Systems Interoperability for Pandemic Response: Evidence from the Philippines’ COVID-19 Management

Background: The Philippines reported its initial confirmed case of COVID-19 on January 30, 2020. In response, the government implemented a science-based, multi-agency governance framework led by the Inter-Agency Task Force for the Management of Emerging Infectious Diseases (IATF). A crucial element of this response was data-driven decision-making, supported by digital systems across surveillance, laboratories, facilities, and local government units (LGUs). Despite daily situation reports from the Department of Health (DOH), retrospective analysis revealed substantial underreporting during the early stages of the pandemic (e.g., 178 versus 1,584 total cases on March 17, 2020), indicating reporting delays and systemic fragmentation. The IATF established the Sub-Technical Working Group on Information and Communications Technology (ICT). Within this group, Workstream 4 (WS4) focused on End-to-End Data Integration to improve interoperability at the national level, supported by the Standards and Interoperability Lab–Asia (SIL-Asia).Objective: This paper documents and assesses an interoperability strategy that (i) unified diverse COVID-19 information systems using HL7 FHIR, (ii) tracked integration progress with a scorecard aligned to a maturity framework, and (iii) evaluated the impact on the timeliness of case confirmation from March 2020 to March 2021.Methods: WS4 used a combined monitoring approach that blends a simple scorecard with a LISI-type maturity pathway. Interoperability was measured as progress across six checkable points built into developer workflows: (1) API documentation provided; (2) data dictionaries mapped; (3) ETL templates supplied; (4) system changes made; (5) testing of integration; and (6) actual technical integration (successful data exchange based on agreed profiles). Each point was scored 0 (not started), 1 (in progress), or 2 (finished). Scores for each system pair were added, averaged across pairs, and scaled to a 0–10 score for the ecosystem.Technical interventions included a national HAPI FHIR sandbox for conformance testing, a CSV-to-FHIR converter to connect spreadsheet-based data into FHIR workflows (e.g., to COVID Kaya), and a locally tailored Philippine COVID-19 HL7 FHIR Implementation Guide (IG) limited to essential resources and fields mapped to the DOH Minimum Data Set. Organizational interventions comprised peer-to-peer technical clinics, targeted consultations, and capacity-building led by SIL-Asia. Impact was evaluated by analyzing DOH timelines for (a) symptom onset to specimen collection, (b) specimen collection to lab result release, and (c) result release to official case confirmation.Results: At baseline (June 2020), the ecosystem interoperability score was 3.0, reflecting early-stage activity focused on documentation and initial mappings. After staged interventions and ongoing monitoring, the score increased to 9.0 by October 2020, with nearly all priority systems exchanging data per the IG.Timeliness greatly improved during the same period. The average time from symptom onset to official confirmation dropped from 44 days (June 2020) to 6 days (October 2020), an 80% decrease. The most significant change was in the interval between lab result release and official confirmation, which fell from 22 days to 3 days (87% decrease), reflecting progress in data management, reconciliation, and automated exchanges across integrated systems. Improvements in onset-to-collection (~13 days) and collection-to-result (~9 days) were supported by increased laboratory capacity and better workflows.Discussion: The Philippine experience demonstrates that large-scale interoperability during a crisis needs both governance and technical strategies. A dedicated integration workstream (WS4), backed by clear mandates and escalation paths, facilitated quick resolution of issues and focused on integration. A “minimum, then mature” approach—using a limited HL7 FHIR IG and DOH Minimum Data Set—lowered entry barriers, while the scorecard showed incremental improvements before full production integration. Tools that accommodated diversity (e.g., spreadsheet bridges for LGUs and GIDAs) ensured fairness in participation and complete surveillance data. Interoperability labs (SIL-Asia) served as ongoing technical and knowledge hubs, offering sandboxes, validators, reference adapters, and capacity-building to reduce risks and speed up integration.Limitations: Gains in timeliness primarily result from interoperability, process learning, and system capacity expansions such as laboratory scale-up. The framework focuses on verifiable technical milestones; future efforts could incorporate routine data quality metrics (e.g., completeness, validity, code-set adherence) and outcome analytics (e.g., impacts on contact tracing effectiveness).Conclusions: A structured, checkpoint-based scorecard aligned with a maturity pathway, supported by targeted tools and dedicated governance, accelerated interoperability during a public health emergency, and translated into measurable improvements in reporting timeliness. Institutionalizing these capabilities—such as standing IGs, national sandboxes, adapters for low-resource settings, and interoperability labs—will strengthen preparedness and resilience for future pandemics.