Task 2: Key concepts for assessing a study population using the NHANES-Medicare linked data

This task will describe how to estimate the number of NHANES participants available for an analysis examining the association between obesity and the number of physician/clinic visits identified from Medicare as an example. If you determine your study is feasible and your proposal is approved, there are additional refinements you may want to make to your study population when working with the restricted use data.


Info icon Information

The Medicare data are restricted-use therefore this example will use the NHANES-CMS Medicare linked data Feasibility Files to demonstrate the necessary steps. Similar steps can be used with the restricted-use data when you are in the Research Data Center (RDC).


This example will use data from 1999-2004 NHANES linked with 2005 Medicare data. For simplicity, our study population will include NHANES participants aged 65 years and older at the time of their exam, without missing body max index (BMI) data. As one alternative, we could have included NHANES participants who turned 65 by 2005.

Step 1:

After reading the documentation, the first step is to determine which public use files and variables are needed.

From NHANES data, this analysis requires BMI measurements from the Body Measures examination file, demographic information on potential covariates (age, sex, and race/ethnicity in this example), and variables to calculate variance and weighted estimates from the NHANES Demographic File.

Files and variables needed:

An obese (yes/no) variable will be created using the BMXBMI variable.

			If BMXBMI>=30 then obese=1;
			Else if 0<BMXBMI<30 then obese=0;

The NHANES files need to be merged together and then merged with the NHANES-CMS Medicare linked data Feasibility File. Additional information on creating a study population from NHANES can be found in the Continuous NHANES tutorial and information on how to merge NHANES data with the Feasibility Files can be found in Course 2 Module 7 of the NHANES-CMS tutorial.

Step 2:

It is important to determine which CMS files will be used in an analysis when estimating the sample size with the NHANES-CMS linked data Feasibility Files. The Denominator File should be requested for all NHANES-Medicare linked data and includes enrollment information needed to determine enrollment status and entitlement eligibility. Since this analysis is examining physician/clinic visits as an outcome, the Medicare Carrier File is necessary. However, the Summary Medicare Enrollment and Claims (SMEC) File could also be used, depending on the level of detail desired.
CMS files needed:


Step 3:

As described in Course 2, Module 9, Medicare does not receive individual claims on managed care [Medicare Advantage (MA) or Medicare Part C] enrollees and therefore researchers may want to exclude these beneficiaries from their analyses. Although the respondent-specific information on managed care is not available in the NHANES-CMS Medicare linked data Feasibility File, researchers can estimate how much their sample size will decrease by looking at the managed care percentages in managed care enrollment tables. The link to these tables can be found in the Resources section at the end of this task.

Step 4

If the proposal describing the study and indicating which variables are needed is approved by the RDC (See Course 1, Module 1 for information on the RDC process), additional refinements to the study population may be needed once the data are ready for analysis. For example, you may want to:

For more information and analytic guidelines refer to Course 3 Module 10 Task 1 and/or the NCHS-CMS Medicare Data File Documentation and Analytic Guidelines.


Information icon Information

Restricted access to the NHANES-CMS linked data in the RDC is due to the person-specific data that could permit the identity of a beneficiary to be deduced. Data with beneficiary identifiers are subject to the Privacy Act, Freedom of Information Act and other Federal government rules and regulations. As such, the information is confidential and is to be used only for reasons compatible with the purpose(s) for which the data are collected.





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