Help and resources for working with health care data
Prior to 2022, Home Health Agencies (HHA) billed Medicare for partial payment before an episode of care was complete by submitting a Request for Anticipated Payment or RAP that would later be replaced by a traditional Medicare claim once the episode of care ended(1).
Emergency department (ED) utilization serves as a foundational metric across health services research. Because ED visits are high-cost and high-intensity, the identification of these events is critical for measurement and evaluation of healthcare quality(1). Health researchers rely heavily on administrative datasets like Medicare claims to do this work. Because there are multiple conceptual frameworks for measuring utilization within administrative datasets, navigating these records requires careful methodological consideration.
Published on Sep 21, 2026 by Rebecca Vick
It came to my attention that the MBSF indicates an unbelievably low dual eligibility rate for Puerto Rico.
Medicare beneficiaries may enroll in a private managed care plan (Medicare Advantage (MA)) or in Fee-for-Service (FFS) Medicare (Original Medicare). The Master Beneficiary Summary File (MBSF) includes all beneficiaries enrolled in Medicare for at least one day of the year and contains variables that distinguish MA from FFS enrollment(1). Medicare Research Identifiable Files (RIFs) that contain utilization data include only subsets of beneficiaries depending upon how they are enrolled.
Professional and technical components are HCPCS modifiers that splits Medicare payment into supervision/interpretative and equipment/facility costs. This allows separate entities to bill for their portion of a service. For example, one facility may manage diagnostic testing while a physician or other health care provider handles interpretation(1). This can also apply in situations where an independent diagnostic facility has two different service locations(2).
Published on Aug 24, 2026 by Samantha Saykao
Institutional providers, such as inpatient facilities, are required to report clinical trial information through the Claim Value Code and Claim Value Amount variables.
The Claims Processing Manual (CPM) is the rulebook for submitting claims to CMS. It covers a wide range of medical coding instructions by clinical setting and form. As the main source of instruction on claims processing and assuming that providers are incentivized to follow submission requirements for reimbursement, it should be a reliable source for defining research methodology.
Medicare fee-for-service (FFS) research identifiable files (RIFs) include both approved and denied claims as well as claims that are denied in part. Claim denials are common, surprisingly complicated, and important for researchers to consider. The choice to include or exclude them could impact study inference(1). Understanding how to identify claims that are denied in whole or in part is key to selecting claims for an analysis.
The Master Beneficiary Summary File: Base file (MBSF: Base), a research identifiable file offered by CMS, contains two annual race variables: the Beneficiary Race Code and the Research Triangle Institute (RTI) Race Code. There are studies that look at the accuracy of these race variables(1,2), but there is little information about whether the information changes within the data itself.
The Centers for Medicare and Medicaid Services (CMS) collects service-level encounter data from Medicare Advantage Organizations (MAOs) for the purpose of recording diagnoses used for risk adjusted payments to MAOs(2). Unlike a fee-for-service (FFS) claim, an encounter record is not a direct record of payment and not used for billing purposes. Thus, Encounter Research Identifiable Files (RIFs) have some unique aspects to consider: