Assessing the validity of prospective hazard analysis methods: a comparison of two techniques

BMC Health Services Research

Jon Berman¹  Sheena Davis¹  Paul Leach¹  Lacey Colligan²  Janet E Anderson⁴  Henry WW Potts³ 

[1] Green Street Berman Ltd., London, UK;Division of Neonatology, University of Virginia, Charlottesville, USA;CHIME, 3rd floor, Wolfson House, 4 Stephenson Way, London NW1 2HE, UK;Florence Nightingale School of Nursing and Midwifery, King’s College London, London, UK

关键词: Prospective hazard analysis;    SWIFT;    HFMEA;    Reliability and validity;    Risk assessment;   

Others  :  1134238
DOI  :  10.1186/1472-6963-14-41

 received in 2013-04-03, accepted in 2014-01-23,  发布年份 2014

【 摘 要 】

Background

Prospective Hazard Analysis techniques such as Healthcare Failure Modes and Effects Analysis (HFMEA) and Structured What If Technique (SWIFT) have the potential to increase safety by identifying risks before an adverse event occurs. Published accounts of their application in healthcare have identified benefits, but the reliability of some methods has been found to be low. The aim of this study was to examine the validity of SWIFT and HFMEA by comparing their outputs in the process of risk assessment, and comparing the results with risks identified by retrospective methods.

Methods

The setting was a community-based anticoagulation clinic, in which risk assessment activities had been previously performed and were available. A SWIFT and an HFMEA workshop were conducted consecutively on the same day by experienced experts. Participants were a mixture of pharmacists, administrative staff and software developers. Both methods produced lists of risks scored according to the method’s procedure. Participants’ views about the value of the workshops were elicited with a questionnaire.

Results

SWIFT identified 61 risks and HFMEA identified 72 risks. For both methods less than half the hazards were identified by the other method. There was also little overlap between the results of the workshops and risks identified by prior root cause analysis, staff interviews or clinical governance board discussions. Participants’ feedback indicated that the workshops were viewed as useful.

Conclusions

Although there was limited overlap, both methods raised important hazards. Scoping the problem area had a considerable influence on the outputs. The opportunity for teams to discuss their work from a risk perspective is valuable, but these methods cannot be relied upon in isolation to provide a comprehensive description. Multiple methods for identifying hazards should be used and data from different sources should be integrated to give a comprehensive view of risk in a system.

