Linked Life Data

18985403

Source:http://linkedlifedata.com/resource/pubmed/id/18985403

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
10
pubmed:dateCreated
2008-11-5
pubmed:abstractText
Conducting health services research requires a wealth of real-life health service data. A source of data which is for the most part free of bias is the data collected for administrative purposes by the statutory health insurance fund. These data have been increasingly used over the past few years. Based on these insuree-related and where possible cross-sector data, descriptive and analytic studies can be conducted. The focus of use thus far has primarily been the generation of basic data on morbidity, the utilization of benefits, and costs. As a rule, this information is presented according to sociodemographic variables and where applicable in terms of temporal trends and according to region. A further domain of interest is the evaluation of interventions (health political measures, legislation, programs) and the assessment of health service quality. Initial outcome studies have been published. Despite the growing acceptance and use of these data, a series of methodological and information technical challenges remain to be addressed: To be mentioned are, in addition to validation studies, the methodological requirements of analytic study designs and the possibility of a data linkage with primary data in order to increase the explanatory power of studies and to facilitate links with other databases such as records and survey data.
pubmed:language
ger
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Oct
pubmed:issn
1436-9990
pubmed:author
pubmed:issnType
Print
pubmed:volume
51
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1095-105
pubmed:meshHeading
pubmed:year
2008
pubmed:articleTitle
[Health services research based on routine data generated by the SHI. Potential uses of health insurance fund data in health services research].
pubmed:affiliation
PMV forschungsgruppe, Universität zu Köln, Köln, BRD. Ingrid.Schubert@uk-koeln.de
pubmed:publicationType
Journal Article, English Abstract, Review