Dear Roger and Thomas, We have looked extensively at Multivalued logic for quantitating uncertainty. It turns out that most folks in that world have taking 0 false and one true with a number of discrete, usually equally spaced values in between for uncertainty.
After a longwinded go around with a Prof of Philosophical Logic at Princeton (Dr. Graham) We determined that there at least three reproducible types of uncertainty (with good inter-rater reliability) and ~ seven semantic categories. The types are Probable (our guess is around 85% true +/- 5%) and Unlikely (our guess is around 15% true +/- 5%) or Just as likely as not (again our guess is around 50% +/- 15%). These number come from the average PPV of the evidence when a physician "Makes a diagnosis" and NPV when a physician rules one out. Other distinctions are less reproducible. When taken together most clinicians would say that Probable is stronger than Likely, however the assignment to actual cases is not in our experience reproducible between knowledgeable reviewers. I suggest that you first code (as we do) True, False or Uncertain. Then qualify Uncertain with a semantic type indicating strength. This allows a model that can grow with our ability to represent more closely evidence based medicine. Warm regards, Peter Peter L. Elkin, MD Professor of Medicine Director, Laboratory of Biomedical Informatics Department of Internal Medicine Mayo Clinic, College of Medicine Mayo Clinic, Rochester (507) 284-1551 Fax: (507) 284-5370 -----Original Message----- From: owner-openehr-technical at openehr.org [mailto:owner-openehr-techni...@openehr.org] On Behalf Of Thomas Beale Sent: Monday, April 11, 2005 11:42 PM To: openehr-technical at openehr.org Subject: Re: Dr R LONJON Confidence indicator ! Dr LONJON Roger wrote: >hello philippe and thomas, >excuse me to intervene, in English of bad quality. >in medicine for me, a result must be validated and must be signed by the >producer. This result is therefore automatically a total confidence level. It >is a very important notion on the legal plan when these results are put to >disposition on a shared medical file (server web) > >Inversely if this result is approximate, with a coefficient of mistake >importing, it is not about a validated data and therefore publishable, because >consequences in r?ponsabilit? for their author are unforeseeable if the patient >carries complaint. > >I am unaware of this aspect of the problem so enters in your reflection. > > It is actually quite common: consider that in a differential diagnosis, confidences are always expressed in each of the possible diagnosesa, e.g. 90%, 9%, 1% for possible reasons for a child's fever. I don't see it as being about mistakes, it's about the estimation by a clinical professional of the probability of correctness of an opinion. In openEHR, confidences always appear in data of the EVALUATION type. There is no question of clinician confidence in OBSERVATIONs - they are for all intents objective. Of course, machines may have limited accuracy (inbuilt error) and numeric results may be reported with limited precision; these situations can be archetyped. - thomas >Cordially > >Dr R LONJON >france > > - If you have any questions about using this list, please send a message to d.lloyd at openehr.org - If you have any questions about using this list, please send a message to d.lloyd at openehr.org
