Although more and more data on lower limb amputations are becoming available by leveraging
the widening access to health care administrative databases, the applicability of
these data for public health decisions is still limited. Problems can be traced back
to methodological issues, how data are generated and to conceptual issues, namely,
how data are interpreted in a multidimensional environment. The present review summarised
all of the steps from converting the claims data of administrative databases into
the analytical data and reviewed the wide array of sources of potential biases in
the analysis of such data. The origins of uncertainty of administrative data analysis
include uncontrolled confounding due to a lack of clinical data, the left- and right-censored
nature of data collection, the non-standardized diagnosis/procedure-based data extraction
methods (i.e., numerator/denominator problems) and additional methodological problems
associated with temporal and spatial analyses. The existence of these methodological
challenges in the administrative data-based analysis should not deter the analysts
from using these data as a powerful tool in the armamentarium of clinical research.
However, it must be done with caution and a thorough understanding and respect of
the methodological limitations. In addition to this requirement, there is a profound
need for pursuing further research on methodology and widening the search for other
indicators (structural, process or outcome) that allow a deeper insight how the quality
of vascular care may be assessed. Effective research using administrative data is
based on strong collaboration in three domains, namely expertise in claims data handling
and processing, the clinical field, and statistical analysis. The final interpretations
of results and the countermeasures on the level of vascular care ought to be grounded
on the integrity of research, open discussions and institutionalized mechanisms of
science arbitration and honest brokering.