This is Part 3 in a five-part series on task-workflow Pragmatic interoperability. Feel free to read parts 1 and 2 before Part 3. Thank you to HL7 Standards for hosting this five-post, 10,000-word series about healthcare interoperability the week before HIMSS16. Fittingly, the series was inspired by a HL7 Standards #HITsm tweetchat. Help me (@wareFLO, a HIMSS Social Media Ambassador) spread the Task-Workflow Pragmatic Interoperability word at #HIMSS16 by using the #HIMSSworkflow hashtag!
In Part 2 of this series, I suggested viewing healthcare interoperability as communication between intelligent systems. We should look to the ultimate intelligent system, us, for inspiration.
By way of bona fides I should mention I have four degrees — Accountancy (BS), Industrial Engineering (MSIE), Intelligent Systems (MSIS in Artificial Intelligence), and Medicine (MD) — but I have one more degree I usually donâ€™t mention: an ABD. ABD stands for All But Dissertation. I took all the courses necessary for a Ph.D. in Computational Linguistics, but transferred into Intelligent Systems at the last moment. I took twenty courses in linguistics and natural language processing: phonetics, phonology, morphology, syntax (I & II), semantics and pragmatics, then NLP (I, II, & III) and NLG (Natural Language Generation). Phew! More on my experience in My Virtual Graduate Degree in Computational Linguistics and Natural Language Processing.
There are many interesting connections between linguistics and workflow. They use similar ways to represent sequences of activity; in the case of workflow, tasks; in the case of linguistics, words in sentences and utterances in conversations. Workflow and task context influence speech recognition performance. “Conversational” user interfaces need to recognize user goals, plans, and activities, all of which can be informed by models of work and workflow. Speech recognition and clinical natural language processing rely on workflow technology-based pipelines to convert sound into text and structured data, conduct post-editing quality assurance, and to route results to users.
Interoperability, in its most general sense, is about communication. The ultimate example of interoperability is human conversation. Conversation is the most common, developmentally first, historically oldest and default means of communication. Conversation is powerful. You and I use conversation to change the world, each other, and ourselves.
Conversation is remarkably resilient. We constantly monitor, adapt, accommodate and repair what we say and mean. Some medical informaticists suggest we view health IT workflows as conversations instead of transactions. Conversations can be modeled as workflows. Business process collaboration can be modeled as conversation.
Instead of mere data transactions, EHRs and other health IT systems need conversational workflows, if they are to become more resistant to errorful interpretation. “Which patient are you referring to?” (reference resolution) “I promise to get back to you” (speech act) “Why did you ask about the status of that report?” (abductive reasoning) These interactions include issues of pragmatic interoperability (workflow interaction protocols over and above semantic and syntactic interoperability).
Human conversation would not be possible without special properties of human language. Let see how they compare to healthcare interoperability standard “languages,” such HL7 2.X, C-CDA, and FHIR, used in conjunction with coding systems such as ICD, LOINC, and SNOWMED. These are not human languages, in the traditional sense studied by linguists, but they are languages nonetheless. Computer programming languages arenâ€™t natural languages, but they can be understood by humans, borrow ideas from linguistics (especially syntax and semantics), and sometimes even influence linguistics research (especially computational linguistics). Linguists list six important design principles of human language: arbitrariness, displacement, cultural transmission, duality, productivity, and reflexivity.
Arbitrariness is simply the fact that any form (for example, any string of characters) may potentially have any meaning. For example, any string of characters can, in principle, refer to any diagnosis. Obviously, previous convention guides adding new codes and their meanings to interoperability vocabularies, but, again in principle, we can choose to assign any meaning to any string when we are designing a vocabulary for communication between information systems.
Displacement is the ability to speak of things not immediately present. Human can speak of things that happened someplace else at some other time than the moment of speech. Animals don’t do this. They communicate but only refer to things and events in the moment (“Watch out! Predator!) Similarly, healthcare interoperability messages may refer to patient events in the past.
Cultural transmission makes possible historical continuity across successive generations. Language is not genetically encoded and instinctual. Similarly, interoperability syntax and semantic pass from one generation of health IT professional to another via cultural practice: training, documentation, programming, and so on.
Duality allows a small set of symbols to be combined and recombined to refer to a large set meanings. Patterns occur at both the syntactic and semantic levels. Every day we utter sentences that have never been uttered before, and yet we understand them. Interoperability languages sometimes rely on a smaller set of primitives, but which can be combined to support a wide variety of meaning.
The last two design principles of human language — productivity and reflexivity — are special. It is more difficult to find examples of the phenomena in current healthcare interoperability languages. However, productivity and reflexivity are important to the future of healthcare interoperability languages.
Productivity is the ability to create new words and meanings. Humans coin words and ideas at a rapid clip, seemingly almost effortless (Jabberwocky!). One might argue that productivity in healthcare interoperability languages would be a bad idea. One of the goals of standard vocabularies is to allow comparison for a wide variety of purposes, but especially research. To constantly allow new vocabulary terms seems disruptive. And yet, look at the many problems of moving from just one version of ICD to another. In this light, it’s tempting to argue we need to build some, perhaps limited, form of productivity into healthcare interoperability languages.
Reflexivity is what I am doing now, using language to talk about language. In fact, in this sentence I’m using language to talk about using language to talk about using language! No animals can do this. Not many human systems of communication can do this: Pantomime, traffic signs, fashion, etc. do not. And yet, it is our ability to talk about talking and write about writing that allows us to introspect and debug the very system we are using to introspect and debug. It is a primary means for recursive self-improvement.
To the degree current healthcare interoperability languages resemble human language, it suggests we consider other ways in which they resemble human language. Specifically, current healthcare interoperability concerns emphasize data interoperability, via syntactic and semantic interoperability. Syntax and semantics are both concepts drawn from linguistics. I suggest healthcare interoperability also begin to incorporate ideas from pragmatics, an important subfield of linguistics, with important strategic interactions with syntax and semantics. In addition to syntactic and semantic interoperability, we should begin to emphasize pragmatic interoperability as well.
Stay tuned for (or proceed to… if there’s nothing there, it hasn’t been published yet) The Science Behind Task-Workflow Interoperability: Pragmatic Interoperability Part 4.
- Pragmatic Interoperability: Healthcare Interoperability’s Missing Workflow Layer (Part 1)
- Task, Workflow, and Interoperability Definitions: Pragmatic Interoperability Part 2
- Human Linguistics & Healthcare Interoperability Languages: Pragmatic Interoperability Part 3
- The Linguistic Science Behind Task-Workflow Interoperability: Pragmatic Interoperability Part 4
- Task-Workflow Interoperability Benefits and Next Steps: Pragmatic Interoperability Part 5
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