Scientific Concept of the National Cohort (status ... - Nationale Kohorte

A.3
A.3 Study design
tial misclassification, which may decrease systematic and random error in data analysis.
In addition, secondary data use may help complete data collection in instances
where primary data from the participant may not be (or no longer are) available, e.g.,
for deceased study subjects.
2. Support follow-up procedures: Secondary data may support the active and passive
follow-up procedures described in Sect. A.3.7. Since these data are largely independent
of self-report of the participants, their use has considerable potential to improve
completeness and validity of the traditional follow-up procedures. They may also help
in studying ”softer” outcomes that are difficult to assess via active or passive follow-up
procedures.
3. Provide alternative means of acquiring occupational data: Access to data of the
Institute for Employment Research (Institut für Arbeitsmarkt- und Berufsforschung)
represents an alternative means of acquiring occupational data on an individual basis
and thus will reduces the burden for study participants and interviewers.
4. Completion of information on individual medications: All reimbursed medications
are documented with prescription date, ATC code, and prescription dosage by statutory
health insurances. Using these data, medication histories can be assessed over
extended time periods, which can augment and improve the information provided by
the participant.
5. Information on individual health care utilization: Both operations and procedures
during a hospital stay and most interventions performed by the treating physician are
documented by statutory health insurances. These are valuable data that are difficult
to collect via a personal interview. The information includes utilization of screening
examinations, surgical procedures, etc.
6. Evaluate health economics: Since statutory health insurances in Germany cover
a broad range of medical services, most of the direct health-related costs are documented
(as are some of the indirect costs). By using such data we can estimate
diagnosis-associated costs and carry out health economics analyses in Germany.
7. Information on the physical environment: Data collected at the federal, state, and
city level provides a multifaceted characterization of the physical environment in Germany
and is widely used for city and regional planning. The approach proposed here
provides the opportunity to comprehensively assess multiexposure scenarios at the
place of residence or work with relatively high precision at comparably low cost and
provides scientific evidence on the effectiveness of ongoing abatement measures.
One major limitation to the use of secondary data is that data may not be available for all cohort
participants, depending on the specific insurance companies that participants adhere
to and on whether participants will allow extraction and linkage of their insurance data to
the National Cohort data base. Furthermore, the content and format of available data, e.g.
on use of medications and health care, can vary considerably across different insurances
and it may not always be possible to obtain uniform information for all cohort members. It
is anticipated that health insurance data may be obtained for about 60-70 percent of cohort
participants, but feasibility studies will need to be conducted to confirm this. Finally, it
is likely that the availability of health insurance data, in particular, will be associated with
socio-economic indicators, because the data from private insurances, which generally can
be adhered to only by higher-income groups, are not as easily accessible as those from
statutory insurances. Thus, it cannot be ruled out that overall health status or disease risks
differ between subjects whose data can be retrieved, and the rest of the cohort. These, and
possible further complexities will have to be properly addressed and accounted for in statistical
analyses, so as to examine and avoid possible biases that could be induced by the
selective availability of data.
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