SPHERES is a health service research trial in the Indonesian primary care system designed to improve health system performance using a structured data-driven action model. The intervention empowers district health leaders to make data-informed decisions that will enhance outcomes across maternal, child, infectious, and non-communicable disease programs.
The SPHERES (Scalable Public Health Empowerment, Research and Education Sites) study is a stepped-wedge health service research trial designed to assess the impact of a complex intervention to enhance the performance of Indonesia's primary health care system through an integrated package of digital health tools to enhance data interoperability, human resource and performance improvement, data-driven decision-making, and changes in work culture toward information-based decision-making, actions, and accountability. The central innovation lies in the "prescription for action" approach, wherein district health managers and heads of primary healthcare centers (PHC) create structured monthly prescriptions that describe actions to be taken to improve primary health care informed by real-time health data visualized on interactive dashboards. These prescriptions are tailored to address gap in priority service delivery challenges including gaps in preventive and promotive care - such as low coverage or quality of antenatal, intrapartum, or postnatal care, or missed opportunities for hepatitis B prevention in pregnancy, or gaps in overall diagnosis and treatment of tuberculosis, or gaps in overall screening and diagnosis and treatment of hypertension or diabetes, - and are grounded in both epidemiological insight and health systems analysis. As a cluster-randomized stepped-wedge health service trial in the Indonesian primary care system, SPHERES involve multiple primary healthcare centers (PHCs) as the unit of intervention across two districts: West Lombok (West Nusa Tenggara Province) and Purbalingga (Central Java Province). At regular intervals (approximately every 4 months), new clusters (approximately 25% of the total number of PHCs in the district) are transitioned from control to intervention status, until all sites receive the SPHERES intervention within 16 months. This phased approach allows for rigorous evaluation while ensuring equitable access to the program. The intervention package includes: (1) establishment of Public Health Data Theaters as training centers for the active use of data for decision-making using interactive dynamic dashboards, public health data rounds, prescriptions for action for precision public health, digital report cards, and team-based care, (2) deployment of Sustainable Scaling Teams to engage districts in developing the essential technical and management skills for digital ecosystems, and (3) establish ecosystems of interoperable data at the district level to support curative, preventive, and promotive care delivery by frontline health workers. Thus, the intervention will be implemented over 16 months, with approximately 25% of PHCs transitioning every quarter from control to intervention in monthly waves, starting August 2025, with all PHCs receiving the intervention by August 2026. To support high-fidelity implementation, at each phase of the stepped-wedge, each cluster undergoes a two-phase transformation, a pre-intervention digital readiness phase, followed by the intervention interventions, i.e. the "prescriptions for action" phase. The preparatory step focuses on strengthening digital infrastructure and practices at the PHC level, including standardizing electronic health record inputs, and ensuring interoperability across digital health platforms. Sequencing this digitalization phase ahead of the "prescriptions for action" phase enhances the fidelity and compliance for managerial and behavioral actions that may be included within the "prescriptions for action" intervention. SPHERES targets improvements in coverage, quality, and outcomes across three priority domains: maternal and child health (including immunization and stunting), infectious disease (tuberculosis and hepatitis B), and non-communicable diseases (diabetes and hypertension). The study will assess impacts on service uptake (e.g., ANC 6 coverage, quality of care, diabetes screening), clinical outcomes (e.g., neonatal mortality, TB treatment success, Hepatitis B vertical transmission), and system-level indicators (e.g., prescription compliance, data use in decision-making). Embedded within the project is a robust capacity-building component for health workers and program managers, along with qualitative assessments of acceptability, feasibility, and perceived value. SPHERES is expected to produce evidence for improving PHC service quality and responsiveness across Indonesia. By combining routine data analytics with a structured decision-support mechanism, the intervention aims to institutionalize active data use at the district level. Findings from SPHERES are expected to inform Indonesia's Ministry of Health Digital Roadmap and broader digital health transformation strategy and offer generalizable insights into how data empowerment combined with human resource management and change in work culture can drive system-wide improvements in low- and middle-income countries.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
HEALTH_SERVICES_RESEARCH
Masking
NONE
Enrollment
1,750,000
A system-level intervention consisting of: * a digital dashboard displaying local health services, outcome indicators, and operational data in a secure Public Health Data Theater; * structured monthly prescription guides targeting service improvements across three priority program areas; * monthly performance monitoring with district health leaders. The intervention is applied at the PHC level, all supported by digital capacity building, district-level deployment of implementation teams, and intersectoral secure health data exchange.
