1. Measuring asthma prevalence in Swansea using SAIL
Dr C Humphreys

2. Local authority request
Context
Re-opening of landfill site, St Thomas Ward
Resident concerns (long history)
Cabinet member commitment on asthma prevalence
Need answer “independently from ‘Public Health’ rather than from this Council”
“what is called for now is a straightforward presentation of the distribution of asthma at ward level”

3. SAIL Secure anonymised information linkage
Health Information Research Unit (HIRU), Swansea University
IBM Blu C Supercomputer
“One of the fastest computers in the world dedicated to life science research”

4. Anonymisation Other recombined data Operational system HIRU (Blue C)
Validate
Construct ALF*
HIRU (Blue C)
Health Solutions Wales
Other recombined data
Data Provider
Demographic data only
Anonymisation process
Validated, anonymised data
Recombine
Encrypt and load
Clinical / activity data
* ALF = anonymised linkage field
Operational system
HIRU (Blue C)

5. Available datasets Individual level – NHS: Individual level – non-NHS:
Population (NHSAR)
Inpatients - PEDW (HES)
Births [ONS]
Deaths [ONS]
Outpatients [HSW]
Child Health Database Wales
NHS Direct Wales
A&E [Morrison hospital]
GP Data [Esp Swansea]
Laboratory systems [ABM]
Out of Hours Services [Esp Swansea]
Radiology- Imaging
Individual level – non-NHS:
Social Services
Educational Attainment
Clinically rich databases:
Cancer [WCISU]
Screening (multiple conditions)
Congenital Anomalies [CARIS]
Myocardial Infarction
Diabetes
Arthropathies
Ecological datasets (many are GIS):
Census- small areas
Ordnance Survey - Mastermap
Transport
Environmental Health
Government departments & agencies
“500 million records
21 datasets”

6. This map is reproduced from Ordnance Survey material with the permission of Ordnance Survey on behalf of the Controller of Her Majesty's Stationery Office © Crown copyright. Unauthorised reproduction infringes Crown copyright and may lead to prosecution or civil proceedings. National Public Health Service for Wales, licence no. CGP0138.

7. SAIL
Swansea GP practice
Other GP practice
‘A Road’
Developed land

8. Asthma A common condition
Risk factors*
Triggers
Family history
Smoking in pregnancy
Second hand smoke
Probably ‘modern lifestyle’
Housing & heating changes
‘Hygiene’
not outdoor pollution; ?indoor pollution
Exercise
Cold air
Chest infections
House dust mites
Pollen
Fur
Tobacco smoke
Environmental pollution may exacerbate asthma
*BMJ 2005 8

9. What we hoped to achieve
Examine prevalence of asthma among Electoral Divisions in Swansea
Persons
Children
Consider role of GP coding systems and deprivation
This study cannot examine ‘cause and effect’ 9

10. Prevalence of condition
Defining asthma cases
Asthma diagnosis recorded in 2007 [14 codes] Or
Asthma administration code recorded in 2007 [44 codes]
Asthma diagnosis recorded before 2007 and prescribed an asthma drug in 2007 [692 drug codes]
Captured in data
Electronic recording
Diagnostic threshold
Primary care contact
Prevalence of condition

11. Results
97% of Swansea residents registered in GP practices were covered by SAIL
1 in 13 adults met criteria for asthma (18,700 out of 241,500; 7.7%)
1 in 12 children aged 5-14 (8.4%)
WHS: 11% adults 16+
QoF Wales: 6.9%; Swansea: 6.5%
But definition is slightly wider

12. Asthma Prevalence All ages, Swansea EDs, 200712

13. 13

14. Asthma Prevalence, Children Age 5-14, Swansea EDs, 2007

15. Deprivation Correlation co-efficient: 0.23
p (borderline); Kendell’s Tau 15

16. GP practice variation Geography not practice dominated
e.g. St Thomas patients: 10 practices
Most GPs use same clinical system
Read v2; 10 use EMIS*; 1 Read v3
Relatively small number of cases missed
3.8% difference with QoF data
St Thomas area largely unaffected
*Local codes can be created; such codes not be included 16

17. Findings of study presented to residents
St Thomas ward asthma rates are similar to Swansea overall rate
Variation in rates show
no clear geographical pattern
no demonstrable association with deprivation
variation not related to GP clinical systems
SAIL has proved an unique and valuable tool for exploring asthma prevalence at a local level 17

18. Using SAIL Potentially rich source of linked data e.g.
Survival (ONS) after stroke admission (PEDW)
Patient pathway
ALFs & RALFs (residential anonymised linked field) – household factors & outcomes
However,
for some datasets information is incomplete (e.g. GP; A&E)
Secondary use data issues
Data coding
>700 codes have to be identified & agreed for GP data (compared with 2 ICD codes for asthma)
Variation in Read versions
Local

19. Using SAIL Have to be onsite at the University Software
Not easily accessible by public transport; parking issues
Software
Have to be able to programme in SQL to extract data
HIAT uses SQL, SAIL has WinSQL: subtle but very important differences
Unable to take any analyses away unless counts >5
All USB ports are deactivated to ensure this is the case
Quality assurance implications
Resource
This project took 165 hours of analyst time, i.e. approx £4,150; not including protocol development, or other staff cost
Further capacity identified as a requirement of the Observatory

20. Thanks Tracy Price (including providing some slides) Nina Williams
Martin Holloway
Martin Heaven
Ronan Lyons (HIRU)
Caroline Brookes (HIRU)
PMCAT, for assistance with definitional codes
Report available nphs website: Asthma in Swansea
Report of a study to examine the prevalence of asthma throughout the City and County of Swansea using the Secure Anonymised Information Linkage (SAIL) System