Getting Health Information Right


Published on

I gave this prezo to Auckland Regional Clinical IS Leadership Group on Feb 21, 2014. It shows how difficult it can be to deal with certain kinds of health information when developing systems by an impressive example (originally from Dr. Sam Heard). Therefore we need rigorous and scientific methods to tackle this - in this case using openEHR's multi-level modelling approach to create a single content model from which all health information exchange payload definitions will be derived. New Zealand's Interoperability Reference Architecture (HISO 10040) is underpinned by openEHR Archetypes to create this content model. The bottom line of the prezo is that almost every national programme starts health information standardisation from the wrong place; most of them are complex technical speficifications, like CDA, which are almost impossible for clinicians to comprehend and provide feedback. The process is flawed! Instead it should start from simple to understand representations, such as simple diagrams, mindmaps etc.and then handed over to techies once clinical validity and utility is agreed upon.That's the beauty of Archetype approach - great tooling and the Clinical Knowledge Manager (CKM) enable clinicians and other domain experts to collaborate and develop clinical models easily.

Published in: Health & Medicine
1 Comment
  • Be the first to like this

No Downloads
Total views
On SlideShare
From Embeds
Number of Embeds
Embeds 0
No embeds

No notes for slide
  • Hi, I work at the National Institute for Health Innovation in Univ. Of Auckland as a senior research fellow.I was trained as a medical doctor with PhD in Information Systems and a Fellow of the Australasian College of Health Informatics. I am a member of HISO, Vice-Chair of HL7 New Zealand and lead the openEHR Localisation Program.I have co-authored the national Interoperability Reference Architecture (HISO 10040)My main research interests are clinical information modelling, interoperability standards and software maintainability. I am using openEHR Archetypes to create computable clinical information models.
  • METeOR meta-data registry sunsetted
  • ... And more
  • ... And more
  • ... And more
  • These are the three building blocks – or pillars – of the HISO 10040 series that embodies the central ideas of the Reference Architecture for Interoperability10040.1 is about regional CDRs and transport10040.2 is about a content model for information exchange, shaped by the generic information model provided by CCR, with SNOMED as the default terminology, and openEHR archetypes as the chief means of representation10040.3 is about CDA structured documents as the common currency of exchange – not every single transaction type, but the patient information-laden ones
  • Published by HISO (2012); Part of the Reference Architecture for Interoperability“To create a uniform model of health information to be reused by different eHealth Projects involving HIE”Consistent, Extensible, Interoperable and Future-Proof Data
  • Definition of health information in each use case (different CDA documents or using Web services based exchange) comes from the same library.With Archetype specialisation all data collected using definitions of different granularities are semantically compatible.For example a query retrieving all Lab Tests (not specifically HbA1c) will also fetch all specialised versions of Lab Tests.
  • A significant opportunity arises for secondary use in this scheme by the use of a data repository that can natively persist and query standardised datasets. Since all health information in transit in various formats (e.g. HL7) within a standard message (payload) conforms to the Content Model, all data persisted in this repository can safely be linked, aggregated and analysed.
  • CDA definitions for messaging is not a starting point but an end point.The source of truth for health information definition is with the Content ModelIt is possible to create CDA definitions based on specific use cases using automatic or semi-automatic XSL transforms.
  • Getting Health Information Right

