TY - JOUR
T1 - Failure Mode and Effects Analysis (FMEA) at the preanalytical phase for POCT blood gas analysis
T2 - Proposal for a shared proactive risk analysis model
AU - Van Hoof, Viviane
AU - Bench, Suzanne
AU - Soto, Antonio Buño
AU - Luppa, Peter P.
AU - Malpass, Anthony
AU - Schilling, Ulf Martin
AU - Rooney, Kevin D.
AU - Stretton, Adam
AU - Tintu, Andrei N.
N1 - Publisher Copyright:
© 2022 Viviane Van Hoof et al., published by De Gruyter, Berlin/Boston.
PY - 2022/7/26
Y1 - 2022/7/26
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85130905599&partnerID=8YFLogxK
U2 - 10.1515/cclm-2022-0319
DO - 10.1515/cclm-2022-0319
M3 - Article
C2 - 35607775
AN - SCOPUS:85130905599
SN - 1434-6621
VL - 60
SP - 1186
EP - 1201
JO - Clinical Chemistry and Laboratory Medicine
JF - Clinical Chemistry and Laboratory Medicine
IS - 8
ER -