Data Source

Other, please specify

Type of Study

Registry

Data gathering method

Health data information system containing anonymised reimbursement and registry data from multiple sources

Conditions of access

Formal agreements (e.g. fees, research contracts, institutional agreements, etc.)

Data is not accessible for researchers unless for very specific purposes; requests should be made to Main Association of Austrian Social Security institutions.

Type of available data (e.g. anonymised microdata, aggregated tables, etc.)

Anonymised microdata

Formats available

Queries for data can be obtained in Excel (.xls, .csv, . Txt)

Language issues

The data is only available in German.

Years of collection, reference years, and sample sizes

Data includes all those covered by social insurance (approximately 98% of the population)

First year of collection

Depending on data (1995, 2001)

Stratification if applicable

Stratification possible for age, gender and district.

Base used for sampling

Registry

Geographical coverage and breakdowns

Austria down to district level

Age range

All ages

Coverage of main and cross-cutting topics

Data collected on drug information, which includes prescription data (updated monthly) and (electronic) reimbursement codex. The data can be broken down by DDD and ATC-codes and by type of medical specialist and geographical region, by cost of drug, area of prescription, sickness fund, type and age of patient since 2000. General information is from sickness funds (financial and cost-performance statistics, number of entitled persons), DIAG-Extranet data (inpatient data), out-patient data (physician cost statistic (Ärztekostenstatistik), ambulatory care providers, e-card consultations and the Population registry data (Statistik Austria). Corresponds to Health and Performance Topic

Further Reading

• Ganjeizadeh-Rouhani, A. "Information Platform: Business Intelligence in Heath Service (BIG)" (2010). (Informationsplattform: Business Intelligence im Gesundheitswesen (BIG)) In: Soziale Sicherheit des Hauptverband der österreichischen Sozialversicherungsträger [in German]

Standardisation

Standardization based on age for the Region and Sickness Fund.

Possibility of linkage among databases

The data warehouse BIG matches data from listed data sources, i.e. matching of alternative drugs to each prescription, thus allowing for calculations on cost reduction potentials. There is no matching on the individual level.

Entry errors if applicable

Not reported

Breaks

Not reported

Consistency of terminology or coding used during collection

Not reported

Strengths: This registry has the potential to match different data sources. Through this system, health experts can find answers to complex and specific research questions regarding health care system performance. Prescription data is updated every month and other data is updated quarterly or once a year. Users may retrieve information through standard reports, ad-hoc queries directly from dataset or may obtain customized reports choosing relevant parameters. Weaknesses: The registry is not user-friendly and researchers need data management expertise in order to use the complex dataset.