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Expanding healthcare failure mode and effect analysis: A composite proactive risk analysis approach

Expanding healthcare failure mode and effect analysis: A composite proactive risk analysis approach
Expanding healthcare failure mode and effect analysis: A composite proactive risk analysis approach

Healthcare Failure Mode and Effect Analysis (HFMEA) is a systematic risk assessment method derived from high risk industries to prospectively examine complex healthcare processes. Like most methods, HFMEA has strengths and weaknesses. In this paper we provide a review of HFMEA's limitations and we introduce an expanded version of traditional HFMEA, with the addition of two safety management techniques: Systematic Human Error Reduction and Prediction Analysis (SHERPA) and Systems-Theoretic Accident Model and Processes – Systems-Theoretic Process Analysis (STAMP-STPA). The combination of the three methodologies addresses significant HFMEA limitations. To test the viability of the proposed hybrid technique, we applied it to assess the potential failures in the process of administration of medication in the home setting. Our findings suggest that it is both a viable and effective tool to supplement the analysis of failures and their causes. We also found that the hybrid technique was effective in identifying corrective actions to address human errors and detecting failures of the constraints necessary to maintain safety.

Combined prospective risk analysis, HFMEA, SHERPA, STAMP-STPA
0951-8320
117-126
Faiella, Giuliana
2d72fcb7-c481-47a2-a3da-3f60dc6ad0f4
Parand, Anam
a3ebcea8-6140-4f78-963c-5145e83230c7
Franklin, Bryony Dean
53972895-6580-47ad-a73c-ebc40bea5088
Chana, Prem
124700bc-4647-4ac0-8ebc-017cf33d1b57
Cesarelli, Mario
e120e865-e5a3-4c65-bf03-29d6c1a3352b
Stanton, Neville A.
351a44ab-09a0-422a-a738-01df1fe0fadd
Sevdalis, Nick
0910262b-1085-41fa-931c-40b643912854
Faiella, Giuliana
2d72fcb7-c481-47a2-a3da-3f60dc6ad0f4
Parand, Anam
a3ebcea8-6140-4f78-963c-5145e83230c7
Franklin, Bryony Dean
53972895-6580-47ad-a73c-ebc40bea5088
Chana, Prem
124700bc-4647-4ac0-8ebc-017cf33d1b57
Cesarelli, Mario
e120e865-e5a3-4c65-bf03-29d6c1a3352b
Stanton, Neville A.
351a44ab-09a0-422a-a738-01df1fe0fadd
Sevdalis, Nick
0910262b-1085-41fa-931c-40b643912854

Faiella, Giuliana, Parand, Anam, Franklin, Bryony Dean, Chana, Prem, Cesarelli, Mario, Stanton, Neville A. and Sevdalis, Nick (2018) Expanding healthcare failure mode and effect analysis: A composite proactive risk analysis approach. Journal of Reliability Engineering and System Safety, 169, 117-126. (doi:10.1016/j.ress.2017.08.003).

Record type: Article

Abstract

Healthcare Failure Mode and Effect Analysis (HFMEA) is a systematic risk assessment method derived from high risk industries to prospectively examine complex healthcare processes. Like most methods, HFMEA has strengths and weaknesses. In this paper we provide a review of HFMEA's limitations and we introduce an expanded version of traditional HFMEA, with the addition of two safety management techniques: Systematic Human Error Reduction and Prediction Analysis (SHERPA) and Systems-Theoretic Accident Model and Processes – Systems-Theoretic Process Analysis (STAMP-STPA). The combination of the three methodologies addresses significant HFMEA limitations. To test the viability of the proposed hybrid technique, we applied it to assess the potential failures in the process of administration of medication in the home setting. Our findings suggest that it is both a viable and effective tool to supplement the analysis of failures and their causes. We also found that the hybrid technique was effective in identifying corrective actions to address human errors and detecting failures of the constraints necessary to maintain safety.

Full text not available from this repository.

More information

Accepted/In Press date: 3 August 2017
e-pub ahead of print date: 4 August 2017
Published date: 1 January 2018
Keywords: Combined prospective risk analysis, HFMEA, SHERPA, STAMP-STPA

Identifiers

Local EPrints ID: 417473
URI: https://eprints.soton.ac.uk/id/eprint/417473
ISSN: 0951-8320
PURE UUID: 246cb672-2a19-4c38-823e-4bc4771b02a2

Catalogue record

Date deposited: 01 Feb 2018 17:30
Last modified: 07 Aug 2018 16:32

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