Data Quality and Integration Challenges in Public Healthcare Information Systems: A Scoping Review
Matendo Didas – College of ICT, University of Dar es Salaam.
Centre for ICT, St. John’s University of Tanzania, Dodoma, Tanzania
James Chambua – College of ICT, University of Dar es Salaam
Godfrey Justo – College of ICT, University of Dar es Salaam
Email: matendodidas@gmail.com
Abstract: The quality and interoperability of data from public health information systems (PHIS) are critical for effective decision-making yet remain a global challenge. This scoping review maps literature published between 2020 and 2025 to identify key issues related to data integration (DI) and data quality (DQ), along with their impacts and proposed solutions. The review followed the Joanna Briggs Institute (JBI) methodology and analyzed studies from PubMed, Scopus, Web of Science, and IEEE Xplore. Out of 1,250 records, 48 studies met the inclusion criteria, focusing on real-world public health applications such as surveillance, routine monitoring, and outbreak response. The findings reveal four interconnected domains of challenges categorized as technical, data quality, organizational and governance, and ethical and legal challenges. These issues were further intensified during the COVID-19 pandemic, exposing weaknesses in public health data systems. The consequences of these challenges include reduced trust in public health institutions, inefficient resource allocation, and limited real-time surveillance capabilities. The review concludes that addressing DQ and DI challenges requires a holistic approach that integrates technical, organizational, and ethical dimensions. Key recommendations include sustained investment in data infrastructure, adoption of flexible and standardized data frameworks, and the establishment of collaborative governance models. Emphasis on ethical data use and equity is essential to ensure inclusive and effective PHIS. This study provides a foundation for guiding future research, policy, and practice toward more resilient health information systems.
