Management Model for the Evaluation of needs and Acquisition of Biomedical Equipment in Healthcare Institutions: Based on WHO Recommendations, and National Regulations

Key findings from this study

This research indicates that:

• The model reduced equipment evaluation time by 70% while generating accreditation compliance scores exceeding 4.4 out of 5 in validation testing.
• Automated comparison of institutional capacity against regulatory standards identified equipment deficiencies and service gaps systematically.
• The modular design enables adaptation across healthcare institutions with different complexity levels and organizational structures.

Overview

The study develops and validates a management model for evaluating biomedical equipment needs in Colombian healthcare institutions. The model integrates demographic, epidemiological, human resources, infrastructure, and equipment variables. It follows WHO recommendations and national regulatory standards to support evidence-based resource allocation and institutional planning.

Methods and approach

The model operates through four sequential phases: data collection, analysis, evaluation of alternatives, and implementation planning. Validation occurred at two healthcare institutions with different complexity levels in Norte de Santander. A web-based platform implemented in Laravel 10 with HTML and CSS automated equipment need identification and gap detection. The system compared institutional capacity against regulatory standards and applied a prioritization mechanism using the PDCA cycle. Both qualitative and quantitative usability assessments were performed to evaluate the platform's effectiveness.

Results

Usability testing demonstrated high operational efficiency, intuitive navigation, and strong integration with healthcare planning processes. The platform reduced evaluation time by 70% and generated average accreditation compliance scores exceeding 4.4 out of 5. Quantitative validation showed statistically significant improvements in compliance indicators and evaluation time reduction (p < 0.05).

The model successfully identified equipment deficiencies and service gaps through automated comparison of institutional capacity against regulatory requirements. The prioritization mechanism supported structured acquisition plans aligned with institutional capabilities and accreditation requirements. Results demonstrated the model's effectiveness in biomedical equipment planning within healthcare institutions.

Implications

The modular and scalable design enables adaptation across diverse healthcare contexts and different institutional complexity levels. This flexibility supports equitable and efficient management of biomedical technology across varying organizational structures. Broader implementation across Colombian healthcare institutions and similar regional health systems becomes feasible given the demonstrated effectiveness and technical accessibility.

The validated approach provides healthcare administrators with evidence-based decision-making tools that align resource allocation with regulatory compliance requirements. Integration with accreditation processes strengthens institutional planning and accountability. The model's ability to reduce evaluation time while improving compliance scores suggests potential for systemic improvements in healthcare technology management at regional and national scales.

Scope and limitations

This summary is based on the study abstract and available metadata. It does not include a full analysis of the complete paper, supplementary materials, or underlying datasets unless explicitly stated. Findings should be interpreted in the context of the original publication.