Expanding healthcare failure mode and effect analysis: A composite proactive risk analysis approach. (January 2018)

• Record Type: Journal Article
• Authors: Faiella, Giuliana; Parand, Anam; Franklin, Bryony Dean; Chana, Prem; Cesarelli, Mario; Stanton, Neville A.; Sevdalis, Nick
• Is Part Of: Reliability engineering & system safety. Volume 169(2018)
• Page Start: 117
• Page End: 126
• Publication Date: 2018-01
• Subjects: Combined prospective risk analysis -- HFMEA -- SHERPA -- STAMP-STPA; Reliability (Engineering) -- Periodicals; System safety -- Periodicals; Industrial safety -- Periodicals; Fiabilité -- Périodiques; Sécurité des systèmes -- Périodiques; Sécurité du travail -- Périodiques; 620.00452
• DOI: 10.1016/j.ress.2017.08.003
• Languages: English
• ISSNs: 0951-8320

Abstract

Highlights: Healthcare Failure Mode and Effect Analysis (HFMEA) methodology's limitations. Systems-Theoretic Accident Model and Processes – Systems-Theoretic Process Analysis (STAMP-STPA). Systematic Human Error Reduction and Prediction Approach (SHERPA). Combination of different prospective safety management techniques. Analysis of medication administration process in home setting. 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.