Medicare Beneficiary Claims Data API (BCDA V2)

Getting Started (cms.gov)

There are three main use cases for value-based care:

Care Coordination - BCDA allows for timely notifications of events like ED visits or hospital admissions, enabling care teams to plan appropriate follow-up care sooner. This can improve outcomes and reduce readmissions.

Gap Closure - BCDA provides more accurate and timely data on things like preventive care gaps or diagnosis coding gaps. This allows providers to be more efficient in their outreach and make the most of patient interactions. Examples include improving Annual Wellness Visit compliance or documenting HCCs.

Financial Forecasting - The timeliness of BCDA data allows organizations to identify cost drivers like high-cost events or episode triggers sooner. This enables more strategic decision-making around resource allocation and interventions to control costs. Examples include projecting spending based on new cancer diagnoses or high-cost prescriptions identified in claims data.

In summary, BCDA facilitates care coordination, gap closure, and financial forecasting by making Medicare claims data available much sooner than the monthly CCLF files. 

Skills and Knowledge needed to use the API

API Interaction: Understanding how to interact with APIs, such as how to construct API calls, interpret responses, handle errors, and paginate through results.

Programming: Proficiency in a programming language that can make requests and handle responses is needed. Python and JavaScript (Node.js) are commonly used for this, but many other languages can also work.

Data Parsing: APIs often return data in NDJSON format, so understanding how to parse these data structures is essential. This involves turning the raw response data into a structure that's easy to work with in your chosen programming language.

Data Analysis: After retrieving and parsing the data, you'll often need to analyze it. This might involve statistical analysis, data visualization, or machine learning, depending on your goals.

Data Security and Privacy: Given that you'll be working with sensitive health data, understanding how to securely handle, store, and transmit this data is crucial. This includes understanding relevant laws and regulations, such as HIPAA.

Healthcare Knowledge: Understanding the context of the data can be very helpful. This might involve knowledge of healthcare systems, medical coding (like ICD-10, CPT, HCPCS, NDC, NPI), Medicare, and Accountable Care Organizations (ACOs).