A Review of Public Healthcare Information Systems in Sri Lanka: Challenges, Benefits, and Future Research Directions

Abstract

Healthcare Information Systems (HIS) have become essential digital infrastructures for managing clinical, administrative, and public health data in modern healthcare environments. In Sri Lanka’s public healthcare sector, several HIS initiatives—including the Hospital Health Information Management System (HHIMS), District Health Information Software 2 (DHIS2), and the Electronic Indoor Morbidity and Mortality Return (eIMMR)—have been implemented to support health service delivery and national health reporting. While these systems have improved data availability and reporting efficiency, persistent challenges related to system fragmentation, limited interoperability, and organizational constraints continue to affect their overall effectiveness. This study presents a narrative review of public healthcare information systems implemented in Sri Lanka from an information system and applied computing perspective. A total of 25 Peer-reviewed journal articles, conference proceedings, and official government reports published between 2010 and 2025 were reviewed to examine system objectives, implementation outcomes, technological characteristics, and reported limitations. The review synthesizes evidence across hospital-, district-, and national-level HIS platforms. Findings indicate that existing HIS implementations have contributed to improved administrative efficiency, data quality, and support for public health policy development. However, limitations related to data governance, system integration, user capacity, and infrastructural disparities remain significant barriers to realizing their full potential. Based on the reviewed literature, future research directions are identified in interoperable system architectures, health data analytics, governance frameworks, and user-centered system design. This review provides an integrated overview of Sri Lanka’s public healthcare HIS landscape and offers insights relevant to other developing-country contexts. The results emphasize crucial needs for scalable analytics-driven decision support in public healthcare, standardized data models, and interoperable system designs from the standpoint of applied computing.