UTILIZATION OF BIOCHEMISTRY ANALYZERS IN A TERTIARY CARE LABORATORY IN SRI LANKA: A MIXED-METHOD STUDY
Abstract
Background: Efficient utilization of laboratory equipment is essential for high-quality patient care and effective use of healthcare resources. However, evidence on equipment utilization in tertiary-care laboratories with high testing volumes remains limited. This study assessed biochemistry analyzer utilization and contributing operational factors at the National Hospital of Sri Lanka. Methods: A mixed-methods descriptive study was conducted using retrospective laboratory workload data from January to October 2023 and key informant interviews. Utilization coefficient (UC) was calculated as actual tests performed divided by theoretical analytical capacity. A UC below 50% was used as an operational classification criterion for underutilization based on previous medical equipment utilization research, rather than as an optimal utilization target. Qualitative data were analyzed thematically, and Fishbone and Pareto analyses were used to identify and prioritize contributing factors. Results: Six functional biochemistry analyzers were assessed, with four operating during daytime and two at night. The laboratory processed an average of 182,318 tests monthly, comprising 98,880 daytime and 83,438 nighttime tests. Overall UC was 10.7%, with higher utilization during daytime (16.1%) than nighttime (7.6%). The low UC reflected a substantial difference between theoretical analytical capacity and actual workload. The principal contributing factors identified through Pareto analysis were supply–demand mismatch of equipment, interrupted reagent supply, and reagent wastage. Conclusion: The findings indicate substantial excess theoretical analytical capacity relative to the workload during the study period. Equipment planning should consider historical and projected workload, shiftspecific demand, analyzer capabilities, reagent requirements, and reserve capacity. Improved reagent supply management and potential referral of selected routine, non-urgent tests could also support more efficient use of existing laboratory infrastructure.