1. Governance of clinical information and the role of Electronic Health Records in service delivery Royal College of Physicians, London, November 2007 Dr Dipak Kalra Centre for Health Informatics and Multiprofessional Education (CHIME) University College London d.kalra@chime.ucl.ac.uk Royal College of Physicians, London, November 2007 Dr Dipak Kalra Centre for Health Informatics and Multiprofessional Education (CHIME) University College London d.kalra@chime.ucl.ac.uk

2. Drivers for integrating health information Manage increasingly complex clinical care Connect multiple locations of care delivery Support team-based care Deliver evidence-based health care Improve safety reduce errors and inequalities reduce duplication and delay Improve cost effectiveness of health services Underpin population health and research Empower and involve citizens Protect patient privacy

3. Purposes requiring a semantically computable EHR Manage increasingly complex clinical care Connect multiple locations of care delivery Support team-based care Deliver evidence-based health care Improve safety reduce errors and inequalities reduce duplication and delay Improve cost effectiveness of health services Underpin population health and research Empower and involve citizens Protect patient privacy

4. Clinical decision making needs to combine health records and medical knowledge Descriptions, findings, intentions Professionalism and accountability Health Records Prompts, reminders Bio-sciences Diseases and treatments Medical Knowledge Pathological processes Evidence on treatment effectiveness Clinical outcomesEpidemiology Clinical audit Care plans Research Trustworthy inferences require these to be represented faithfully and consistently

5. Making safe inferences from EHR data Can a single observation be interpreted: is it clear what coding scheme was used? are there qualifiers or co-ordinated terms to modify the meaning? is it clear which measurement units, normal ranges etc. apply to the data? does historical meaning stay the same?

6. Hepatitis, acute, - amoebic - due to poison - infective - syphilitic, secondary Nomenclature of disease, 1948 SNOMED-CT 2006 “Hepatitis due to infection”

7. infective hepatitis now includes syphilis Clinical knowledge evolves!

8. Making safe inferences from EHR data Can a single observation be read: is it clear what coding scheme was used? are there qualifiers or co-ordinated terms to modify the meaning? is it clear which measurement units, normal ranges etc. apply to the data? does historical meaning stay the same? Can the correct inferences be made about the observation: is there enough context in order to know what was meant by the author when the observation was first created? is this contextual information (meta-data) in a standardised form?

9. If we query the EHR List of diagnoses and procedures ProcedureAppendicectomy1993DiagnosisAcute psychosis2003DiagnosisMeningococcal meningitis1996 ProcedureTermination of pregnancy1997 DiagnosisSchizophrenia2006 Can we safely interpret a diagnosis without its context?

10. Clinical interpretation context “They are trying to kill me” Symptoms Reason for encounter Brought to ED by family Mental state exam Hallucinations Delusions of persecution Disordered thoughts Management plan Admission etc..... Diagnosis Schizophrenia Working hypothesis Certainty Emergency Department Seen by junior doctor Junior doctor, emergency situation, a working hypothesis so schizophrenia is not a reliable diagnosis

11. Data archive management EHR data life-cycle Professional accountability Medical knowledge and health culture Life-long EHR Clinical encounter Clinical contextsMedico-legal contexts Potential interpretation contexts schizophrenia

12. Examples of clinical interpretation context within the overall clinical story past, present intended treatments, planned procedures clinical circumstances of an observation e.g. standing, fasting presence / absence / certainty of the finding hypotheses, concerns a diagnosis for a relative but not the patient! confidence and evidence seniority of the author justification, clinical reasoning, guideline references

13. Examples of medico-legal context Authorship, responsibilities, signatories Dates and times occurrence, clinical encounter, recording, schedules, intentions Information subjects whose record is this? (who is the patient?) about whom is this observation? (e.g. family history) who provided this information? Version management Access privileges which need to be defined in ways that can be interpreted across organisational and national boundaries Consents

14. Point of care delivery Continuing care (within the institution) Long-term shared care (regional national, global) Teaching Research Clinical trials explicit consent Education Secondary research Epidemiology Data mining de-identified +/- consent Public health Health care management Clinical audit implied consent Governance requirements faithfulness completeness medico-legal integrity standards conformance consistent semantics privacy management Clinical data life-cycle Citizen in the community

15. Clinical trials, functional genomics, public health databases EHR repositories Clinical devices, instruments Clinical applications Decision support, knowledge management and analysis components Mobile devices Personnel registers, security services The role of EHR interoperability standards Date: 1.7.94 Whittington Hospital Healthcare Record John Smith DoB: 12.5.46 ISO/EN 13606 openEHR.org EHR archetypes

16. openEHR / 13606 Archetypes: a shared library of clinical data structures

18. Equivalent expressions ? = “Have you been getting headaches?”: “Yes”

19. Conclusions Contextual information is essential for the safe interpretation of health records EHR interoperability standards provide a means of representing and communicating this context in a consistent way Archetypes provide a means of systematising EHR data structures and content True semantic interoperability is harder to achieve, but is on the European roadmap This must be our goal to support knowledge-driven health care