linkage of available administrative data-bases in italy

8/6/2019 Linkage of Available Administrative Data-Bases in Italy

1/12


2/12

Data collected for administrative purposes has

extensively been used for health outcomes

research

Administrative data are cheap and provide real

world view of health care patterns and outcomes

However, classification bias and lack of importantinformation might be a relevant issue in some

contexts


3/12


4/12

To identify the same real world entity that can be differently represented

in data sources or when unique identifiers are not available or affected

by errors

All linkage strategies have a dual core: the choice of matching

variables and the decision model. Linkage strategies should minimize

false-matches and false-non matches

ISTAT provides an open source software for record linkage (RELAIS 2.1)


5/12

Matching Variables should be complete, accurate,

consistent

Heterogeneous and uncorrelated sets of identifiers

have greater identification power. For example, last

name, first name and date of birth are mutually

independent, i.e. each provide a unique piece of

information

One or more identifiers among First and Last name,

Fiscal Code, SSN ID Code, Date of Birth, are present in

all available Italian data sources


6/12

All methods rely on a number of comparison functions

Probabilistic Approach:

Several algorithms and comparison functions estimates the similarities across

values of the matching variables in the source datasets

It is then calculated a composite matching weight for each possible pairs

(usually the search space is constrained).

A pre-specified threshold for the matching weight is selected

Deterministic Approach:

There is a full (equality comparison function) or a pre-specified (rule-based

comparison function) level agreement in the values of the matching variables

Fast and accurate with error-free unique identifiers or high quality matching

variables

With poor quality identifiers may lead to low matching rates

Evaluation of matching quality cannot be done with automated routines


7/12

Employment

Linkage StrategyHealth Outcomes

Final Dataset

ID

ATECO code

Firm Identifiers

Employment Dates

Income

ICD-9 Code

Procedure Codes

DemographicsHealth Care Setting

Population At Risk

Anagrafe

INPS

SDO

Analytic Strategy

RiskMapping

[Case-Control Study]

Plausibility Check

against a prioriHypotheses

Communication ofSelected Cases to

PSAL Local Services

Ascertainment of

Occupational Origin

1.

2.

3.

4.


8/12

Local Health

Administration

SDO Search

(2001-2002)

Submitted

to PSAL

Ascertained

Occupational Cancers

Bergamo 19 11 0

Brescia 32 26 11Como 31 15 7

Cremona 50 25 1

Pavia 26 23 7

Milano 133 100 55

Lecco 24 19 4

Lodi 27 26 9Sondrio 4 4 -

Varese 15 12 6

Mantova 20 10 2

Total 381 271 102

Amendola P. et al. G ItalMed Lav Erg 2007; 29:3


9/12

The Health Care Cost of Occupational Diseases

and Injuries

Are Common Chronic Conditions Associated with

the Risk of Occupational Injuries and Diseases?

The linked data repository can be augmented with

ad hoc datasets for conducting special studies

reducing the cost of extensive data collection (i.e.

Progetto Rene, in depth occupational data from

selected populations)


10/12

In a world of limited resources, Public Health should incorporate cost-

effectiveness and opportunity costs evaluation in policy decision making

Cost-Effectiveness represent the expected marginal cost of any health care benefit

provided by an intervention

Opportunity costs represent the loss in health determined by allocating resources for

a particular intervention at the expenses of other existing options

Marginal Costsdue to Injury

Linkage Strategy

PopulationAt Risk

Linkage

Cornestone

Health Care

Costs

Injury and

Disease Data


11/12

The interaction between chronic conditions

and the work environment is not well

known.

E.g. There is some evidence that Diabetes is

associated to higher rates of occupational

Injuries (Sprince et al. J Occup EnvironMed. 2008 Jul;50(7):804-8.)

Linkage Strategy

Anagrafe

INPS

SDO

ICD-9 Code

Procedural CodesPrescription DataPharmacy Claims

DemographicsExemption Codes

Health Care Setting

File F

Pharm.

ASL Files

Personal Identifiers

AT

ECO codeFirm IdentifiersEmployment Dates

Income

INAIL

Injury DateInjury TypeInjury Site

Injury desc

Prevalence Rate of population reporting life domain limitation

by ICF chapter and age

0

5

10

15

20

25

30

Sens

ory

Learnin

g

Commu

nication

Mov

ement

Mobility

Self-

care

Domestic

Life

Interperso

nalIn

teraction

atleast1

limita

tion

1 4- 44 4 5- 64


12/12

Once a linkage routine is developed, administrative data can be augmented with

health surveillance data or clinical data collected forad hoc studies.

E.g. The combined data set would provide accurate information about drug

prescriptions (administrative records), exposure to chemicals (health surveillance),

and health outcomes (from both administrative and health surveillance data).

ICRHICRH

linkage of available administrative data-bases in italy

Documents