  National surveys of the healthcare system in the United States were conducted
to characterize the structure of healthcare system and investigate the impact
of evidence-based innovations in healthcare systems on healthcare services.
Administrative data is additionally available to researchers raising the
question of whether inferences about healthcare organizations based on the
survey data can be enhanced by incorporating information from auxiliary data.
Administrative data can provide information for dealing with
under-coverage-bias and non-response in surveys and for capturing more
sub-populations. In this study, we focus on the use of administrative claims
data to improve estimates about means of survey items for the finite
population. Auxiliary information from the claims data is incorporated using
multiple imputation to impute values of non-responding or non-surveyed
organizations. We derive multiple versions of imputation strategy, and the
logical development of methodology is compared to two incumbent approaches: a
na\"ive analysis that ignores the sampling probabilities and a traditional
survey analysis weighting by the inverses of the sampling probabilities. , and
illustrate the methods using data from The National Survey of Healthcare
Organizations and Systems and The Centers for Medicare & Medicaid Services
Medicare claims data to make inferences about relationships of characteristics
of healthcare organizations and healthcare services they provide.