    1. 1. Getting Clinical Information Right Emerging Medication Standards Koray Atalag, MD, PhD, FACHI HISO Member HL7 New Zealand Vice-Chair openEHR Programme Lead The National Institute for Health Innovation
    2. 2. Agenda • The problem • What‟s out there? • Medication Example • Methods & Standards • Recommendations & Discussion
    3. 3. What’s the problem? • Healthcare is hard! – Breadth, depth, complexity, variability etc. • So is dealing with health information... – What is a Heart Attack? – Is there such a disease as hypertension? – Is Diabetes a single disease? • Burning issue: getting a core dataset ASAP – Who will be responsible to govern definitions? – How to coordinate and support dataset teams? – How to get clinicians/experts on the same page? • An obvious gap in current approach • Start with Medication (+ Allergies & ADR)
    4. 4. So what’s actually out there? • PMS: each vendor has own data model • GP2GP: great start for structure • NZePS: started with a propriety XML payload, now waiting for standard CDA – PMS vendors implementing Toolkit based Adapter • • • • Shared Care / Maternity / St John? Hospitals? Labs & Pharmacies? Others?  Can you really trust incoming data? (without human control)
    5. 5. Unified Medication Definition • Essential to get it right – first in patient safety! – Needs to be clinically valid, computable and support multiple use • Reused in many places, including: – – – – – – ePrescribing, eReferrals My List of Medicines Shared Care systems Patient and clinician portals Health (status & event) summary Public Health / Research • New HISO Connected Care suite of standards – HISO 10043 CDA Common Templates – 10041.1 CDA Templates for Medications, Allergies and Adverse Reactions just passed public consultation – coming soon • NZMT / NZULM & Formulary > great start!
    6. 6. Why bother? (with a standard structured Medication model) “If you think about the seemingly simple concept of communicating the timing of a medication, it readily becomes apparent that it is more complex than most expect…” “Most systems can cater for recording „1 tablet 3 times a day after meals‟, but not many of the rest of the following examples, ...yet these represent the way clinicians need to prescribe for patients...” Dr. Sam Heard
    7. 7. Example: Medication timing Acknowledgement: Sam Heard
    8. 8. Medication timing – and more!! Acknowledgement: Sam Heard
    9. 9. Medication timing cont. Acknowledgement: Sam Heard
    10. 10. Medication timing – cont. Acknowledgement: Sam Heard
    11. 11. Medication timing – even more! Acknowledgement: Sam Heard
    12. 12. HISO 10040 Interoperability Reference Architecture 10040.1 R-CDRs XDS 10040.2 CCR SNOMED CT openEHR 10040.3 CDA Acknowledge Alastair Kenworthy
    13. 13. The Principles 1. 2. 3. 4. 5. 6. 7. Align to national strategy: as per national and regional plans Invest in information: use a technology agnostic common content model, and use standard terminologies Use single content model: information for exchange will be defined and represented in a single consistent way Align to business needs: prioritise the Reference Architecture in line with regional and national programmes Work with sector: respect the needs of all stakeholders Use proven standards: adopt suitable and consistent national and international standards wherever they exist (in preference to inventing new specifications) Use a services approach: move the sector from a messaging style of interaction to one based on web services
    14. 14. It’s REFERENCE LIBRARY (of reusable clinical information models) Data & meta-data definitions (data dictionary) Relationships & clinical terminology
    15. 15. Usage of the Content Model
    16. 16. Health Information Exchange & More Single Content Model Automated Transforms PAYLOAD CDA System A Map To Content Model FHIR HL7 v2/3 EHR Extract System B Map To Content Model UML XSD/XMI PDF Mindmap Data Source A Data Source B No Mapping Secondary Use Native CDR / Datamart
    17. 17. Creating CDA Payload
    18. 18. Draft HISO Medication Standard
    19. 19. Peer review of models
    20. 20. Resulting Models (using CKM Tool)
    21. 21. Who else is doing it?
    22. 22. Other upcoming HISO standards • • • • 10041.4 CDA Templates for Referral Requests 10040.4 Clinical Document Metadata Standard 10050.1 Maternity Data Set Standard 10050.2 CDA Templates for Maternity Care Summary • 10052 Ambulance Data Set Standard They all share common clinical concepts; certainly the Medication Definition – Who’s responsible for making sure they are aligned? – What mechanism exist to assist dataset developers / clinical domain experts? – How do you keep them aligned over time / governance?
    23. 23. Options / Recommendations  Who can be responsible for making sure datasets are aligned and interoperable?  MoH, NHITB, HISO, HIGEAG, NICLG, other?  What mechanisms to assist dataset developers / clinical domain experts?  Policy, principles, guides, examples  HISO 10040.2 Exchange Content Model  Tools? CKM but also Word, Excel, mindmaps, UML  How do you keep them aligned over time / support governance?  CKM – Not Data dictionary, meta-data registry, Excel
    24. 24. Bottom line • Content is „clinician‟s stuff‟ – not techy; – yet most standards are meaningless for clinicians • We need to invest in information – Whatever technology will be • Method defined in HISO standard – Worked well for Medications • Let‟s build rest of it as we go! – NIHI is keen to facilitate clinical content development and governance + tooling support – This will also fulfil MoH “Data Dictionary” need
    25. 25. Thank you  Questions? The National Institute for Health Innovation