- From: Chimezie Ogbuji <ogbujic@bio.ri.ccf.org>
- Date: Wed, 27 Sep 2006 07:23:53 -0400 (EDT)
- To: w3c semweb hcls <public-semweb-lifesci@w3.org>
On Tue, 26 Sep 2006, Kashyap, Vipul wrote: > 1. Lack of explanation capabilities: A key feature for clinical decision > support is that physicians like to get > > explanations for the recommendations proposed by the system. Well, I'd argue that the recommendations are the accompanying literature that document the very measured thought process that went into setting up the model: the choice of variables, considerations in combinations of variables, outliers & statistical anomalies, etc. provide more contextual recommendation than a logical proof trace you would get from a purely declarative approach. The addition of associated probabilities with the output of the model make for a more responsible indicator especially for aspects of a pathway that are heavily dependent on a large number of variables - each in very specific ways. > 2. Lack of "knowledge visibility": The biggest downside is from the KM > perspective, what if one of the conditions changes? We need this to be visible > so that we can have KM processes handle these changes. I'm not sure I follow. The models I'm speaking of are 'driven' by patient data, a different patient would result in a different outcome scenario (with associated confidence limits and probability). The only constants are the weights that are very much specific to the pathway (so ofcourse it would be irresponsible to swap these into different pathways that may not have been part of the considerations that guided the creation of the statistical model in the first place. Chimezie Ogbuji Lead Systems Analyst Thoracic and Cardiovascular Surgery Cleveland Clinic Foundation 9500 Euclid Avenue/ W26 Cleveland, Ohio 44195 Office: (216)444-8593 ogbujic@ccf.org
Received on Wednesday, 27 September 2006 11:24:01 UTC