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What if We Really Had a Silver Bullet to Deal with Health Information ?. 1 Dec 2011, COMPASS Seminar Koray Atalag, MD, PhD, FACHI. What’s the Problem with Health Information?. We capture heaps of data - sit in silos  Partly structured and coded eg ICD10, ICD-O, READ, LOINC etc.

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what if we really had a silver bullet to deal with health information

What if We Really Had a Silver Bullet to Deal with Health Information?

1 Dec 2011, COMPASS Seminar

Koray Atalag, MD, PhD, FACHI

what s the problem with health information
What’s the Problem with Health Information?
  • We capture heaps of data - sit in silos 
  • Partly structured and coded
    • eg ICD10, ICD-O, READ, LOINC etc.
  • Coding is not easy / expensive
    • Depends on context, purpose, or just coder’s mood!
    • Automated coding is not reliable
  • Difficult to code from free text after capturing
    • Usually context is lost
    • Best at the time and place of data capture
  • Still wealth of valuable information in free text
  • We cannot link, aggregate and reuse!
what are the implications
What are the Implications?
  • Apart from:
    • Safety, quality, effectiveness and equity in healthcare
    • New knowledge discovery and advances in Science
  • Cost of not sharing health information:
    • In US could sum up to a net value of $77.8 billion/yr(Walker J. The Value Of Health Care Information Exchange And Interoperability. Health Affairs 2005 Jan)
    • In Australia well over AUD 2 billion(Sprivulis, P., Walker, J., Johnston, D. et al., "The Economic Benefits of Health Information Exchange Interoperability for Australia," Australian Health Review, Nov. 2007 31(4):531–39.)
if the banks can do it why can t health
If the Banks Can Do It, Why Can’t Health?
  • Clinical data is wicked:
    • Breadth, depth and complexity
      • >600,000 concepts, 1.2m relationships in SNOMED
    • Variability of practice
    • Diversity in concepts and language
    • Conflicting evidence
    • Long term coverage
    • Links to others (e.g. family)
    • Peculiarities in privacy and security
    • Medico-legal issues
    • It IS critical…
wickedness medication timing
Wickedness: Medication timing

Acknowledgement: Sam Heard

wickedness medication timing1
Wickedness: Medication timing

Acknowledgement: Sam Heard

wickedness medication timing2
Wickedness: Medication timing

Acknowledgement: Sam Heard

wickedness medication timing3
Wickedness: Medication timing

Acknowledgement: Sam Heard

wickedness medication timing4
Wickedness: Medication timing

Acknowledgement: Sam Heard

a new approach
A New Approach:
    • Open source specifications for representing health information and person-centric records
    • Based on 20+ years of international experience including Good European Health Record Project
    • Superset of ISO/CEN 13606 EHR standard
    • Not-for-profit organisation - established in 2001 www.openEHR.org
    • Separation of clinical and technical worlds*
  • Big international community and research
key innovation
Key Innovation

“Multi-level Modelling”

separation of health information representation into layers

1) Reference Model: Technical building blocks (generic)

2) Content Model: Archetypes (domain-specific)

3) Terminology: ICD, CDISC/CDASH, SNOMED etc.

  • Data exchange and software development based on first layer
  • Archetypes provide ‘semantics’ + behaviour and GUI
  • Terminology provides linkage to knowledge sources (e.g. Publications, knowledge bases, ontologies)
archetypes models of health information
Archetypes: Models of Health Information
  • Puts together RM building blocks to define clinically meaningful information (e.g. Blood pressure)
  • Configures RM blocks
      • Structural constraints (List, table, tree)
      • What labels can be used
      • What data types can be used
      • What values are allowed for these data types
      • How many times a data item can exist?
      • Whether a particular data item is mandatory
      • Whether a selection is involved from a number of items/values
  • They are maximal datasets–contain every possible item
  • Modelled by domain experts using visual tools
content modelling in action
Content Modelling in Action

Back in 2009 – GP view of BPWHAT HAVE WE MISSED?

