This document summarizes information from the SNIIRAM database in France. It discusses: - SNIIRAM is a national database containing medical claims data from primary, secondary, and tertiary care. - It allows linkage of data between different levels of care to study patient pathways. - Examples of studies using SNIIRAM data include analyzing inhaled corticosteroid use patterns in asthma patients, comparing effectiveness of allergen immunotherapy in children with rhinitis, and assessing montelukast's impact on asthma control in infants.

1. SNIIRAM: PRIMARY AND
SECONDARY CARE RESOURCE
USE IN FRANCE – NATIONAL
CLAIMS DATA
Eric Van Ganse, Manon Belhassen
PharmacoEpidemiology Lyon (PEL)
Respiratory Medicine, Croix Rousse University Hospital, Lyon, France
UMR CNRS 5558, Claude-Bernard University, Lyon, France.
January 23, 2015
REG 2015 Winter summit
Maximising the Yield: Databases around the World Part I – Europe & Canada

2. INTRODUCTION
French Health Care System

3. Health Care System:
3
• Established in 1945
• World Health Organization (2000) : France provides "close to best
overall health care" in the world
• In 2005, France spent 11.2% of GDP on health care
• >75% of all health care expenditures are covered by government
funded agencies

4. Health Care System
4
• 46% of General Practitioners (GPs) still work in solo
practices and are ‘self-employed’, while drawing their
income from public funding
• the French National Health Service directly refunds all
patients >70% of all health care costs
• This reimbursement =100% in case of “expensive
long-term conditions”

5. SNIIRAM: PRIMARY AND
SECONDARY CARE
RESOURCE USE IN FRANCE
– NATIONAL CLAIMS DATA

6. Linkage between primary and
secondary care
6
• SNIIR-AM:
• SNIIRAM is the National Information System for the Health
Care Insurance (all systems)
• Implemented in 2004, SNIIRAM is a national database of
medical and HCP interventions (claims)

7. Linkage between primary and
secondary care
7
• The SNIIR-AM is the first information system based on
linkage between:
• Primary care data (GPs and Specialists, Community
Pharmacies,…)
• and…
• Secondary care data (Public & Private Hospitals)

8. Linkage between primary and
secondary care
8
• Data:
• On beneficiaries (individual data and anonymous) information,
ie medico-administrative (LTD number, occupational diseases,
discharge diagnoses from hospitals in ICD 10 codes, date of
pregnancy, …)
• On benefits: detailed identity of all acts, and dates
• On HCPs (individual data not anonymous): identifyer, gender,
age, medical specialty, type of practice, conventional status,
union affiliation, district

9. Linkage between primary and
secondary care
9
Limitations:
• The data model is complex : it reflects the rules of the
Social Security (reimbursement > research)
• Concepts and names are numerous and voluminous
• The time needed to access and process individual data
can be long.

10. Data Collection during the Hospital Stay
• FINESS
•Status : public / private
• Adress
• Patients ID (anonymised)
• Age
• Gender
• Main Diagnosis (DP), Related (DR)
& Associated (DAS)
(ICD-10)
• Acts (≈7 600 codes from the CCAM)
• Products « added »
10
• Mode of entry (home, A&E,…)
• ICU, neuro-vascular,…
• Mode of discharge (home, HAD, SSR,..)
Patients’
records
Hospital DataPatients Data
Medical Data
Data on Patient’s
Management
Financial Data

11. Linkage between primary and
secondary care
11
• EGB:
• The EGB is a cohort at the 1/97 of the beneficiaries of
the social security (national health insurance), whether
they have received healthcare reimbursements or not.
• It currently gathers together some 650,000
beneficiaries of the coverage for salaried workers,
other than civil servants and students (general
scheme), and should eventually cover all of the French
social security schemes over a 20-year period.

12. Linkage between primary and
secondary care
12
• This sample is used:
• to conduct longitudinal studies (individual medical histories)
• to trace the health care pathway of patients over long periods,
both in primary and secondary care
• to estimate the population protected by the social security as
well as the rate of access to health care and the characteristics
of individual healthcare expenditure.

