Fragmented road safety data across Philippine agencies hinders practical analysis and intervention. This paper explores a data matching algorithm for the Philippine Integrated Traffic Incident Database (PITAD), designed to consolidate data from various sources. The algorithm prioritizes matching incident time/date, and GPS coordinates with secondary criteria such as vehicle types and demographics. By pre-processing data, computing matching scores based on time, location, and additional factors, and clustering matched entries, the algorithm tackles data fragmentation and improves data quality within PITAD. This paves the way for comprehensive analysis of road safety trends, enabling data-driven decisions for targeted interventions and, ultimately, enhanced road safety in the Philippines.