Acknowledgement: Heather Leslie & Ian McNicoll

blood pressure ckm review
Blood pressure: CKM review

Acknowledgement: Heather Leslie & Ian McNicoll

blood pressure ckm review1
Blood pressure: CKM review

Acknowledgement: Heather Leslie & Ian McNicoll

blood pressure v2
Blood Pressure v2

…additional input from other clinical settings

Acknowledgement: Heather Leslie & Ian McNicoll

blood pressure v3
Blood Pressure v3

…and researchers

Acknowledgement: Heather Leslie & Ian McNicoll

ckm versioning
CKM: Versioning

Acknowledgement: Heather Leslie & Ian McNicoll

blood pressure translation
Blood Pressure: Translation

Acknowledgement: Heather Leslie & Ian McNicoll

how do they all fit together
How Do They All Fit Together?
  • Common RM blocks ensure data compatibility
    • No need for type conversions, enumerations, coding etc.
  • Common Archetypes ensure semantic consistency
    • when a data exchange contains blood pressure measurement data or lab result etc. it is guaranteed to mean the same thing.
    • Additional consistency through terminology linkage
  • Common health information patterns and organisation provide a ‘canonical’ representation
    • All similar bits of information go into right buckets
    • Easy & accurate querying + aggregation for secondary use
  • Addresses provenance and medico-legal issues
a simple health information organisation

EHR

Folders

Compositions

Sections

Entries

Clusters

Elements

Data values

A Simple Health InformationOrganisation
patterns in health information
Patterns in Health Information

Observations

Clinician

measurable or observable

Published evidence base

Subject

Actions

Personal knowledge

Administrative Entry

Recording data for each activity

Evaluation

clinically interpreted findings

Investigator’s agents

(e.g. Nurses, technicians, other physicians or automated devices)

Instructions

order or initiation of a workflow process

specialisation of archetypes
Specialisation of Archetypes
  • Data conforms %100 to parent archetype
  • International -> national -> regional -> local
  • Generalist -> specialist -> subspecialist

Problem

Diagnosis

  • Text or Term
  • Clinical description
  • Date of onset
  • Date of resolution
  • Side
  • No of occurrences

Diabetesdiagnosis

  • Term
  • +
  • Grading
  • Diagnostic criteria
  • Stage
  • Term
  • +
  • Diagnostic criteria
    • Fasting > 6.1
    • GTT 2hr > 11.1
    • Random > 11.1
providing a canonical representation
Providing a Canonical Representation

Shared Archetypes

etc. etc. etc.

Medications

Clinical Encounter

Vital Signs

Diagnoses

Diagnostic Tests

Family History

Life Style

Demographics

Physical Exam

Genetics

Interventions

Past History

NZ Address

Ethicity1,2.

Whanau

GP visit

Flu-like

PHO enrolm.

BP 130/90

HR 90

T: 38.5 C

Dx 1

Dx 2

etc.

Rx A

Dispense

Administer

Routine Blood

Urine

X-Ray

Subject A

Rx

N/A

N/A

Routine

N/A

N/A

Diabetes Dx

-Type

-Severity

-Course etc.

USAddress

State

Next of kin

Hospital adm.

Diabetes

Priv insurance

Specific blood test

Urine culture

Genomic assay

Retinography

Fluid Tx

Insulineinj

Infection Tx

Psychologic

BP 120/70 (24 hour avg)

HR 70

T: 37 C

Rx B

Dispense

Administer

Detailed

Foot and eyes

DNA Seq.

Assays

Low sugar

Exercise

Pedigree

Chronic

Subject B

Each finding usually depends on other – clinical context matters!

Person-Centric Record Organisation

can clinicians agree on single definitions of concepts
Can Clinicians Agree on Single Definitions of Concepts?
  • “What is a heart attack?”
    • 5 clinicians: ~2-3 answers – probably more!
  • “What is an issue vs. problem vs. diagnosis?”
    • No consensus for conceptual definition for years!

BUT

  • There is generally agreement on the structure and attributes of information to be captured
  • Problem/Diagnosis name
  • Status
  • Date of initial onset
  • Age at initial onset
  • Severity
  • Clinical description
  • Date clinically recognised
  • Anatomical location
  • Aetiology
  • Occurrences
  • Exacerbations
  • Related problems
  • Date of Resolution
  • Age at resolution
  • Diagnostic criteria

Acknowledgement: Sam Heard

achievable
Achievable?
  • ̴ 10-20 archetypes  core clinical information to ‘save a life’
  • ̴ 100 archetypes  primary care
  • ̴ 2000 archetypes  secondary care
    • [compared to >600,000 concepts in SNOMED]
achievable cont
Achievable? – cont.
  • Initial core clinical content is common to all disciplines and will be re-used by other specialist colleges and groups
    • Online archetype consensus in CKM
    • Achieved in weeks/archetype
    • Minimises need for F2F meetings
    • Multiple archetype reviews run in parallel
  • Leverage existing and ongoing international work

Acknowledgement: Sam Heard

thanks questions
Thanks...Questions?

Visit:

www.openehr.org

Not a silver bullet, but definitely a good shot!

k.atalag@auckland.ac.nz