13. Linkage between primary and
secondary care
13
• Strengths:
• EGB is a representative sample covered by all health
insurance plans
• Its rate of sampling, close to 1/100th allows to collect data on a
large population (about 650,000 people in the general
scheme), so answering many questions on the health behavior
of the population
• Thus, it is possible to monitor a population protected by LTD
such as diabetes (13,000 people in the EGB in 2007), severe
chronic respiratory failure (2,500 people) or AD (2,000 people)

14. Linkage between primary and
secondary care
14
• Limitations:
• The education level, income level, or occupational category of
beneficiaries, are missing.
• The sample contains information on the actual care reimbursed,
but self-medication or drugs prescribed but not purchased cannot
be measured.
• Similarly, it is impossible to verify whether absent refills (“gaps”)
are due to lack of prescriptions or to lack of purchase < patients,
as therapy prescribed but not dispensed is not listed in claims data
• No clinical information (examination of the patient by the
physician, results of laboratory tests or imaging)
• No diagnosis, unless seconday care or LTD (“algorithms”)

15. Linkage between primary and
secondary care
15
Access to the data:
• Since 2001, the CNIL has formalized the conditions of use of
the SNIIRAM: users must be formally and nominally
‘habilitated’ and all identifiers of individuals are irreversibly
anonymised before being stored
• The database of Social Security is considered to be secure.
• Today, access to EGB and SNIIR-AM are restricted to “public
teams” working at Universities or Research Institutions
• No way for a drug company to have direct access to the data
(hot debate)

16. THREE EXAMPLES OF
EGB AND SNIIR-AM
STUDIES
RATIO project
APSIs project
SINGULAIR project

17. RATIO project
RELATIVE EXPOSURE TO INHALED STEROIDS
(RATIO “ICS-TO-TOTAL ASTHMA THERAPY”)

18. Background
• Inadequate use of inhaled corticosteroids in asthma
(ICS) are a major cause of loss of asthma control and
unscheduled medical care
• In claims data, the “ICS-to-total-asthma-therapy” ratios
(R) have shown interest to identify asthmatics more at
risk of exacerbations, as a result of insufficient
exposure to ICS for their level of disease severity, and
hence, poor control.

19. Methods
• Patients aged<40, with ≥3 dispensings of anti asthma
drugs in 2005.
• The ICS-to-total-asthma-therapy ratio measured the
proportion of ICS units, out of the overall number of
respiratory drug units (prescribed/ dispensed) during a
12 month-period .
• According to ratio values, patients were classified into 3
groups:
• ICS non users (ratio=0%)
• Low-ICS-ratio group (0% < ratio <50%)
• High-ICS-ratio group (ratio ≥ 50%).

20. Methods
Outcomes
• Markers of asthma exacerbations: asthma-related
hospitalizations, visits to GPs, use of oral steroids
(OCS) or antibiotics (ATB)
Analyses
The outcomes were compared during a 12-month period
between:
• Non ICS users (R=0%)
• Low-ICS-ratio group (0<R<50%)
• High-ICS-ratio group (R≥50%).

21. Results
• Patients in the low-ICS-ratio group had higher rates of
asthma-related hospital admissions, and higher
dispensing levels of oral corticosteroids and antibiotics
than the other groups
R = 0%
N=404
0%<R< 50%
N=792
R ≥ 50%
N=966
p
≥ 1 asthma-related hospitalisation 0.50% 1.89% 0.21% 0.0007
≥ 1 dispensing of oral
corticosteroids (%)
34.6% 53.3% 42.2% <0.0001
Units of oral corticosteroids (mean) 0.5 1.2 0.9 <0.0001
≥ 1 dispensing of antibiotics(1) (%) 56.1% 71.1% 61.9% <0.0001
Units of antibiotics(1) (mean) 2.1 3.4 3.1 <0.0001
Medical visits (mean) 5.4 7.0 5.7 <0.0001

