This study aims to develop and validate a model for the evaluation of needs and acquisition of biomedical equipment in Colombian Health Care Institutions (IPS). Grounded in World Health Organization (WHO) recommendations and national regulations, the model integrates demographic, epidemiological, and institutional data to support informed decision-making and optimize resource allocation based on local healthcare needs. The model incorporates demographic, epidemiological, human resources, infrastructure, and equipment variables. It follows four phases: data collection, analysis, evaluation of alternatives, and implementation planning. Validation was conducted in two IPS with different complexity levels in Norte de Santander, using a web-based tool developed in Laravel 10. Both qualitative and quantitative usability assessments were carried out. The model was deployed through a web platform built with HTML, CSS, and Laravel 10, allowing automated identification of biomedical equipment needs and service gaps. It identified deficiencies by comparing institutional capacity against regulatory standards and applied a prioritization mechanism using the PDCA (Plan, Do, Check, Act) cycle. This supported structured acquisition plans aligned with institutional capabilities and accreditation requirements. Usability testing revealed high operational efficiency, intuitive navigation, and strong integration with healthcare planning processes. Evaluation time was reduced by 70%, and average accreditation compliance scores exceeded 4.4 out of 5. Validation was conducted in two healthcare institutions in a single Colombian region, which defines the scope and generalizability of the findings. Quantitative validation showed statistically significant improvements (p < 0.05) in compliance indicators and evaluation time reduction. The model demonstrated effectiveness in biomedical equipment planning within IPS, supporting evidence-based decisions and strategic resource use. Its modular and scalable design enables adaptation across diverse healthcare contexts, fostering equitable and efficient management of biomedical technology. The results provide consistent evidence of the model’s applicability and potential for broader implementation across healthcare institutions.
Villamizar et al. (Sun,) studied this question.