Integration of Hospital-Level Clinical Data with National Administrative/Claims Data for Near-Real-Time Insight into Infectious Diseases
Main Applicant – Dr Ian Wee Liang En, Consultant, Department of Infectious Diseases/Infection Prevention and Epidemiology, Singapore General Hospital (SGH)

Surveillance systems play a central role in supporting data-driven policies for public health intervention.

In recent years, data that are electronically and routinely collected have emerged as convenient sources of surveillance data. During the COVID-19 pandemic, epidemiological data was crucial in offering insight into disease burden, at-risk groups and potential utility of novel therapeutics; however, delays in data collection and coordination meant that clinical/epidemiological data was often not available real-time and provisioned with substantial delay.

We aim to integrate hospital data collected on infectious diseases/syndromes, particularly those of potential pandemic or epidemic significance (e.g. respiratory viral infections, dengue) in real-time via electronic-health-record (EHR) based systems (e.g. EPIC, SCM); with national level administrative, claims, laboratory and surveillance data for the same infectious diseases/syndromes. We aim to a) assess concordance and completeness of hospital-level data versus national-level records; b) potential cost and time-savings afforded via utilisation of EHR data (versus manual data-collection; c) obtain new insights into clinical burden/epidemiology of infectious diseases in Singapore, via linkage of hospital-level with national data.

Insights derived from this work will inform clinical guidelines, enhance vaccination and therapeutic strategies, and improve patient care pathways. Ultimately, this study will enable a faster, more coordinated, and data-driven pandemic response, supporting Singapore’s healthcare resilience.