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Data foundations for digital health.pptx
- 1. Data foundations for digital health Dr Heather Leslie @omowizard
- 2. The challenge We humans are biological animals. We are analog devices trapped in a digital world… We are compliant, flexible, tolerant. Photo credits: Unknown; Shvets Production; Pavel Danilyuk; Jonathan Borba: https://www.pexels.com The digital health challenge Yet we people have constructed a world of machines that requires us to be rigid, fixed, intolerant. Donald Norman. The Invisible Computer. 1998 © Atomica Informatics
- 4. Data design • Chaotic • Inconsistent • Fragmented • Reactive • Proprietary Photo credit: Brian Hewitt © Atomica Informatics
- 6. The Information structure problem… • All clinical software programs, registries, messages… have a different underlying information structure OPTIONS: • *Transformation* between unique or unequal information structures OR • Common understanding of information - requiring shared or equal information models © Atomica Informatics
- 7. The Information structure problem… • All clinical software programs, registries, messages… have a different underlying information structure OPTIONS: • *Transformation* between unique or unequal information structures OR • Common understanding of information - requiring shared or equal information models © Atomica Informatics
- 8. Chaotic Proprietary > Fragmented Opaque > < Systematic Open standard < Coherent Transparent © Atomica Informatics Health data ecosystem
- 9. • open·E·H·R | open·air = Open Electronic Health Record (EHR) Open source, ISO 13606-2 Specification - shared EHR architecture Community of members • Industry - vendors, platforms, integrators… • Organisations – health services, eHealth programs… • Individuals – clinicians, informaticians, academics… openEHR International – nfp, UCL © Atomica Informatics
- 10. CLINICIANS model their clinical knowledge Beale T, Heard S. An ontology-based model of clinical information. Stud Health Technol Inform. 2007;129(Pt 1):760-4. © Atomica Informatics
- 12. Reference Model Archetypes Templates Data dictionary International/ National resource ‘Little data’ patterns • Standardised • ‘Fit for use’ • Centrally governed Datasets • Clinical Documents • Messages • Forms • Minimum data sets openEHR infostructure © Atomica Informatics Technical rules
- 13. • Building block • Computable specification for a single clinical concept • Blood pressure • Medication order • Symptom • Diagnosis • Family History • Maximal data set • Universal use-case • Design once, for re-use • Governance is critical Archetype © Atomica Informatics
- 14. Archetype • Building block • Computable specification for a single clinical concept • Blood pressure • Medication order • Symptom • Diagnosis • Family History • Maximal data set • Universal use-case • Design once, for re-use • Governance is critical © Atomica Informatics
- 15. Template • Building block • Computable specification for a single clinical concept • Blood pressure • Medication order • Symptom • Diagnosis • Family History • Maximal data set • Universal use-case • Design once, for re-use • Governance is critical © Atomica Informatics • Data set; multiple archetypes • Computable specification for a specific clinical purpose • Consultation note • Discharge summary • Referral • Death certificate • Ultrasound report • Flexible clinical diversity • Constrain represent the specific use-case • 1-∞ archetypes per template • Governance NOT critical Archetype
- 17. www.openEHR.org/CKM Clinical Knowledge Manager (CKM) © Atomica Informatics
- 18. Blood Pressure review & publication 61 experts 13 countries 15 languages Arabic (Syria) Chinese (PRC) Dutch English Farsi Finnish German Japanese Korean Norwegian Bokmal Portuguese (Brazil) Russian Spanish (Argentina) Spanish (Spain) Swedish © Atomica Informatics
- 19. CKM snapshot Community • 2850 registered users • 105 countries • >1100 volunteer reviewers Archetypes – ~500 • 6000+ data points • 25% published • 31 languages Core archetypes: • Service request • Adverse reaction risk • Tobacco, Alcohol use • Physical exam findings • Lab & Imaging result • Problem/Diagnosis • Procedure • Measurements • Vital signs 16,000+ person hours © Atomica Informatics
- 20. Archetype reuse Leslie H, openEHR Archetype Use and Reuse Within Multilingual Clinical Data Sets: Case Study J Med Internet Res 2020;22(11). Open access from: https://www.jmir.org/2020/11/e23361 Most new data sets/templates ~70-85% reuse © Atomica Informatics How many archetypes? 50 – Primary care <3000 – Hospital
- 21. • Design once, share, reuse • 2 level modelling Standardised archetypes Configurable templates • Free for use • Multilingual • Independent/agnostic of Technology trend Clinical system or application Organisation Project • Lifelong data – cradle to grave • ‘Fit for purpose’ • Reduce+++ data transformation data exchange aggregation & analysis • Basis for standardisation of: clinical decision support AI • Personalized medicine - accurate • Roadmap for existing systems • Bootstrap new development © Atomica Informatics
- 22. Contact Dr Heather Leslie Atomica Informatics heather.leslie@atomicainformatics.com @omowizard openEHR International @openEHR / @clinicalmodels openEHR CKM - https://www.openehr.org/ckm/ openEHR Discourse site - https://discourse.openehr.org/ © Atomica Informatics
Editor's Notes
- When we use computers in healthcare, we have to face the inherent challenges of documenting the gentle art of clinical medicine into binary 0’s & 1’s. In some areas this is simple. In others, not so much. As humans we’re good at filling in the gaps. Think of the most infuriating questionnaire you’ve tried to fill out as a proxy for some of the issues around health data design. Only Yes/No answers when there are shades of grey or it’s not applicable multiple sub questions but only a single answer Ambiguities We can see this. The almost universal experience is that we know we can do it better, despite it being designed by intelligent, well meaning people Yet somehow we aren’t as critical with out data design. We assume the data is good. We assume the data has been designed by someone who knows what they are doing. But who ever looks under the hood of a digital application or checks out the data base. How do we know that the atomic data at the heart of our clinical systems, applications, projects etc is fit for use, much less leveraging this information for accurate applications of decisions support, personalised medicine or AI.
- Doomed to interminable and unsustainable patching between applications or domains
- What does it take to have systems & data that are different?
- My challenge to you is to think of this Lego city as an analogy for our EHRs. With the unseen infrastructure of city planning, electricity, gas, water, sewage etc representing all of the largely unseen parts of the EHR – the architecture, security etc. And the creations built of Lego bricks according to published patterns represent the content of the EHR.
- 61 clinical experts from 13 countries and is now available in 13 languages,