22. APSIs project
COMPARATIVE EFFECTIVENESS STUDY OF
ALLERGENS PREPARED FOR A SINGLE
INDIVIDUAL (APSIS) IN ALLERGIC CHILDREN

23. Background
• Allergic rhinoconjunctivitis (ARC) is a common disorder
with a prevalence of around 30% in the French population
middle-aged population
• ARC may facilitate the development of asthma
• Asthma is present in around 6% of the French population
with consequences on medical resource utilization and
quality of life
• Allergens Prepared for a Single Individual (APSIs) are an
anti-allergic therapy for patients with ARC

24. Objective
• To assess the effectiveness of APSIs in children.

25. Methods
• A population of rhinitis-treated children (aged 5-15 years) with
antihistamines and nasal therapy reimbursed between 2007
and 2010 was identified in the EGB database
• Among them, children initiating APSIs between 2010 and 2012
(index date) were identified
• Each child of the APSIs cohort was matched to a non-APSIs
child with rhinitis (APSIs initiation was taken as index date)
• The outcome was the costs of medical resource utilization
related to rhinitis and asthma of each cohort during 3 years
after APSIs initiation, not taking into account the cost of APSIs

26. Results
• A total of 585 APSIs children (24% with 3 years follow-up) were
identified (63% boys)
• The APSIs cohort was less expensive for the payer than the
reference cohort from the second year (on average 180€/child
in APSIs cohort against 230€/child in reference cohort)
• This difference increased during the 3rd year: APSIs children
saved on average 100€ compared to children of the reference
cohort.
• The differences were mainly due to lower expenses (50%)
related to asthma medications and hospitalizations in the
APSIs cohort

27. Results

28. SINGULAIR project
EFFECTIVENESS OF MONTELUKAST ON
ASTHMA CONTROL IN INFANTS

29. Background
• Montelukast 4mg (MTL-4) is an add-on therapy for
asthmatic infants
• French regulators have requested real-world evidence on
effectiveness of MTL-4 in infants (6-24 months)

30. Objective
• To compare the effectiveness of MTL-4, associated or not
with ICS, vs. ICS without MTL-4, on health outcomes of
infants with mild to moderate uncontrolled asthma

31. Methods
• We preselected infants receiving ≥2 consecutive dispensations
of respiratory drugs (R03 ATC classification) from 2010 to
2012, and presenting an exacerbation within 6 months of the
second R03 dispensing.
• Asthma exacerbation was identified by:
• asthma-related hospitalizations,
• dispensing of oral corticosteroids,
• addition of short-acting beta agonists to existing respiratory therapy,
• switch to a higher ICS dosage, or nebulized CS.
• Infants being treated with ICS without MTL-4 were compared to
those receiving MTL-4 on asthma control:
• the occurrence of a new exacerbation,
• the total number of exacerbations during the 6 months follow-up period
• asthma-related health care utilization

32. Results
Infants aged 6-24 months Number Percentage
With 2 dispensations of respiratory medications (R03) between
March 8, 2010 and December 31,2011
171,392 100 %
 With initial exacerbation (T0) 152,212 88.8 %
 With at least 6 months follow-up from T0 115,489 67.4 %
 MTL4-group 4,490 3.9 %
 ICS group 74,561 64.6 %

33. Results
• Time to occurrence of a new exacerbation was shorter in
ICS group (54.1 days) compared to MTL-4 group (57.7
days). In both groups, more than 3 out of 4 infants had at
least one exacerbation during follow-up.
• Total number of exacerbations during 6 months follow-up:
no statistical difference between MTL-4 and ICS.
Relative risk 95% CI p
Group
(MTL-4 vs ICS)
1,00 0,97 – 1,03 0,8617

34. Results - Health care utilization in both
groups (except for treatment therapy):

35. SNIIRAM/EGB: Overall Conclusions
• French databases are a useful tool to perfom
observational studies: SNIIRAM is one of the largest and
most complete dataset in the world
• Access and data management are complex, but results
are of interest!
• Contact : eric.van-ganse@univ-lyon1.fr