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Knowledgebase
Introductory
Articles
CMS offers files from aggregate data to individual person level data. This article describes the differences between the aggregate, public use files, the limited data sets,…
This article describes the Federal Regulations that govern the release of CMS data for research.
The purpose of this article is to identify 1) common strengths of Medicare and Medicaid administrative data and 2) broad limitations for researchers to consider when…
Popular
Articles
This article provides guidance on how to identify hospital emergency room claims from the Medicare files.
Providers that bill Medicare use codes for patient diagnoses and codes for care, equipment, and medications provided. This articles provides resources to identify the codes…
To describe the CMS cell size suppression policy and provide examples of common scenarios and possible options.
Featured Article
There are many different provider variables in the Medicare Fee-for-Service (FFS) Claims and Encounter data. Researchers are often interested in the performing NPI and/or the facility CCN or organizational NPI, but other variables are sometimes…
There are many different provider variables in the Medicare Fee-for-Service (FFS) Claims and Encounter data. Researchers are often interested in the performing NPI and/or the facility CCN or organizational NPI, but other variables are sometimes useful. The purpose of this article is to help you understand these variables and we present the completeness of these data to assist researchers who are designing research studies using Medicare FFS claims and Encounter data.
ResDAC faculty and Technical Advisors (TAs) are frequently asked to recommend a best algorithm for identifying cases, treatments, outcomes, etc.In the experience of ResDAC faculty, there is never a single best algorithm that meets all situations. There is often ambiguity with a mix of clear “yes”, clear “no” and a group in the middle (the “uncertain” ones). How exactly we define the three groups and what we do with that “uncertain” group depends on a variety of factors.
The purpose of this article is to provide an overview of the Centers for Medicare & Medicaid Services' (CMS') payment standardization process, as well as provide methodological documentation that explains how the standardized claim payment amounts for Medicare Part A, Part B, and Part D claims are calculated.
The purpose of this article is to describe how to use the Medicare managed care enrollment information found in the Medicare Beneficiary Summary File (MBSF) Research Identifiable File (RIF) or Denominator in the Limited Data Set (LDS). Medicare managed care is sometimes also called Medicare Advantage, Medicare Part C or Medicare + Choice.
Medicare-paid observation stays may be found in the Medicare Outpatient, Inpatient, or MedPAR files. This article describes how to identify observation stays that appear in each as defined by CMS billing guidance.
For data years 2006 and forward, dually eligible Medicare beneficiaries are identified in the Medicare Master Beneficiary Summary File, Base segment. Initially available only as a RIF, this file was released as an LDS file in 2016. The monthly variable “Medicare-Medicaid Dual Eligibility” identifies dual status.
Dual eligibles are also identified in the Medicaid Analytic Extract (MAX) Personal Summary (PS) file.
The Medicare Hospital Service Area File is one of the few CMS non-identifiable files that can be opened in Microsoft Excel. The article describes the steps to import the file into Excel.
The purpose of this article is to describe what ambulatory surgical centers are and to explain how this provider type differs from other provider types that bill Medicare.
This article describes three variable groups that can be used to identify managed care enrollment for Medicaid beneficiaries. Codes for the variables are also given that identify beneficiaries who received their comprehensive medical care under the Fee-For-Service (FFS) payment system.
This article summarizes two methods available to link mothers and their infants using the MAX data. Frequently researchers using the CMS Medicaid Analytic Extract (MAX) data are looking for ways to link mothers with their infants. Given the available identifiers in MAX data, there are two options.
Values that are "missing" in the Minimum Data Set (MDS) nursing home assessment can be represented by several different symbols. While all of these symbols represent that a value is "missing," the specific symbol indicates the specific reason why the value is missing.
This article has three goals: (1) to describe missing patterns on pain variables; (2) to describe the difference between real missing and skip patterns; (3) to describe which assessments should be used for calculating pain measures. This information is most relevant for researchers who work on either creating their own pain measures or constructing CMS quality measures. The new MDS 3.0 requires nursing home staff to interview residents regarding health conditions, such as pain, mood and cognitive function through…