"Quality Issues: Collection,
Coding, Metadata
- some NHS experiences"
Philip Johnston
NHS Scotland, Information Services Division
Quality Issues: Collection, Coding, Metadata
- some NHS experiences
• about Information Services Division (ISD)
• about ISD data
• ISD processes, and some examples
• some statistics on quality
about ISD
• part of National Services Scotland, and NHS
• 40+ years old
• around 650 staff across Scotland
• Scotland's national organisation for health information,
statistics and IT services
• 17 work programmes – eg waiting times, mental health
about ISD data
• around 60 data sets, evolving
• variety of data providers – eg: hospitals, NHS boards, GP
practices, voluntary sector, private sector
• per year: ~60 publications, ~3000 information requests,
~500 Parliamentary Questions
• Part of National Statistics
• “Scotland has some of the best health service data in the
world”
ISD data : some context
• some uses: clinical governance, planning, epidemiology,
performance management, setting policy
• some stakeholders: NHSScotland, Scottish Executive,
Scottish Parliament, local authorities, Audit Scotland, GRO,
researchers, media, public, political parties
• some influences: health policy, devolution, National
Statistics, Freedom of Information, data protection, patient
involvement, IT developments (eg web), media awareness
ISD data : SMR01, an example dataset
• patient/episode -based
• acute inpatients / day cases
• ~100 data items, including clinical codes (ICD, OPCS)
• ~1.2m records/year
SMR01 data collection
• electronic, secure (encrypted)
• varying timetables for submission
• data for ~1000 locations, from ~17 IT systems
• ~100 validation files, with ~3m records
• ~1500 error/query checks
Main condition accuracy at 3-digit level
Scot land
TEACHING HOSPITALS
West er n Inf ir mar y/ Gar t navel Gen & Beat son Hospit als
Royal Inf ir mar y of Edinbur gh, Cit y & PMR Or t ho. Hospit als
Glasgow Royal Inf ir mar y & Canniesbur n Hospit al
Aber deen Royal Inf ir mar y & Woodend Hospit al
West er n Gener al Hospit al, Edinbur gh
Ninewells Hospit al
LARGE GENERAL HOSPITALS
Cr osshouse Hospit al
St John' s Hospit al at Howden
SMR01 quality :
accuracy
Vict or ia Hospit al, Fif e
Vict or ia Inf ir mar y, Glasgow
Queen Mar gar et Hospit al, Fif e
Inver clyde Royal Hospit al
Raigmor e, Cait hness & Belf or d Hospit als
Bor der s Gener al Hospit al
St obhill Hospit al
Per t h Royal Inf ir mar y
The Ayr Hospit al
Falkir k and Dist r ict Royal Inf ir mar y
Wishaw Gener al Hospit al
• Accuracy of coding of
main condition, 200002, by hospital
St ir ling Royal Inf ir mar y
Hair myr es Hospit al
Monklands Hospit al
Sout her n Gener al Hospit al
Royal Alexandr a Hospit al
Dumf r ies & Galloway Royal Inf ir mar y
SMALL GENERAL HOSPITALS
St r acat hr o Hospit al
Vale of Leven Dist r ict Gener al Hospit al
Dr Gr ay' s Hospit al, Elgin
Lor n & Islands Dist r ict Gener al Hospit al
CHILDREN' S HOSPITALS
Royal Hospit al f or Sick Childr en, Edinbur gh
Royal Hospit al f or Sick Childr en, Yor khill
Royal Aber deen Childr en' s Hospit al
0
10
20
30
40
50
60
70
80
Percentage accuracy (target 90%)
90
100
SMR01 quality : timeliness
SMR01 quality : other measures
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•
•
•
•
•
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validity
completeness
fitness for purpose
relevance
coherence
comparability
data ‘sign off’
SMR01 quality – some factors
• conflicting local/national priorities
• IT system issues (eg purpose / specification / delivery)
• timeliness vs accuracy
• quality of source data (eg case notes)
• training and definitions
• changes in service delivery
SMR01 : example of
accuracy versus timeliness
SMR01 : some metadata
• definition?
• Data Dictionary (web-based; ~1500 items), including
definitions and recording manuals
• statistics on quality of data
• data audit controls
• Change Control process
• ‘health warnings’ on outputs
• statistical imputation / suppression
other data collection : some examples
• census of Allied Health Professionals
(non-NHSnet; developmental)
• Scottish Birth Record
(national repository)
• the future, eg: clinical datasets, electronic health record,
SNOMED, data warehouses
Quality Issues: Collection, Coding, Metadata
- some NHS experiences – in summary
• range of complex, interdependent factors affect data
quality
• ISD applies considerable resource to data quality
• ISD ability to measure data quality, and to understand
influences, is essential and is much valued by users