Advancing healthcare equipment reliability: the role of CMMS and RBEM methodologies in medical equipment maintenance

Purpose This study investigates a novel methodological integration of computerized maintenance management systems (CMMS) data with risk-based equipment management (RBEM) principles to enhance medical equipment reliability and maintainability in healthcare settings. Design/methodology/approach This study combines the use of a CMMS and RBEM scoring methodology to develop an analytical equipment management (EM) scoring model designed to dynamically prioritize maintenance tasks. The scoring thresholds and parameters for factors such as the mean time between failures (MTBF) and age-related decay functions were empirically calibrated using reliability ranges documented in peer-reviewed CMMS and maintenance literature. The utility of the model is demonstrated through a simulation-based case study of critical medical assets. Predictive analytics has also been applied to forecast potential equipment breakdowns and inform maintenance policy decisions Findings The proposed methodology substantially improves the reliability and maintainability of healthcare equipment. The enhanced EM model successfully re-prioritized high-risk equipment, demonstrating a significant theoretical shift from time-based to data-driven maintenance. Simulation outputs indicate that the model has the potential to substantially improve equipment reliability; for critical assets, the projected uptime increase is from 91.5% to 97.0%, alongside a simulated reduction in emergency repair incidents by 64%. These projections align with documented industry benchmarks, showing annual maintenance cost savings of 15%–20% in CMMS-enhanced programs. The combined methodology ensures a defensible, evidence-based process for maintenance policies. Research limitations/implications Selecting appropriate reliability models is crucial for maintenance planning. CMMS–RBEM integration provides operational insights that improve maintenance compliance, reduce equipment failures and support continuous quality improvement in patient care. Practical implications Research emphasizes the critical role of CMMS and RBEM methodologies in medical equipment maintenance. Selecting appropriate reliability models is crucial when evaluating medical equipment maintenance, where the combined implementation of CMMS and RBEM leads to substantial improvements in healthcare equipment reliability and is considered a crucial advance in healthcare maintenance management. Enhance proactive, data-driven prioritization of vulnerable devices. New methodologies are essential for building resilient healthcare organizations that ensure continuous improvement in patient care quality. Social implications The implementation of integrated CMMS and RBEM systems offers significant social implications, primarily by enhancing the availability and equity of qualitative medical care. By ensuring critical life-support devices, such as ventilators, maintain high uptime and functionality, the system minimizes treatment delays and postponements for vulnerable patients, thereby directly improving health outcomes and patient safety. This approach bolsters the overall resilience of the health system, making critical medical services more reliable and equitable for the community, especially in high-volume, resource-constrained environments. Originality/value This study provides a practical, quantitatively driven framework for integrating CMMS data and RBEM logic, addressing the industry gap between descriptive maintenance logging and predictive, risk-based prioritization. The proposed EM scoring model offers a clear and auditable tool for biomedical engineers to optimize resource allocation and enhance patient safety.