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Developing a Data-Driven Medical Governance Platform for Resource Allocation with Decision Support Recommender Agent

Rosicar E. Escober a , Jayson M. Victoriano b , Ace C. Lagman c

a La Consolacion University Philippines, Malolos, Bulacan, Philippines

b Bulacan State University, Malolos, Bulacan, Philippines

c FEU Institute of Technology, Manila, Philippines

Lecture Notes in Networks and Systems, (2026), pp. 435-445

Abstract: This research addresses the challenges faced by community welfare services in the Philippines, particularly within the context of healthcare delivery. With the rapid advancement of information technologies, there is a critical need to enhance the efficiency and efficacy of medical information management. The study highlights the issues of delayed access to accurate health information due to disparate systems and poor data quality, which hinder timely medical assistance. It proposes developing a comprehensive e-health solution designed to automate and digitize healthcare records management within barangays—the grassroots level of governance in Philippine society. In terms of the medical resources, allocation, the researcher used Exponential smoothing for forecasting resources ahead of time, reducing the risk of shortages or overstocking. The researcher used Technology Acceptance Model Software Quality Model to assess the system overall capability as perceived by experts and end users. In terms of ISO instrument, all criteria are rated very acceptable in which it emphasizes the system’s overall effectiveness and user-centered design, contributing to a favorable perception of its performance. In terms of the Technology Acceptance Model evaluation, the total mean of 4.03 demonstrates a strong consensus among respondents, highlighting their positive outlook on the system’s usefulness, ease of use, and overall attitude toward its implementation in academic environments.

Recommended Citation

Escober, R. E., Victoriano, J. M., & Lagman, A. C. (2026). Developing a Data-Driven Medical Governance Platform for Resource Allocation with Decision Support Recommender Agent. Lecture Notes in Networks and Systems, 435-445. https://doi.org/10.1007/978-981-96-9191-3_37
R. E. Escober, J. M. Victoriano, and A. C. Lagman, "Developing a Data-Driven Medical Governance Platform for Resource Allocation with Decision Support Recommender Agent," Lecture Notes in Networks and Systems, pp. 435-445, 2026. doi: 10.1007/978-981-96-9191-3_37.
Escober, Rosicar E., et al.. "Developing a Data-Driven Medical Governance Platform for Resource Allocation with Decision Support Recommender Agent." Lecture Notes in Networks and Systems, 2026, pp. 435-445. https://doi.org/10.1007/978-981-96-9191-3_37.
Escober, R. E., Victoriano, J. M., & Lagman, A. C.. 2026. "Developing a Data-Driven Medical Governance Platform for Resource Allocation with Decision Support Recommender Agent." Lecture Notes in Networks and Systems: 435-445. https://doi.org/10.1007/978-981-96-9191-3_37.

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