Data Access, User Engagement, and Interoperability Standards in Public Health Data Portals: Environmental Scan Study

Rapid digitalization has led to the generation of vast volumes of health data across diverse sources, including public health surveillance, electronic health records from hospitals, primary care facilities, and telemedicine. However, it often remains fragmented across multiple domains and systems due to siloed data collection practices and a lack of interoperability standards, limiting its potential to generate actionable public health insights.

In this study, we examined publicly available health data portals and assessed their scope, user engagement features, and implementation of interoperability standards.

We conducted an environmental scan to profile publicly available health data portals. We identified portals through systematic web searches, expert consultation using the Delphi technique, and snowball sampling from initial sources. We assessed each portal for the type of data hosted, the scope of user engagement, and the implementation of interoperability standards (Systematized Nomenclature of Medicine Clinical Terms [SNOMED CT]) or adopted Fast Healthcare Interoperability Resources (FHIR) as a data exchange standard.

We identified 17 data portals in total, of which 9 (53%) hosted global data and 1 (6%) hosted regional data. Portals hosted data across diverse domains including communicable diseases and noncommunicable diseases, maternal and child health, injuries, and others. Most portals supported basic user interactions such as data querying (n=15, 88%) and downloading (n=15, 88%), but none offered in-portal analytics. While 3 (18%) portals used International Classification of Diseases (ICD) coding systems, none implemented SNOMED CT or adopted FHIR.

Our study highlighted substantial fragmentation and a lack of interoperability across health data portals, which limits the ability to conduct integrated analysis and obtain comprehensive public health insights. Realizing the full potential of health data will require accessibility and interoperability, intelligent analytics, and seamless integration across domains.