| Partners | Indonesian Organisations | ||
| Yayasan Institut Pengembangan Suara Mitra / Summit Institute for Development Faculty of Engineering University of Mataram Research Center for Public Health and Nutrition, Health Research Organization, BRIN Faculty of Medicine and Health Sciences University of Mataram (FMHS-UNRAM) | |||
| Australian Organisations | |||
| Commonwealth Scientific and Industrial Research Organisation | |||
| Lead Researcher/s (Principal Investigator) | Yuni Setiyawati | ||
| Researchers | Budi Irmawati dr. Wahyu Sulistya Affarah, MPH., Sp. KL(K) Suparmi, SKM., MKM Marlien Varnfield Giri Wahyu Wiriasto Ario Yudo Husodo Gibran Satya Nugraha | ||
| Research location | West Java West Nusa Tenggara | ||
| Keyword | Artificial intelligence (AI), neural networks, FHIR, team based care, analytic dashboard, primary health care | ||
| Principal Organisation | Yayasan Institut Pengembangan Suara Mitra / Summit Institute for Development | ||
| Research summary | Our proposed activity expands the agenda of digitizing integrated primary health care using artificial intelligence (AI), and fosters equitable collaborative research partnerships between Indonesia and Australia by providing equal opportunities for researchers from both countries to contribute their expertise. Recently, by using Fast Healthcare Interoperability Resources (FHIR), SID created a team-based care model in 4 districts in Indonesia (soon to be 10 in 2027) that covered 10 million persons. As a core partner of the MoH to accelerate integrated primary healthcare (ILP), SID collaborates with the Digital Transformation Office (DTO) to digitize the workflows of frontline health workers, enabling connections between the community and referral systems via the FHIR data ecosystem including SATUSEHAT. This includes a dashboard for local area monitoring and decision making. SID and partners have developed initial predictors of health system performance, and for this proposal 3 features will be added with AI analytics: (1) Predict care-seeking tendencies (revisits, compliance, etc.) for individuals, families, and communities as clients. (2) Determine the likelihood of interventions and treatment combinations that predict health outcomes. (3) Predict the performance of health workers for high quality service delivery. This will be done in 3 districts in West Nusa Tenggara and West Java utilizing supervised-learning with deep neural networks as AI tools, with the goal of anticipating and closing gaps in public health, facilitating technology and knowledge transfer to local authorities, and developing a digital health monitoring system. The project aims to enhance indicators of reproductive, maternal, neonatal, and child health care quality and coverage, enabling districts and key partners to make informed decisions based on dashboard data at the primary level. SID actively engages community members in every phase of research projects with the goal of democratization of knowledge creation, and we strive to ensure that all participants have a voice and receive benefits to help them flourish. Our approaches promote mutual respect, understanding and cooperation, and aim for more inclusive, equitable and impactful research that addresses the priority needs for both nations. |
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