed by the government’s call to harness the role of digital technologies in health, as highlighted above [22]. As reported elsewhere [19], the mobile phone and web-application system we developed communicate over the internet to link the CHVs and health facilities. The mobile application used by the CHVs was a data capture module designed to replace selected paper based Ministry of Health (MoH) reporting tools. The functionality of the system was enhanced by the integration of a decision support function to enable identification of high risk cases and better management of community referrals. This was to further allow integration of patient data from the community to the health facility and enhanced better case management of referrals. Data quality was improved by validation checks that limited the submission of incomplete reports. The data from the community was accessed in real-time through the web by the health care providers and community health assistants (CHAs). Throughout the system development and implementation, CHVs views were included. The aim of this paper is to explore the experiences of CHVs, health workers and members of Sub-County Health Management Teams following implementation of the project in a bid to highlight challenges and opportunities presented by such processes in this and similar settings.
Theory of Change
As described elsewhere and demonstrated in Fig. 1, our theory of change was based on the assumption that a digitalized decision- support module of the application would enable the CHVs identify pregnant women, new mothers and their newborns exhibiting danger signs hence enable correct and timely decisions on referral for care in health facilities [19]. In essence, CHVs with more knowledge and skills on the needs of women and neonates at risk would be in a better position to care for community members in need of healthcare. As such, there would be an increase in the utilisation of mother and newborn services and a decrease in morbidity and mortality in the urban slums.
The inputs and processes described in Fig. 1 delivered the short and long term outcomes in addressing the delay in seeking maternal, newborn health (MNH) services. The digital application (m-PAMANECH) was developed to use a mobile and web-portal digital solutions that link the demand and supply of maternal and newborn services. The application had the official MoH 513 (household register), MoH 514 (service delivery log book) and MoH 100 (referral tool) used by the CHVs and the MoH 515 (CHA Summary) used by the CHAs. To improve the functionality and the utility of m-PAMANECH, a decision support tool (DST) was integrated in the application. The DST assisted the CHVs screen danger signs among pregnant women, newborns (0-28 days) and mothers in the immediate postpartum (within 6 weeks post birth). Consequently identifying cases that require immediate intervention by timely and correct referring to the health facility. Following customization of the application, m-PAMANECH was operationalized at the community and the five health centres providing MNCH services, by the recruitment and training of CHVs and health care workers. At the community level, a dedicated team of 50 trained CHVs accessed the m-PAMANECH application on the mobile handsets.
With the different access levels created for every user, the CHAs and the facilities accessed the submitted data remotely through the web. Allowing clinicians to treat referred patients and record their treatments and the sub-county community health strategy focal person and the CHAs, to follow-up on the CHVs through the system. The use of the application by the CHVs and the follow up by the CHAs ensured the intervention was delivered as expected, support was sustained and non- adherence to the intervention captured and documented. The effects of the inputs and immediate outcomes were assessed by examining the results in the population that the application was intended to serve. These results include increased level of MNH knowledge and expertise of the CHVs, timely care seeking decisions and enhanced care seeking behaviours ultimately increasing the utilization of MNH services, reduced complications and deaths.