Medical doctors with the covering of their insurance company are seen in the western world as easy targets for litigation. In some cases the plaintiff is an opportunistic gold digger however in others the doctor truly messed up.
Mess up in IT and you get a couple of bugs that HOPEFULLY are picked up in in testing. Mess up in medicine and you bury your patient. Hence litigation from IT snafus pale in comparison to those in the medical sector.
In attempting to understand and mitigate their insurance losses, a recent study concluded that one of the causes is due to doctors heavy reliance on pattern recognition. Patient symptoms are constantly tested against various mental patterns and the final diagnosis is based on the pattern that best fits the situation.
I suppose all professions do that to one degree or another as we assess and problem solve situations. But where doctors really get caught out is when a string of patients are seen with similar symptoms in succession (eg headache, lethargic, snotty nose = flu). Somewhere in this string there may be a patient with very similar symptoms but because the doctor is so used to seeing flu patients on this morning, this patient is incorrectly diagnosed with flu when they could have something far more serious.
In this case the doctor’s pattern recognition worked against them: having seen five patients with flu, the sixth patient with similar symptoms, must also have flu.
In some cases, this misdiagnosis of an serious situation results in additional pain, trauma, death and even worse, litigation.
The study recommended that this monotonous diagnosis trap can be easily overcome by training doctors to generate at least two or three alternate diagnosis for every patient assessment. And only then deciding on the most likely diagnosis.
If doctors are susceptible to the monotonous diagnosis trap, then surely it is also applicable to others who are involved in regular problem solving. In the business intelligence industry, our days a spent creating competitive advantages for our clients through collecting and manipulating data. So when you process six requests for Profit and Loss reports in a row, they tend to follow a similar pattern.
What has disturbed me after reading the research is questioning what have we missed and what opportunities have we forgone. In our case, all of the BI reports run and balance to the cent, but could we have done it better?
With this in mind, we have decide to create a new habit within our organisation: The habit of Three Alternate Ways. Before embarking on a minor (eg a step within a program) or major (eg. architecture of a new BI system) course of action, we discipline ourselves to think of three possible alternatives, and then proceed with the best.
PS: After trying this for 7 days, I can confirm that this new habit is tough to master. Its so easy to slip back into the old ways of “one solution and lets implement it”. So far, our perseverance has had a small pay-off in that it lead to new way of writing a BI report that saves 27% of the calculation time.
With this in mind, 1) I’ll keep you posted and update this blog, 2) I’ll write a new article or 3) Go to the beach instead…..