I've been working on expressing various queries using HL7 Version 2, Version 3, and FHIR. What I've encounter is probably not shocking to some of you.
5 lines of HL7 Version 2 query encoded in HL7 ER7 format (pipes and hats), translates into about
35 lines in HL7 Version 2 XML, which translates into about
92 lines of HL7 Version 3 XML (about triple that of Version 2 XML), which translates into about
95 characters in one line of FHIR.
When expanded into version 3, a system that understands the principles of HL7 Version 3 can completely "understand" the semantics (but someone still needs to write the software to execute them). In fact, I can turn an HL7 Version 3 XML representation into meaningful English, because the semantics of the message have been so well captured in it.
But, people don't talk the way that Version 3 does, nor do computers. We both use three additional sources of information:
Context: Why are we talking? What's our purpose in having this discussion? Who are we talking to? What are we talking about?
World Knowledge: This includes models of the world that describe the things that we are talking about. What do we know? What does it look like?
Inference: Given what we are told, and context and world knowledge, what can be inferred from the communication. It is because of inference that Postel's law can be applied. DWIM (Do What I Mean), that CPU operation we all wish was in our computers, can be applied when you know what it is the person could possibly have meant from all available choices.
HL7 Version 2 put the model in the message specification, but didn't tell you what it was talking about at a find enough grained level to make it possible for a human to understand the message. It might be a language, but it's almost completely positional, with no human readable mnemonics to aid in understanding.
HL7 Version 3 put the detailed model in the message, rather than the message specification, and used a singular, 6 part model of the world (Act, Participation, Entity, Role, Act Relationship and Role Relationship) to describe everything. V3 is clearly a language for computers to speak in, but not one for humans really. The message is completely detailed, but for a developer, there's so much repeated model to wade through that it's hard to find the point. It's a language that talks about itself as much as it communicates.
FHIR builds on those details HL7 Version 3 models, but keeps that information as "World Knowledge" in the FHIR Specification (much the same way that Version 2 did). What FHIR also did was provide for a representation that makes it easy to find the point. There's just enough granularity in the message to find the code, the identifier, et cetera, for the thing you are looking for.
FHIR goes a step further in adoption of RESTful protocols, because the most common computer operation is to have it answer a question given certain inputs, and get back the answers. And there's a protocol for how to do that that just about everyone using the web already understands. It doesn't need OIDs (or anything with dots and numbers in it) to give it meaning. We automatically know what a query parameter is. And FHIR said "these are the kinds of things we need to be able to represent" when we ask questions.
Semantic Interoperability? Pah. I don't need semantic interoperability. I need the damn thing to do what I mean, or better yet, do what I'm thinking. FHIR at least, and at last, that I can think in.
Keith
5 lines of HL7 Version 2 query encoded in HL7 ER7 format (pipes and hats), translates into about
35 lines in HL7 Version 2 XML, which translates into about
92 lines of HL7 Version 3 XML (about triple that of Version 2 XML), which translates into about
95 characters in one line of FHIR.
When expanded into version 3, a system that understands the principles of HL7 Version 3 can completely "understand" the semantics (but someone still needs to write the software to execute them). In fact, I can turn an HL7 Version 3 XML representation into meaningful English, because the semantics of the message have been so well captured in it.
But, people don't talk the way that Version 3 does, nor do computers. We both use three additional sources of information:
Context: Why are we talking? What's our purpose in having this discussion? Who are we talking to? What are we talking about?
World Knowledge: This includes models of the world that describe the things that we are talking about. What do we know? What does it look like?
Inference: Given what we are told, and context and world knowledge, what can be inferred from the communication. It is because of inference that Postel's law can be applied. DWIM (Do What I Mean), that CPU operation we all wish was in our computers, can be applied when you know what it is the person could possibly have meant from all available choices.
HL7 Version 2 put the model in the message specification, but didn't tell you what it was talking about at a find enough grained level to make it possible for a human to understand the message. It might be a language, but it's almost completely positional, with no human readable mnemonics to aid in understanding.
HL7 Version 3 put the detailed model in the message, rather than the message specification, and used a singular, 6 part model of the world (Act, Participation, Entity, Role, Act Relationship and Role Relationship) to describe everything. V3 is clearly a language for computers to speak in, but not one for humans really. The message is completely detailed, but for a developer, there's so much repeated model to wade through that it's hard to find the point. It's a language that talks about itself as much as it communicates.
FHIR builds on those details HL7 Version 3 models, but keeps that information as "World Knowledge" in the FHIR Specification (much the same way that Version 2 did). What FHIR also did was provide for a representation that makes it easy to find the point. There's just enough granularity in the message to find the code, the identifier, et cetera, for the thing you are looking for.
FHIR goes a step further in adoption of RESTful protocols, because the most common computer operation is to have it answer a question given certain inputs, and get back the answers. And there's a protocol for how to do that that just about everyone using the web already understands. It doesn't need OIDs (or anything with dots and numbers in it) to give it meaning. We automatically know what a query parameter is. And FHIR said "these are the kinds of things we need to be able to represent" when we ask questions.
Semantic Interoperability? Pah. I don't need semantic interoperability. I need the damn thing to do what I mean, or better yet, do what I'm thinking. FHIR at least, and at last, that I can think in.
Keith
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