Integrating Administrative Data in Health Studies:
A Case Study
Martin Kenneally
m.kenneally@ucc.ie
Brenda Lynch
brendalynch@ucc.ie
Objectives
• Profile the Health Status of Irish Regions (2010)
• Link Regional Health Profiles to Regional Prescribing.
• Incorporate Regional Demographics, Community Drug
Scheme Coverage rates and Prescribing Norms
• Simulate effects of Health Status, GMS coverage &
Demographics on Prescribing Rates & Cost outcomes.
• Identify correlates of health status
Profile Regional Health Status
• Construct a Composite Health Index to;
• (a) Calibrate the health status of 8 Irish regions below
• (b) Use Ireland as Standard with base value of 100.
Regions
Counties
1. East
Dublin
Kildare
Wicklow
2. Midlands
Laois
Offaly
Longford
3. Mid West
Clare
Limerick
N Tipperary
4. North East
Cavan
Louth
Meath
5. North West
Donegal
Leitrim
Sligo
6. South East
Carlow
Kilkenny
S Tipperary
7. South West
Cork
Kerry
8. West
Galway
Mayo
Roscommon
W. Meath
Monaghan
Waterford & Wexford
Profiling Steps
1. Select Health Indicators: (mainly morbidity rates) for each type
of major health condition
2. Standardized Rates = national/regional morbidity rate *100
3. Aggregate Rates: using Prescription Weights.
3(a) Aggregate separately for GMS, DP and LTI drug schemes in
each region.
3(b) Then Aggregate across schemes in a region (using coverage
weights) to obtain that region’s Regional Health Index
• (i) Use Index to Benchmark Regional Health Status
• (ii) Use Index to Benchmark Regional Health Gaps
• (iii) Simulate selected policy outcomes
• (iv) Identify Correlates of Health Status & Health Gaps
Official/Administrative Datasets Available
• Official: CSO e.g. QNHS – Health Module (Used)
• Admin: non-CSO, respondent centred, dedicated focus e.g.
• IPH: General. Morbidity Prevalence Rates by County (Used)
• PCRS: Drug Scheme Coverage & Prescribing data (Used)
• Health Atlas: Focus on Public Patients
• Tilda: Focus on Over 50s (Ageing)
• SLAN: Focus on Lifestyle, Attitudes & Nutrition. Periodic.
• CME: General, 2008/9 only [BNF not ICD codes used].
Technical Challenges
• Missing Definitions, sources and methods
• Disjoint Definitions/Concepts e.g. CSO vs PCRS ‘regions’
Health Data Gaps
QNHS Health Module covers 19 Health Conditions:
(i) ‘Adults only’ (excludes under 18s)
(ii) Rates refer to “at any time in a respondent’s past”
(iii) Excludes GERD & pregnancy/immunization services and
(iv) Does not cross-tabulate conditions by region/medical cover.
PCRS: Publishes prescribing by scheme, region, age & gender
but does not publish allied morbidity rates on the same basis.
Upshot, we don’t know;
(i) How much morbidity rates of ‘public’ & ‘private’ patients differ
(ii) How much GP visit rates reflect ill-health v’s type of health cover
(iii) How much prescribing rates reflect ill-health v’s health cover
Community Drug Schemes Incorporated
Incorporated
• 1. GMS (General Medical Services)
Means tested. Income adjusted for mortgage/housing, childcare, travel
costs, savings etc.
Discretionary Medical Card also granted to avoid “undue hardship”.
