Deploying Smartphone-Based Artificial Intelligence Interventions to Community Health Workers in Low- and Middle-Income Countries: Recommendations for Product Developers, Implementing Partners, and Governments

Community health workers are crucial to public health efforts in low- and middle-income countries. Despite their contributions to improving health, they encounter numerous barriers in performing their day-to-day work. Artificial intelligence applications may offer a potential solution to some of these barriers. We examined the implementation of smartphone-based artificial intelligence interventions with community health workers in Uganda, Rwanda, and Nigeria, including how the interventions were developed, how they were used, and successes and challenges of their implementation. This research identified four key considerations for intervention developers, implementing partners, and governments, with respect to implementation of these applications, including: 1) empowering community health workers through professionalization, compensation, and training; 2) understanding the digital ecosystem and aligning with digitization efforts; 3) designing the solution to fit local context, ensuring the development and training of the intervention is applicable to the local environment; and, 4) managing data responsibly with adherence to data privacy and security regulations. This research describes the opportunities for filling gaps in supervisory support, improving diagnosis, and making work more efficient. Providing the community health workforce with digital tools replaces onerous, inefficient paper-based record keeping, enables opportunities for improved supervision, and facilitates decision-making in settings where these workers may be the only point of access to health services and information. Author SummaryCommunity health workers are often the backbone of the health workforce in low- and middle-income countries. Despite their contributions to community health improvement, they often face barriers and inefficiencies in delivering services. The expansion of smartphone-based artificial intelligence interventions may offer solutions. We examined the implementation of smartphone-based artificial intelligence interventions with community health workers in Uganda, Rwanda, and Nigeria. We found that smartphone-based artificial intelligence applications may help to replace onerous, inefficient paper-based record keeping, enable opportunities for improved supervision, and facilitate decision-making in settings where these individuals may be the only health service providers. This research also identified four key considerations for intervention developers, implementing partners, and governments, with respect to implementation of these applications, including: 1) empowering community health workers through professionalization, compensation, and training; 2) understanding the digital ecosystem and aligning with digitization efforts; 3) designing the solution to fit local context, ensuring the development and training of the intervention is applicable to the local environment; and, 4) managing data responsibly with adherence to data privacy and security regulations.