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January 03, 2004

Systemic Learning and Local Advocates

Part of my previous quote from NHPR could be read as critical of Edwards:

But for all the people who benefited from Edwards' legal work, some of those he opposed still feel a sting. Dr. Peter Gentling performed an unnecessary mastectomy because of a lab error. The ensuing lawsuit forced him into early retirement. Gentling says his insurance company's representative agreed to settle at the mere mention of Edwards' name.

I took this as a good quote because it managed to present two perspectives on John Edwards without diluting either.

The issue of fairness (lab error vs doctor error) is one of intra-hospital risk vs. liability allocation.

If lab technicians and doctors were represented by a single insurance company, the liability boundary would be negotiated with representatives of each internal group.

If lab technicians and doctors were represented by separate insurance companies, the liability boundary would be negotiated by "pooled" internal groups from multiple hospitals.

In either case, intra-hospital liability is completely separate from hospital-patient liability. Why? Because the purpose of organizational boundaries is to constrain liability.

The systemic function of insurance is not compensation - it's feedback (in the control theory sense).

Insurance uses the instrument of price to distribute multi-organization learning. It takes tacit human practice into the realm of accountability, while acknowledging the undocumentable space between science and skill.

If this doctor's case identified an unstable liability boundary between lab technicians and doctors, it would be in the interests of both groups to, (a) stabilize the boundary for future cases, and (b) remediate local unfairness as payment for the experience gained by the system.

If the cited doctor experienced local unfairness, he did not have a suitable advocate. He could have hired John Edwards, had Edwards not already been representing the recipient of an unnecessary mastectomy.

Thus do systems learn, but we humans must often go to extraordinary lengths to remediate local unfairness. By definition, systemic learning occurs in the presence of the unexpected.

May we all find suitable advocates.

Posted by dotpeople at January 3, 2004 09:10 PM | TrackBack