【 授权许可】

   
2014 Potts et al.; licensee BioMed Central Ltd.

【 参考文献 】

• [1]Wreathall J, Nemeth C: Assessing risk: The role of probabilistic risk assessment (PRA) in patient safety improvement. Qual Saf Health Care 2004, 13:206-212.
• [2]Battles JB, Dixon NM, Borotkanics RJ, et al.: Sense making of patient safety risks and hazards. Health Serv Res 2006, 41:1555-1575.
• [3]Stanton NA, Salmon PM, Walker GH, et al.: Human Factors Methods: A Practical Guide for Engineering and Design. Farnham, UK: Ashgate; 2005.
• [4]Israelski E, Muto W: Human factors risk management in medical products. In Handbook of Human Factors and Ergonomics in Health Care and Patient Safety. Edited by Carrayon P. Hahwah, NJ: Lawrence Erlbaum Associate; 2007:615-647.
• [5]Lyons M, Adams S, Woloshynowych M, et al.: Human reliability analysis in healthcare: a review of techniques. Int J Risk Safety Med 2004, 16:223-237.
• [6]DeRosier J, Stalhandske E, Bagian JP, et al.: Using health care failure mode and effect analysis: the VA National Center for Patient Safety’s prospective risk analysis system. Jt Comm J Qual Patient Saf 2002, 28:248-267.
• [7]Ward JR, Clarkson PJ, Buckle P, Berman J, Lim R, Jun GT: Prospective hazard analysis: tailoring prospective methods to a healthcare context. Final report, Patient Safety Research Portfolio (Research Project PS/035). Cambridge, UK: Engineering Design Centre, University of Cambridge; 2010. http://www.birmingham.ac.uk/Documents/college-mds/haps/projects/cfhep/psrp/finalreports/PS035-RevisedPHAFinalReportv11withToolkitJuly2010.pdf webcite (accessed 6 August 2013)
• [8]Card AJ, Ward JR, Clarkson PJ: Beyond FMEA: the structured what-if technique (SWIFT). J Healthcare Risk Manage 2012, 31:23-29.
• [9]Lyons M: Towards a framework to select techniques for error prediction: supporting novice users in the healthcare sector. Appl Ergon 2009, 40:379-395.
• [10]Anderson JE, Kodate N, Walters R, et al.: Can incident reporting improve safety? Healthcare practitioners’ views of the effectiveness of incident reporting. Int J Qual Health Care 2013, 25:141-150.
• [11]Kessels-Habraken M, van der Schaaf T, de Jonge J, et al.: Integration of prospective and retrospective methods for risk analysis in hospitals. Int J Qual Health Care 2009, 21:427-432.
• [12]Senders J: FMEA and RCA: the modern mantras of modern risk management. Qual Saf Health Care 2004, 13:249-250.
• [13]Shebl N, Franklin B, Barber N, et al.: Failure mode and effects analysis: views of hospital staff in the UK. J Health Serv Res Policy 2012, 17:37-43.
• [14]Crawley F, Tyler B: Hazard identification methods. Rugby, UK: Institute of Chemical Engineers; 2003.
• [15]Phipps D, Meakin GH, Beatty PC, et al.: Human factors in anaesthetic practice: Insights from a task analysis. Br J Anaesth 2008, 100:333-343.
• [16]Apkon M, Leonard J, Probst L, et al.: Design of a safer approach to intravenous drug infusions: failure mode effects analysis. Qual Saf Health Care 2004, 13:265-271.
• [17]Franklin BD, Shebl NA, Barber N: Failure mode and effects analysis: too little for too much? BMJ Qual Saf 2012, 21:607-611.
• [18]Shebl NA, Franklin BD, Barber N: Is failure mode and effect analysis reliable? J Patient Saf 2009, 5:86-94.
• [19]Ashley L, Armitage G: Failure mode and effects analysis: an empirical comparison of failure mode scoring procedures. J Patient Saf 2010, 6:210-215.
• [20]Saka O, McGuire A, Wolfe CDA: Economic Burden of Stroke in England. London, UK: National Audit Office; 2005. http://www.nao.org.uk/wp-content/uploads/2005/11/0506452_economic_analysis.pdf webcite
• [21]Colligan L, Anderson JE, Potts HWW, et al.: Does the process map influence the outcome of quality improvement work? A comparison of a sequential flow diagrams and a hierarchical task analysis diagram. BMC Health Services Res 2010, 10:7. BioMed Central Full Text
• [22]Potts HWW, Keen J, Denby T, et al.: Towards a better understanding of delivering e-health systems: a systematic review using the meta-narrative method and two case studies. Final report, NIHR Service Delivery and Organisation programme. London, UK: HMSO; 2011. http://www.netscc.ac.uk/hsdr/files/project/SDO_FR_08-1602-131_V01.pdf webcite (accessed 24 September 2012)
• [23]Austin T, Kalra D, Lea N, et al.: Analysis of clinical record data for anticoagulation management within an EHR system. Open Med Inform J 2009, 3:54-64.
• [24]Chapman DG: Some properties of the hypergeometric distribution with applications to zoological sample censuses. Univ Calif Publ Stat 1951, 1:131-160.
• [25]Shebl NA, Franklin BD, Barber N: Failure mode and effects analysis outputs: are they valid? BMC Health Serv Res 2012, 12:150. BioMed Central Full Text
• [26]Hassall M, Sanderson P, Cameron I: Using cognitive work analysis techniques to identify human factor hazards. Proc Hum Fact Ergon Soc Ann Meet 2010, 54:269-273.