# Ankle brachial pressure index

**URL:** https://discourse.openehr.org/t/ankle-brachial-pressure-index/3362
**Category:** Ask IEB
**Tags:** archetype
**Created:** [19 December 2022 13:35 UTC](https://discourse.openehr.org/t/ankle-brachial-pressure-index/3362 "2022-12-19T13:35:05Z")
**Posts on this page:** 1
**Showing post:** 23

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### Author: ![heather.leslie](https://discourse.openehr.org/user_avatar/discourse.openehr.org/heather.leslie/32/1980_2.png) [@heather.leslie](https://discourse.openehr.org/u/heather.leslie)
#### Post date: [13 February 2023 22:40 UTC](https://discourse.openehr.org/t/ankle-brachial-pressure-index/3362/23 "2023-02-13T22:40:14Z")

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> [@thomas.beale](#):
>
> We need to think together (clinical + technical groups) on what these additions might be.

Maybe, but [your explanation about why you didn’t need Clinical Program collaboration](https://discourse.openehr.org/t/collaboration-between-programs-and-tooling-vendors/1942/2) created a significant barrier to participation, confirmed by:

> [@Collaboration between programs and tooling vendors](https://discourse.openehr.org/t/collaboration-between-programs-and-tooling-vendors/1942/2):
>
> … I think we get a reasonable amount of insight into current clinical needs this way.

There is no doubt that both programs working together in sync is a critical success factor for openEHR IMO, but we need a serious change in culture for the future Clinical Program to be able to effectively work alongside the techs/engineers/Specs program, as equals. I didn’t ask for a collaboration so that you could teach me. In fact, I wanted opportunities to educate you about our modelling practice because, time and time again, despite your long list of tech-friendly clinicians, it is clear that you often don’t understand the reasoning and experience that underpins the current modelling, or have any curiosity to find out.

> [@thomas.beale](#):
>
> The lesson here in my view is that we need a **meta-classification of clinical statement types** that indicates the modelling style to be used, i.e. things like:
> 
> - _native data group_ (molecular style): BP, Apgar, Problem/Dx etc
> - _virtual data group_ (molecule with citations of other elements): BMI and some other scores/scales;
> - _common data collection_ - typical lab panels e.g. CHEM7, thyroid, LFT etc
> - _standalone element_ (atomic style) - height, weight, HR, most lab analytes
> - … maybe more

I know you want to engineer modelling patterns to make sense, but health data is inherently messy and for every pattern we potentially identify, we find instances that break them. There is a danger in potentially overthinking this only to create more confusion with little added value .

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