• 2. DP (Drug Payment Scheme) –
Not means tested. Person/family pays first €144/month; HSE pays any excess
• 3. LTI (Long Term Illness)
Not means tested. Schedule includes - Cerebral Palsy, Spina Bifida, Epilepsy
Acute Leukaemia, Multiple Sclerosis, Diabetes &
***************************************************************************************
Not incorporated
• HTD (High Tech Drug Scheme) – mainly hospital originated anti-rejection
drugs for transplants and chemotherapy
Regional Population % Covered by Each Scheme in 2010
GMS
DP
LTI
HTD
All
35
61
3
1
100
1.East
28
67
4
1
2. Midlands
38
58
3
1
3. Mid-West
38
59
2
1
4. North-East
38
58
3
1
5. North-West
49
47
3
1
6. South-East
41
55
3
1
7. South
36
61
2
1
8. West
41
56
2
1
Ireland
100
100
100
100
100
100
100
100
Methodology
1) Select 28 health indicators (18 prevalence rates/10 others)
2) Assign to 6 ATC Health Categories/Dimensions: Alimentary,
Cardio, CNS, Respiratory, Various & Other
3) Break down 6 ATC categories into 24 Therapeutic Drug Groups
4) Construct (prescription weighted) Composite Health Indices
for the 6 ATC categories under each scheme in each region.
5) Aggregate scheme-specific Indices into Regional Indices
(using scheme coverage weights). Base Value is Ireland = 100
KL Composite Health Index
Index
115
110
105
100
95
90
85
80
Midlands 91.89
North West West - 96.52
94.04
South East 97.05
Republic of
Ireland - 100
South 100.48
North East 102.31
Mid West 103.92
Region
East - 106.14
Largest Health Gaps by ATC Category
Index
135
130
Mid West - 129.56
125
120
115
North East - 108.25
110
East - 104.39
105
East - 105.50
ROI - 100
Best Health
Worst
Health
East - 107.91
West - 102.26
100
ROI - 100
Mid - 92.91
95
90
Mid-West - 95.76
Mid - 95.15
North West - 91.28
Mid - 86.87
85
Mid - 84.97
80
75
70
VARIOUS
ALIMENTARY TRACT
NERVOUS SYSTEM
OTHER
CARDIOVASCULAR
RESPIRATORY SYSTEM
ATC Category
Health Gaps & Weights in East & Midlands Regions
%
30
20
22.93
10
10.79
4.75
13.10
14.22
5.85
0
12.85
Absolute difference between
East's CHI and Midland's
CHI
7.99
2.46
16.58
-10
26.02
32.54
-20
National ATC % Weighting
-30
-40
ALIMENTARY
TRACT
VARIOUS
NERVOUS SYSTEM
OTHER
RESPIRATORY
SYSTEM
CARDIOVASCULAR
ATC Category
Simulated Prescribing & Cost Outcomes
• We constructed & validated a simulation model.
• Simulation Model incorporates regional health status,
scheme coverage & prescribing norms;
• Simulates number & type of drug prescribed in each region
in 2010 with high (97%) accuracy
• Prescribing semi-elasticity w.r.t. GMS coverage is twice semi-
elasticity w.r.t. health-status
• Pattern and causes of regional unit drug cost variations still
under investigation.
Income, Demographics, Coverage & Health Status
Region
CSO Disposable Percentage Aged % Covered by
Income 2010
over 65
GMS
Composite Health
Index
East
20,300
10.00%
28%
106.14
Republic of Ireland
19,300
11.10%
35%
100.00
South
19,200
12.00%
36%
100.48
Mid West
19,100
11.80%
38%
103.92
West
18,500
12.30%
41%
96.52
South East
18,100
12.00%
41%
97.05
North East
17,300
10.00%
38%
102.31
North West
17,300
13.00%
49%
94.04
Midlands
17,100
11.00%
38%
91.89
Unanswered Questions & Policy Issues
1) Macro-causality pattern of regional health status
remains “Smudged”
2) “Ground-clearing”: lacking the with precision of, say,
Kabir et al. 2013 on CHD
3) North-West v’s North East (for example):
• Why is GMS cover in NW so much higher? (Equity)
• Is poorer NW health status due to poor demographics?
• How much do other factors contribute to health status?
Recommendations to Increase Usability
• Working Party of Official & Admin Groups to Agree;
• Common and individual domains
• Common base observation unit (e.g. DEDs for SAPS & Census)
• Common publication unit (NUTS3 or NUTS4)
• Harmonised methodologies.
• ‘Definitions, Sources and Methods’ manual (IPH/PCRS)
• Linked prescribing and morbidity data (for policy analysis)
• Published accessible anonymised (Statbank style) Archive
Tables
• Increased professional statistical input
• The End