Gerard Freriks wrote: > Hi, > > A few words from a non-techie. > > Quantity means that what is the resulting figure expressing a quantity. > Hb: 8.5 mmol/L > > A property of the Hb measurement can be an uncertainty. > This is not an uncertainty of the figure "8.5", but of the Hb > measurement where 8.5 is the correct resulting number and mmol/L the > code for the units. > There can be the question that the reported 8.5 really is 8.5 > with/without roundoff error. > Only roundoff could be added to DV-QUANTITY as an added extra property, > I think. > > Uncertainty is added information that the uncertainty of the measurement > is plus or minus something according to a specified (or implied) > distribution type. > In my view uncertainty is the property of the measurement i.e. the > specific archetype/template that will express the number > This uncertainty will be expressed in an archetype using attributes > using DV-QUANTITY expressing the uncertainty as limits and a > distribution type term (with a default gaussian distribution?)
The foregoing seems sensible to me. I think that uncertainty or confidence interval (or credible interval) information for a scalar quantity (such as a biochemistry result) should be treated in a similar manner to normal ranges for lab tests results. How does openEHR handle normal ranges, which, depending on the type of test, may be specific to each lab/assay method or kit and reference population. My microbiologist colleagues keep reminding me that most serological results can't really be interpreted in the absence of assay- and lab-specific reference titres, and the same is true of many NAT (nucleic acid test) assays, especially those involving PCR. Usually the microbiologist or pathologist will provide their lab- and assay-specific interpretation of the numbers for the requesting doctor eg "titre 1 in 256 i.e. positive for XYZ", and it could be argued that it is enough to capture just the interpretation of the numbers - but that doesn't seem tot be the guiding principle elsewhere in openEHR. For example, I marvel at the completeness of the archetype for capturing blood pressure measurements, right down to the detail of which phase of the Korotkoff sounds is used, as I recall. Applying that same degree of attention to detail to lab results means having the ability to accommodate quite a lot of metadata about each scalar result. Mostly that detailed metadata about accuracy or confidence limits or about assay types won't be collected, won't be available or won't matter, but occasionally it will matter, and I suppose that's what openEHR needs to plan for, within reason. Tim C > -- <private> -- > Gerard Freriks, arts > Huigsloterdijk 378 > 2158 LR Buitenkaag > The Netherlands > > T: +31 252 544896 > M: +31 654 792800 > > > On 17-mrt-2006, at 12:42, Thomas Beale wrote: > >> The real question is: what is the type & origin of data that need to >> represented in the more sophisticated way that we are now suggesting? >> Is it a different category of data? Should be leave the current >> DV_QUANTITY as is and add a new subtype? Or is it that we should >> consider a quantity with a 95% T-distribution confidence interval as a >> pretty normal thing? Should we then start considering the "simple" >> idea of a symmetric accuracy range (+/- xxx) as really just one >> specific type of a confidence interval (it might translate to >> something like 98% on a normal curve). In other words, should we >> generalise he "accuracy" notion into a "confidence interval" notion? > >
