Optimizing Diagnostic Asset Lifecycle Management: From Health-System Objectives to Asset Performance through an ISO 55000-Informed Adaptive Framework

Vollständiger Abstract

Worum geht es in dieser Arbeit?

Investment in molecular diagnostic technologies has expanded testing capacity in resource-constrained health systems, yet equipment availability does not necessarily translate into sustained diagnostic value. This study examines how lifecycle management influences the performance and value realization of quantitative polymerase chain reaction (qPCR) diagnostic assets. A mixed-methods, multi-site assessment of approximately twenty qPCR devices combined technical inspections, environmental measurements, maintenance and operational records, diagnostic activity data, direct observation, and stakeholder interviews. More than 3,000 diagnostic test records were examined. Although most devices were nominally functional, effective performance varied substantially. Average utilization was approximately 40%, while partial module failures, reagent interruptions, environmental and power constraints, reactive maintenance, fragmented asset information, and limitations in quality assurance reduced effective diagnostic capacity. These findings indicate that diagnostic asset performance emerges from interactions among equipment, infrastructure, users, consumables, laboratory processes, quality systems, information, and governance rather than from technical functionality alone. The empirical findings were interpreted against a structured review of evidence on healthcare technology management, medical equipment lifecycle management, laboratory quality, and ISO 55000 asset-management principles. The resulting Adaptive Diagnostic Asset Lifecycle Management Framework (ADALM) introduces the Dynamic Performance Gap (DPG) as the difference between expected and observed asset-system performance. Identified gaps are interpreted through risk and value considerations and translated into adaptive lifecycle decisions. ADALM establishes a line of sight between health-system objectives, asset-management objectives, lifecycle decisions, diagnostic service performance, and health-system value. The framework offers a context-sensitive approach for improving strategic, operational, health, economic, and environmental performance of critical medical assets.