FMEA vs. FRACAS vs. RCA – 3/2005

March 11, 2005

FME(C)A – Failure Mode Effects (and Criticality) Analysis FRACAS – Failure Reporting And Corrective Action System RCA – Root Cause Analysis

Many people who work in hospitals have never heard of any of these reliability tools. Those that have (often on patient safety committees) have heard of FMEA and RCA, but often not FRACAS. This essay explains the differences among these techniques.

JCAHO requires:

  •  FMEA to performed once a year
  •  RCA to be performed for sentinel events and near misses.

The use of RCA by hospitals has been critiqued by Berwick (1) who suggests that RCA seeks to find a single cause. I have responded (2) as in my experience, RCA is not limited to seeking single causes. A more important limitation of RCA as practiced by hospitals is that it is often limited, as implied by JCAHO policy, to sentinel events and near misses. This leaves the many less severe events out of the picture.

FRACAS (3-4) is really the same thing as RCA although FRACAS is often combined with other tools such as reliability growth management which is based on learning curve theory. Moreover, in FRACAS all observed error events are analyzed and in this way FRACAS is very similar to FMEA.

The term FRACAS will be used here instead of RCA. Both FRACAS and FMEA can be combined with fault trees. Some attributes of FMEA and FRACAS are shown in the following table.

Attributes of FMEA and FRACAS for a process

  FMEA FRACAS
General “proactive” “reactive”
Purpose affect the design before launch correct problems after launch
Errors may occur – the potential errors must be enumerated have occurred – observed errors are simply counted
Error rate is assumed is measured
Issues with technique Is it complete? Models can be wrong. All errors counted? Culture inhibits reporting errors.
Can be combined with fault trees fault trees
Evaluate quality of the technique difficult – completeness, reasonableness of mitigations is qualitative simple – measure error rate

FMEA and FRACAS can inform Fault Trees

A fault tree is a “top down” structured way1 of representing causes for an undesirable event. Fault trees allow multiple causes for an event and use “AND” and “OR” gates to distinguish between error types. Fault trees can contain both potential and observed errors. Because of this, they are ideal to contain the knowledge expressed in both a FMEA and FRACAS. That is, when a process is designed, the ways it might fail are captured in a fault tree (and FMEA). After the process is launched, the ways in which the process has failed are captured through FRACAS and this knowledge is used to update the fault tree. In both the FMEA and FRACAS, the fault tree is also updated when a mitigation is implemented, since this represents a design change to the process. This is shown in Figure 1.

Figure 1 Use of FMEA, FRACAS, and Fault trees to prevent errors in processes.

Don’t neglect FRACAS

Both FMEA and FRACAS are useful. Yet, the JCAHO focuses on FMEA. In a sense, this is logical because FMEA is more encompassing than FRACAS. That is, FMEA addresses potential errors, yet can also accommodate observed errors, whereas FRACAS is intended only for observed errors. The problem is that with 98,000 deaths due to medical errors each year, there are a huge number of observed errors and there is the possibility to pay insufficient attention to potential errors if one performs only FMEA.

Consider a hypothetical FMEA for a transplant service. Consider two error events:

  1. patient infection after surgery – an observed error
  2. organ selected with incorrect blood type – a potential error

If one goes through the entire service, it is likely that the number of observed error events will cause a ranking problem. Ranking is important because there are limited funds for which to apply to mitigations. So even though selection of an organ with the wrong blood type may have never occurred, it is possible that the selection process is flawed and could benefit from mitigations. Yet, it is also possible that this will not occur because the focus is on observed errors. Hence, one should perform both FMEA and FRACAS, as indicated in Figure 1. This reduces the likelihood of ranking problems since the FMEA will focus on potential problems and the FRACAS will focus on observed problems.

A challenge with FMEAs

As indicated in the above table under “purpose”, use of FMEA is intended to affect the design of a process. Yet, in the medical diagnostics industry, an FDA required hazard analysis for instrument systems (a fault tree / FMEA for hazards) was at times merely a documentation of an existing design. The same issue exists for FMEAs in hospitals, since many FMEAs will be performed for existing processes.

References

  1. Berwick, DM. Errors Today and Errors Tomorrow NEJM 2003;348:2570-2572.
  2. Krouwer, JS. There is nothing wrong with the concept of a root cause. Int J Qual Health Care 2004;16:263.
  3. Mil-Std 2155, available at http://www.barringer1.com/mil_files/MIL-STD-2155.pdf
  4. Krouwer, JS. Using a Learning Curve Approach to Reduce Laboratory Error, Accred. Qual. Assur., 7: 461-467 (2002) available at http://krouwerconsulting.com/KrouwerLearningCurve.pdf

1The graphical structure imposed by a fault tree increases the likelihood that a FMEA will be more complete, since a FMEA is basically an unordered list in a table.