Process Thinking Bob Luttman, Robert Luttman & Associates

Home Page Introduction Process Thinking Flowcharts Cause-Effect Analysis Critical Path Method (a.k.a. PERT Charts) Failure Mode Effect Analysis (a.k.a. Variance Effect Analysis) Summary and Conclusion Assignment Questions Comments References/Bibliography

Failure Mode Effect Analysis -> Variance Effect Analysis Failure Mode Effect Analysis was invented by NASA early in the US Apollo space program. NASA created the tool to alleviate the stress between two conflicting mottos; "failure is not an option" and "perfect is the enemy of good". The first meant successfully completing the mission and returning the crew. The second meant that failure of at least some components was unavoidable, the job was to predict them, prevent them when possible, plan for them, and build in the ability to overcome failures. Failure Mode Effect Analysis was a tool for facilitating the process of predicting failures, planning preventive measures, estimating the cost of the failure, and planning redundant systems or system responses to failures. We have adapted the tool to variance management systems and clinical pathways as Variance Effect Analysis. Variance Effect Analysis is an attempt to answer the So What Question and assess the various Cascade Effects in a pathway.   Using the VEA First, this is not meant for all variances. This is not a mindless bureaucratic exercise. The important variances, though, should go through this process. A blank form is here. I will refer to it a we discuss how to use it. Filling out the form is as follows: The variance's effects are listed in Column A. A brief description is sufficient. In Column B the probability of the effect occurring is entered; you could base the number on data, clinical judgment, literature reviews or other sources. In Column C a severity score is entered; any quantitative scale is appropriate though the organization should use one global scale for internal consistency. Column D is the product of B and C which gives the Weighted Severity. Column E list responsive or preventive measures which alleviate, prevent, or mitigate the effect. Summing the Weighted Severity column gives a sense of the So What factor for each variance. The team designing the pathway should focus on preventing these variances or building in processes to overcome them. Care providers should focus on assuring that the variances do not occur and reacting appropriately when they do occur. Likewise for improvement efforts: eliminate these variances. Again, one possible outcome of this analysis is separate pathways for certain patient subpopulations. Or dynamic pathways that incorporate "emergency" protocols for specific events such as arrhythmia or failure to extubate. The great power of tool like Variance Effect Analysis is the discussion it can facilitate. If an ounce of prevention is worth a pound of cure, most of the ounce is in recognizing the possibility something happening and how to avoid it.

rluttman@robertluttman.com
Improving Healthcare Across the Continuum