There are some #openEHR marketing materials circulating that states "openEHR is a clinical data persistence standard" which is incorrect and people is getting and forwarding the wrong message.
First the marketing material mixes what is the #openEHR specification with some implementation (won't name names). Second, openEHR specifications don't even mention how to persist clinical data.
In terms of data #openEHR allows/enables long term clinical data management, but allows vendors to implement the persistence of data in any way, paradigm or technology that fits their needs.
Healthcare information has many zoom levels, from microcellular, tissue, organ or DNA data, to international metrics and statistics, and everything in between. When working on healthcare data platforms it's important to know at which level(s) you are working.
That will determine how you design your components, repositories, rules, APIs, etc. and when your processes change between different zoom levels, for instance, aggregating data.
The data zoom level will also determine how data is exchanged and processed. Understanding that will lead you to a better platform architecture, but not understanding at which zoom level you are working, can lead to a messy software architecture.
Recordé la publicación "Estándares e interoperabilidad en salud electrónica: Requisitos para una gestión sanitaria efectiva y eficiente" de la Comisión Económicapara América Latina y el Caribe (CEPAL) de Naciones Unidas donde hice mención de #openEHR allá por 2011.
Fui coautor junto a Selene Indarte, en ese momento presidenta de SUEIIDISS (HL7 Uruguay), ella escribió desde el punto de vista de la gestión sanitaria y quien les habla desde los estándares y la interoperabilidad.
Creo que la publicación fue muy importante en aquel momento, y para mi que CEPAL me haya dado la oportunidad de escribir con tan pocos años de experiencia en el área, pero con un camino ya recorrido, fue un honor. Aquí la publicación repositorio.cepal.org/handle/11362/3…
In the last couple of weeks I've been studying and testing the #openEHR demographic model which has a lot of potential though it needs some improvements.
First it needs more flexibility to specify roles by setting the identities to optional. Second there is an inconsistency in the languages attribute which is DV_TEXT and a better option would be CODE_PHRASE.
Also, the demographic #openEHR model needs more support by modeling tools, we actually need demographic OPTs to be able to test conformance with the openEHR specs.