Poster ID
P-43
Poster Title
Beyond Counting Genomes: An Implementation-Science Monitoring and Evaluation Framework for Indonesia’s National Population Genomics Cohort
Authors
Ines I Atmosukarto PhD (Center for Biomedical and Health Genomics Indonesia Ministry of Health)
BGSI ecosystem (Indonesia Ministry of Health)
BGSI ecosystem (Indonesia Ministry of Health)
Abstract
Background. Indonesia’s Biomedical and Genome Science Initiative (BGSI) is scaling its Generasi Sehat (GenSet) population cohort toward ~40K participants across the 38 provinces of the world’s largest archipelagic nation, complementing hospital-based recruitment through BGSI’s disease-based Hubs and responding to the region’s under-representation in global genomic datasets. Conventional monitoring and evaluation (M&E) tracks recruitment and sequencing throughput as key performance indicators but poorly explains why targets are met or missed, constraining adaptive management at national scale.
Objective. We designed an M&E framework that measures Genset’s achievement and identifies the contextual determinants of GenSet’s implementation, aiming to produce a transferable model for national initiatives in resource-variable settings.
Framework. We built an integrated logical framework mapping the input–process–output–outcome–impact causal chain across the GenSet recruitment lifecycle, layering three lenses: the logframe as structural backbone; RE-AIM (Reach, Effectiveness, Adoption, Implementation, Maintenance) as measurement layer; and the Consolidated Framework for Implementation Research (CFIR) as diagnostic layer, identifying determinants (inner setting, outer setting, innovation characteristics, individuals, implementation process) underlying each result level. Indicators span recruitment, informed-consent fidelity, specimen and data quality, whole-genome sequencing QC, digital systems, ethics/ELSI, data security, and participant engagement.
Application. The framework operates as an indicator matrix pairing each logframe level with RE-AIM metrics and mapped CFIR determinants, letting program managers trace root causes of underperformance rather than merely record gaps, and feed findings into a continuous-improvement cycle. It is being field-evaluated in Q3/Q4 2026 across three contrasting provinces (DKI Jakarta, East Java, South Sulawesi), chosen to span health-system capacity, geography, and population diversity across western and eastern Indonesia.
Conclusion. Embedding implementation science into genomics M&E gives national initiatives, particularly those building representation for under-served Southeast Asian populations, a transferable, accountability-oriented instrument for responsible scale-up. We propose it as a candidate reference model for other budding national initiatives.
Objective. We designed an M&E framework that measures Genset’s achievement and identifies the contextual determinants of GenSet’s implementation, aiming to produce a transferable model for national initiatives in resource-variable settings.
Framework. We built an integrated logical framework mapping the input–process–output–outcome–impact causal chain across the GenSet recruitment lifecycle, layering three lenses: the logframe as structural backbone; RE-AIM (Reach, Effectiveness, Adoption, Implementation, Maintenance) as measurement layer; and the Consolidated Framework for Implementation Research (CFIR) as diagnostic layer, identifying determinants (inner setting, outer setting, innovation characteristics, individuals, implementation process) underlying each result level. Indicators span recruitment, informed-consent fidelity, specimen and data quality, whole-genome sequencing QC, digital systems, ethics/ELSI, data security, and participant engagement.
Application. The framework operates as an indicator matrix pairing each logframe level with RE-AIM metrics and mapped CFIR determinants, letting program managers trace root causes of underperformance rather than merely record gaps, and feed findings into a continuous-improvement cycle. It is being field-evaluated in Q3/Q4 2026 across three contrasting provinces (DKI Jakarta, East Java, South Sulawesi), chosen to span health-system capacity, geography, and population diversity across western and eastern Indonesia.
Conclusion. Embedding implementation science into genomics M&E gives national initiatives, particularly those building representation for under-served Southeast Asian populations, a transferable, accountability-oriented instrument for responsible scale-up. We propose it as a candidate reference model for other budding national initiatives.
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