Failure Mode and Effects Analysis (FMEA) at the preanalytical phase for POCT blood gas analysis: proposal for a shared proactive risk analysis model

Author:

Van Hoof Viviane1,Bench Suzanne2,Soto Antonio Buño3,Luppa Peter P.4,Malpass Anthony5,Schilling Ulf Martin6,Rooney Kevin D.7,Stretton Adam5,Tintu Andrei N.8

Affiliation:

1. Faculty of Medicine and Health Sciences , University of Antwerp , Wilrijk , Belgium

2. Guys and St Thomas NHS Foundation Trust , London , UK

3. Pathology Department , La Paz Hospital , Madrid , Spain

4. Institute for Clinical Chemistry and Pathobiochemistry, Technische Universität München , Munich , Germany

5. Becton, Dickinson and Company , Wokingham , UK

6. Department of Clinical Education, Test and Innovation , Linkoping University Hospital , Linkoping , Sweden

7. Royal Alexandra Hospital , Paisley , UK

8. Erasmus MC, University Medical Centre Rotterdam , Rotterdam , The Netherlands

Abstract

Abstract Objectives Proposal of a risk analysis model to diminish negative impact on patient care by preanalytical errors in blood gas analysis (BGA). Methods Here we designed a Failure Mode and Effects Analysis (FMEA) risk assessment template for BGA, based on literature references and expertise of an international team of laboratory and clinical health care professionals. Results The FMEA identifies pre-analytical process steps, errors that may occur whilst performing BGA (potential failure mode), possible consequences (potential failure effect) and preventive/corrective actions (current controls). Probability of failure occurrence (OCC), severity of failure (SEV) and probability of failure detection (DET) are scored per potential failure mode. OCC and DET depend on test setting and patient population e.g., they differ in primary community health centres as compared to secondary community hospitals and third line university or specialized hospitals. OCC and DET also differ between stand-alone and networked instruments, manual and automated patient identification, and whether results are automatically transmitted to the patient’s electronic health record. The risk priority number (RPN = SEV × OCC × DET) can be applied to determine the sequence in which risks are addressed. RPN can be recalculated after implementing changes to decrease OCC and/or increase DET. Key performance indicators are also proposed to evaluate changes. Conclusions This FMEA model will help health care professionals manage and minimize the risk of preanalytical errors in BGA.

Publisher

Walter de Gruyter GmbH

Subject

Biochemistry (medical),Clinical Biochemistry,General Medicine

Reference44 articles.

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