Purbalingga District Health Office
Purbalingga, Central Java, Indonesia
West Lombok District Health Office
Gerung, West Nusa Tenggara, Indonesia
Difference in neonatal mortality rate between intervention and control periods
Neonatal mortality per 1,000 live births, calculated using health facility and civil registration data, and community household sampling surveys
Time frame: Baseline up to 16 months, with data collected monthly at each site (i.e. baseline, at the end of month 1, at the end of month 2, and so on until at the end of month 16)
Difference in complete antenatal care (ANC 6) visit coverage between intervention and control periods
Percentage of pregnant women completing ≥6 ANC visits calculated using health facility data, paper based registry, and/or community household sampling surveys
Time frame: Baseline up to 16 months, with data collected monthly at each site (i.e. baseline, at the end of month 1, at the end of month 2, and so on until at the end of month 16)
Difference in complete basic childhood immunization coverage between the intervention and control period
Proportion of children aged 12-23 months receiving all recommended basic childhood vaccines according to Indonesian Pediatric Society guidelines using health facility data, paper based registry, and/or community household sampling surveys
Time frame: Baseline up to 16 months, with data collected monthly at each site (i.e. baseline, at the end of month 1, at the end of month 2, and so on until at the end of month 16)
Difference in TB treatment success rate between intervention and control periods
Percentage of new bacteriologically confirmed TB patients with documented treatment success (cure or completion) calculated using health facility data
Time frame: Baseline up to 16 months, with data collected monthly at each site (i.e. baseline, at the end of month 1, at the end of month 2, and so on until at the end of month 16)
Difference in screening coverage for diabetes mellitus among adults between the intervention and control periods
Proportion of adults aged ≥40 screened for random blood glucose or fasting blood glucose calculated using health facility data
Time frame: Baseline up to 16 months, with data collected monthly at each site (i.e. baseline, at the end of month 1, at the end of month 2, and so on until at the end of month 16)
Difference in the rate of vertical transmission of hepatitis B between intervention and control periods
Proportion of infants born to hepatitis B surface antigen (HBsAg)-positive mothers who test positive for HBsAg at 9 to 12 months of age. Data will be collected to evaluate the effectiveness of Tenofovir initiation, timely birth dose, routine childhood Hepatitis B vaccination, and HBIG administration as part of the vertical transmission prevention protocol.
Time frame: Baseline up to 16 months, with data collected monthly at each site (i.e. baseline, at the end of month 1, at the end of month 2, and so on until at the end of month 16)
Difference in the uptake of dashboard use among district health managers and heads of PHC
Proportion of monthly coordination meetings in which district health managers and heads of PHC accessed and used the SPHERES digital dashboard to review performance data and guide decision-making. Usage will be measured through system access logs and meeting documentation.
Time frame: Baseline up to 16 months, with data collected monthly at each site (i.e. baseline, at the end of month 1, at the end of month 2, and so on until at the end of month 16)
Difference in prescription-for-action implementation rate at the PHC
Proportion of prescriptions-for-action issued during Public Health Data Theater sessions that are completed by PHCs within one month. Data will be collected from district monitoring reports and PHC-level follow-up documentation.
Time frame: Baseline up to 16 months, with data collected monthly at each site (i.e. baseline, at the end of month 1, at the end of month 2, and so on until at the end of month 16)
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