Assessment of Immunization Data Quality Management in Primary Care Units Following the Transfer of Sub-District Health Promotion Hospital Responsibilities to the Lamphun Provincial Administrative Organization, Fiscal Year 2025.

Abstract

This study employed a mixed-methods design with a parallel approach to evaluate the data management process, assess the effectiveness of health information systems, and propose recommendations for managing immunization programs at sub-district health promotion hospitals (SHPHs) transferred to the Provincial Administrative Organization. The sample consisted of hospital directors and officers responsible for data recording at SHPHs. Quantitative and qualitative data were collected using a researcher-developed questionnaire and by analyzing immunization data (EPI files) from the Ministry of Public Health’s Health Data Center (HDC) for fiscal years 2022–2025. Data were analyzed using descriptive statistics, content analysis, and the Friedman test. The findings indicated that the overall quality of data management was high, with the highest mean score in administration (=4.56), followed by information and data management (=4.14), and the lowest in personnel (=3.54). This suggests effective system management, although continuous capacity building for personnel remains necessary. Most SHPHs had transitioned from JHCIS to MyPCU; however, overlapping functions and limited data integration were observed. The Friedman test revealed significant differences in median vaccine coverage for Hib3 (p=0.022) and HBV3 (p=0.046), while other vaccines showed consistently high median values, reflecting the quality of service delivery and effective monitoring of target groups. Qualitative findings emphasized critical success factors, including efficient information systems and supportive inter-agency collaboration. Recommendations include developing effective data linkage mechanisms, enhancing personnel competencies in health informatics, and providing sufficient resources to sustain effective immunization data management in the long term.