Skip to main content

Failure mode and effects analysis: a comparison of two common risk prioritisation methods.

Publication ,  Journal Article
McElroy, LM; Khorzad, R; Nannicelli, AP; Brown, AR; Ladner, DP; Holl, JL
Published in: BMJ Qual Saf
May 2016

BACKGROUND: Failure mode and effects analysis (FMEA) is a method of risk assessment increasingly used in healthcare over the past decade. The traditional method, however, can require substantial time and training resources. The goal of this study is to compare a simplified scoring method with the traditional scoring method to determine the degree of congruence in identifying high-risk failures. METHODS: An FMEA of the operating room (OR) to intensive care unit (ICU) handoff was conducted. Failures were scored and ranked using both the traditional risk priority number (RPN) and criticality-based method, and a simplified method, which designates failures as 'high', 'medium' or 'low' risk. The degree of congruence was determined by first identifying those failures determined to be critical by the traditional method (RPN≥300), and then calculating the per cent congruence with those failures designated critical by the simplified methods (high risk). RESULTS: In total, 79 process failures among 37 individual steps in the OR to ICU handoff process were identified. The traditional method yielded Criticality Indices (CIs) ranging from 18 to 72 and RPNs ranging from 80 to 504. The simplified method ranked 11 failures as 'low risk', 30 as medium risk and 22 as high risk. The traditional method yielded 24 failures with an RPN ≥300, of which 22 were identified as high risk by the simplified method (92% agreement). The top 20% of CI (≥60) included 12 failures, of which six were designated as high risk by the simplified method (50% agreement). CONCLUSIONS: These results suggest that the simplified method of scoring and ranking failures identified by an FMEA can be a useful tool for healthcare organisations with limited access to FMEA expertise. However, the simplified method does not result in the same degree of discrimination in the ranking of failures offered by the traditional method.

Duke Scholars

Altmetric Attention Stats
Dimensions Citation Stats

Published In

BMJ Qual Saf

DOI

EISSN

2044-5423

Publication Date

May 2016

Volume

25

Issue

5

Start / End Page

329 / 336

Location

England

Related Subject Headings

  • Risk Assessment
  • Patient Harm
  • Patient Handoff
  • Outcome Assessment, Health Care
  • Operating Rooms
  • Male
  • Intensive Care Units
  • Incidence
  • Humans
  • Healthcare Failure Mode and Effect Analysis
 

Citation

APA
Chicago
ICMJE
MLA
NLM
McElroy, L. M., Khorzad, R., Nannicelli, A. P., Brown, A. R., Ladner, D. P., & Holl, J. L. (2016). Failure mode and effects analysis: a comparison of two common risk prioritisation methods. BMJ Qual Saf, 25(5), 329–336. https://doi.org/10.1136/bmjqs-2015-004130
McElroy, Lisa M., Rebeca Khorzad, Anna P. Nannicelli, Alexandra R. Brown, Daniela P. Ladner, and Jane L. Holl. “Failure mode and effects analysis: a comparison of two common risk prioritisation methods.BMJ Qual Saf 25, no. 5 (May 2016): 329–36. https://doi.org/10.1136/bmjqs-2015-004130.
McElroy LM, Khorzad R, Nannicelli AP, Brown AR, Ladner DP, Holl JL. Failure mode and effects analysis: a comparison of two common risk prioritisation methods. BMJ Qual Saf. 2016 May;25(5):329–36.
McElroy, Lisa M., et al. “Failure mode and effects analysis: a comparison of two common risk prioritisation methods.BMJ Qual Saf, vol. 25, no. 5, May 2016, pp. 329–36. Pubmed, doi:10.1136/bmjqs-2015-004130.
McElroy LM, Khorzad R, Nannicelli AP, Brown AR, Ladner DP, Holl JL. Failure mode and effects analysis: a comparison of two common risk prioritisation methods. BMJ Qual Saf. 2016 May;25(5):329–336.

Published In

BMJ Qual Saf

DOI

EISSN

2044-5423

Publication Date

May 2016

Volume

25

Issue

5

Start / End Page

329 / 336

Location

England

Related Subject Headings

  • Risk Assessment
  • Patient Harm
  • Patient Handoff
  • Outcome Assessment, Health Care
  • Operating Rooms
  • Male
  • Intensive Care Units
  • Incidence
  • Humans
  • Healthcare Failure Mode and Effect Analysis