This presentation provides an insight into the challenges of eHealth data and information.

1. Hildegard McNicoll
Why is eHealth so hard?

2. Healthcare realities …
Large and segmented
populations
Safety critical but distractible
environment
Generally poor IT infrastructure
Highly politicised
Culturally nuanced
Increasingly mobile ageing
population
Information governance issues

3. Healthcare is powered by information
To facilitate immediate care
To facilitate review of care
quality
To inform healthcare
management
To inform research

4. Why is health information so hard?
Very different kinds of information
Compressed, summarised
information
Reporting
Making sense of complex care
Large number of complex datatypes
not just string, numeric, url, date

5. Biomedical concepts
Symptoms, examination signs
Lab tests, imaging results
Illnesses, procedures
Asthma
Depression
Appendicectomy
Medications, devices
Penicillin 250mg tablets
Hip arthroplasty component

6. Documentation of care
Immediate care context
Diagnosis (name, dates, grade)
Lab test (name, result)
Medico-legal context
Who, when, why, what, how

7. Compression and summarisation
Registry and research
coded diagnosis versus Y/N
‘Curated’ problem lists
Remove ‘inactive’ or trivial problems
Add new problems ? all problems
From whose perspective?

8. Medication ‘dose syntax’
How can we capture a prescription like
“Co-codamol 8mg/500mg/5ml oral suspension 5-10mls
4-6hourly for 7 days for pain, maximum 40mls daily”
How can we cope with dose vs product prescribing

9. Medication ‘dose syntax’
How can we capture a prescription like
“Co-codamol 8mg/500mg/5ml oral suspension 5-10mls
4-6hourly for 7 days for pain, maximum 40mls daily”
How can we cope with dose vs product prescribing

10. Complex datatypes
Coded terms
Dates and times
Durations
‘Ordinals’
Multimedia
Proportions
Quantities with units
Interpretations

11. Task / workflow management
Track progress of referral
Referral requested
Referral scheduled
Referral performed
Referral cancelled

12. External terminologies
Medications / drug allergies:
dm+d, RxNorm, proprietary
Conditions, procedures:
ICD-10, SNOMED-CT
Lab tests/ analytes:
LOINC, SNOMED-CT
Organisation types, Sex / gender:
Local/national admin terminologies

13. Health information is nasty

14. Health information is nasty
Complexity is a challenge for
any e-Health developer
building APIs, messages
building apps
Need good requirements from
clinicians
How do we know they are widely
applicable?
How do we make sure that we
capture and share that clinical
knowledge?