Hi Stef,
Very interesting and, in principle, quite correct but I am not sure how practicable this would be in the real world. There are so many variables that might determine whether a Blood pressure is either accurate or appropriate, including the purpose for which the historical blood pressure reading is being monitored or reviewed. For instance a series of post-op Blood pressures may be accurately taken but be quite inappropriate to use for long term hypertension monitoring. The other problem is that you can only make some of these measures of data quality in retrospect e.g. You may have a BP device that has been calibrated correctly but later malfunctions. Or you may have a seemingly competent patient who turns out to have been messing up the process. I can see some value in a simple flag (defaulting to false) to identify BP readings that should not be used for monitoring purposes because they are known to have quality issues or were taken in inappropriate circumstances e.g post-op or severe illness but I think your data quality markers may be too complex to be workable. Regards, Ian McNicoll Medical Informatics From: Stef Verlinden [mailto:[email protected]] Sent: 10 July 2007 10:42 To: For openEHR clinical discussions Subject: Data quality questions/ proposal One of the major requirements we have is what I call a 'data quality marker'. So the blood pressure recorded is 88/124 but what is the 'value/ quality' of this measurement. IMHO any recorded value is useless unless the quality of this measurement can be established and taken into account when interpreting the data In order to establish this data quality we need to add some attributes to the observation archetypes used to record such measurement. So far as we can see now we think that these attributes are a data quality field and a device/instrument reference (which requires a device archetype) and this is what we would like to propose to the community. Since I don't know exactly how to do that and we still have many unanswered questions I'll describe what we're thinking about. It's very well possible that these thing are already in place, in that case we're aren't aware of that and would like to be pointed in the right direction. In our 'model' data quality can be described as: excellent, good, doubtful and insufficient. Here the first hurdle arises: one needs a protocol to define what is excellent, good etc. These are probably 'local' criteria, so the can't be embedded in a general archetype. Our idea is to create a specialisation of the observation archetype in question, in which the local protocol is attached. For instance this blood pressure archetype with the local Dutch data quality criteria would be openEHR-EHR-OBSERVATION.blood_pressure-data_qualityNL.v1.adl To give an example these are the criteria for blood pressure we're thinking off: Excellent: data measured/obtained by a qualified healthcare provider, with a certified instrument/device that's calibrated against a 'golden standard', the measurement error is within a tight bandwidth (<5%), the validity duration of the calibration isn't expired, maintained on time and by qualified personal (This can't be met when self-measuring in the home situation) Good: data measured/obtained by a qualified person (this can also be a properly trained patient/citizen), with a certified (CE marked) instrument/device that's self calibrating, the measurement error is within a tight bandwidth (I.e. machine is approved by the European society of Hypertension (ESH), the machine isn't broke and functioning well Poor/ Doubtful data measured/obtained by a qualified person (this can also be a properly trained patient/citizen), with a certified instrument/device that's self calibrating, the measurement error isn't within a tight bandwidth (CE marking alone allows measurement errors >7%), the machine isn't broke and functioning well Insufficient: in all the other situations As a consequence we need to add at least one other attribute: a reference/ link to the device used. In our opinion there should be a separate archetype for a device/instrument. In this archetypes not only the unique identifiers of this device are recorded but also information about calibration, maintenance etc. etc. So far as I understand/can see such an archetype doesn't exist today. Our idea is to use the demographic archetype model for this. In fact there is already a demographic archetype subtype for 'agents'. So either we extent this subclass so it can be used for devices or we create a new archetype class for devices/instruments based on this agent model. Another thing that is already established is the capability of a healthcare professional. I.e. is this person properly trained to operate a device/instrument? In that respect I would like to add similar capabilities for non-health care professionals. In the above case patients/ citizens also can measure their own blood pressure. Before they can do that, they're trained and examined. Only then they're capable of producing 'good quality' (provided that they meet the other criteria as well) data. Can anybody please comment on this? As stated before it would be really of great help if we could organise some sort of 'archetype boot camp' to create an expanding community of clinicians who know how to create archetypes and harmonize the 'wishes and ideas' that will come up as soon as more people start creating and using archetypes. Cheers, Stef -------------- next part -------------- An HTML attachment was scrubbed... URL: <http://lists.openehr.org/mailman/private/openehr-clinical_lists.openehr.org/attachments/20070710/4c7d8f26/attachment.html>
