As low- and middle-income countries transition from paper to digital systems, family planning programs can benefit from unprecedented opportunities to improve services. Investments in digital health tools have expanded exponentially, but information on what works—and what does not— remains limited and scattered. As investments have increased, digital applications and data fragmentation have proliferated, but stakeholders are moving towards more coordinated efforts to scale digital health solutions, support countries’ digital health infrastructure, and share evidence-based learnings.
This Digital Health Compendium enables users to explore case studies across a range of digital health technologies used to enhance family planning programs mainly in sub-Saharan Africa, but also in other regions of the world. Digital health applications in family planning programs can be broadly classified as those affecting demand generation, service delivery, supply chain management, and the policy and enabling environment. In many low- and middle-income countries, digital health innovations were adopted earlier in other health sectors, including HIV/AIDS, maternal and child health, and noncommunicable disease prevention and response. As a result, much of the impact evidence is likewise restricted to those sectors. To advance greater adoption of digital technology in family planning programs, more data and information on the challenges, opportunities, scalability, and results are needed. This compendium aims to consolidate emerging information and data on applications of digital technology in family planning programs to inform adoption and scale-up of successful approaches.
All of the case studies were submitted by the implementing organizations and include a description of the digital health intervention, program context, and, if available, important findings and lessons learned through rigorous evaluations or program data. The compendium facilitates a quick search for case studies based on the target user for digital health intervention, building block for the digital health enabling environment, family planning program classification, and country location. The case studies give policy and program decisionmakers insights on real-world applications of digital health, promising practices, challenges, and other lessons that can be applied to current and future programs.
Target Users: WHO classifies digital health interventions based on four categories of intended users. Learn more about WHO’s Classification of Digital Health Interventions.
Enabling Environment Building Blocks: The digital health enabling environment consists of interrelated building blocks that support a robust national digital health ecosystem and the individual applications and systems that work within it. Learn more in the National eHealth Strategy Toolkit from WHO and the International Telecommunications Union.
Family Planning Program Classification: Digital health applications in family planning programs can be broadly classified as those affecting demand generation, service delivery, supply chain management, and the policy and enabling environment.
A global Digital Acceleration Strategy (DAS) that leverages digital channels including social media, telemedicine, e-counseling, and e-pharmacy platforms to safely continue providing consumers with sexual and reproductive health and rights (SRHR) self-care information, connecting clients to care, and delivering high-quality products during the COVID-19 pandemic. Drawing on the learnings from the DAS, PSI will be expanding its digital work to a holistic sexual health and wellness offering through the launch of VIYA, PSI's first global lifestyle brand.
A free online referral platform in Kampala, Uganda that providers referrals between health facilities and from the community.
A 24/7 telemedicine service that offers convenient access to quality family planning, sexual reproductive health [KP1] and other health services in Uganda.
A telehealth approach that helps community health workers provide basic health services, sexual and reproductive health services, and products to communities in Uganda, Kenya, Tanzania, and Burundi.
Leveraging machine learning to forecast the utilization of vaccines and other pharmaceutical products.
Connecting ministries of health with frontline health workers via SMS