Pim Mw Janssens1. 1. Laboratory of Clinical Chemistry and Haematology, Rijnstate Hospital, The Netherlands pjanssens@rijnstate.nl.
Abstract
BACKGROUND: Prospective risk analysis (PRA) is an essential element in quality assurance for clinical laboratories. Practical approaches to conducting PRA in laboratories, however, are scarce. METHODS: On the basis of the classical Failure Mode and Effect Analysis method, an approach to PRA was developed for application to key laboratory processes. First, the separate, major steps of the process under investigation are identified. Scores are then given for the Probability (P) and Consequence (C) of predefined types of failures and the chances of Detecting (D) these failures. Based on the P and C scores (on a 10-point scale), an overall Risk score (R) is calculated. The scores for each process were recorded in a matrix table. Based on predetermined criteria for R and D, it was determined whether a more detailed analysis was required for potential failures and, ultimately, where risk-reducing measures were necessary, if any. RESULTS: As an illustration, this paper presents the results of the application of PRA to our pre-analytical and analytical activities. The highest R scores were obtained in the stat processes, the most common failure type in the collective process steps was 'delayed processing or analysis', the failure type with the highest mean R score was 'inappropriate analysis' and the failure type most frequently rated as suboptimal was 'identification error'. CONCLUSIONS: The PRA designed is a useful semi-objective tool to identify process steps with potential failures rated as risky. Its systematic design and convenient output in matrix tables makes it easy to perform, practical and transparent.
BACKGROUND: Prospective risk analysis (PRA) is an essential element in quality assurance for clinical laboratories. Practical approaches to conducting PRA in laboratories, however, are scarce. METHODS: On the basis of the classical Failure Mode and Effect Analysis method, an approach to PRA was developed for application to key laboratory processes. First, the separate, major steps of the process under investigation are identified. Scores are then given for the Probability (P) and Consequence (C) of predefined types of failures and the chances of Detecting (D) these failures. Based on the P and C scores (on a 10-point scale), an overall Risk score (R) is calculated. The scores for each process were recorded in a matrix table. Based on predetermined criteria for R and D, it was determined whether a more detailed analysis was required for potential failures and, ultimately, where risk-reducing measures were necessary, if any. RESULTS: As an illustration, this paper presents the results of the application of PRA to our pre-analytical and analytical activities. The highest R scores were obtained in the stat processes, the most common failure type in the collective process steps was 'delayed processing or analysis', the failure type with the highest mean R score was 'inappropriate analysis' and the failure type most frequently rated as suboptimal was 'identification error'. CONCLUSIONS: The PRA designed is a useful semi-objective tool to identify process steps with potential failures rated as risky. Its systematic design and convenient output in matrix tables makes it easy to perform, practical and transparent.