Joining NPI and CMS Hospital Datasets with Placekey

Joining NPI and CMS datasets now takes just a few seconds

Introduction: Enhancing Healthcare Data with Placekey

When working with healthcare data, joining datasets from different sources can unlock new insights and streamline operations; however, these datasets are often large, have inconsistent file structures making them difficult to work with. Instead of deriving insights to make strategic decisions, time is often spent wrangling messy data. With Placekey, anyone can join datasets for quick insights in just a few clicks.

Lets take two pre-Placekeyed datasets, the National Provider Identifier (NPI) and the Centers for Medicare & Medicaid Services (CMS) hospital datasets. Joining these datasets can be challenging due to differences in data structures and inconsistent identifiers. Utilizing Placekeys the join datasets tool in the developer dashboard, these two datasets can be joined with just a few clicks.

Placekey is an open entity matching service for places and addresses that helps with deduping, matching, syncing, and merging physical places. If you are interested in doing this join on your own sign up and use the join dataset tool in the developer dashboard.

Insights from the Join

We applied Placekeys to 5,425 CMS hospital records with 7,910,953 NPI records. Joining these on Placekey revealed significant overlaps, with 4,294 shared Placekeys between the datasets. Here's a snapshot of the results:

• Total overlaps: 4,294 Placekeys matched between datasets.
• NPI Dataset:
  • 4,294 values matched for 'Hospital overall rating'.
  • 4,294 values matched for 'Count of MORT Measures Worse'.
• CMS Hospital Dataset:
  •  4,294 Placekeys matched from a total of 5,425.
  •  Added 4,294 'npi' values.
  •  Added 3,375 'provider_last_name_legal_name' values.

This quick analysis provides a comprehensive view of provider data by linking the CMS hospital records with the NPI dataset using Placekey. The overlap of 4,294 shared Placekeys highlights significant alignment between the datasets, enabling enriched insights. For instance, the integration adds detailed metrics such as hospital overall ratings and mortality measure counts to the CMS dataset, while also supplementing NPI data with hospital-specific information like legal provider names. This enhanced dataset creates a unified, more actionable resource for healthcare analysis and decision-making.

How to Perform the Join Yourself

Performing the join between NPI and CMS hospital datasets takes just a few clicks with Placekey. 

Watch the following video for a quick walkthrough.

This demonstration uses a tool available in the Placekey Developer Dashboard to guide you through the steps, making it easy to replicate the process and enrich your datasets with additional insights.

‍About the Datasets

The CMS Hospital Dataset provides information about Medicare-certified hospitals, including quality of care metrics, hospital ownership, and patient experiences. This dataset helps compare hospital performance and ensure healthcare compliance and quality.

The NPI Dataset is a registry of healthcare providers in the United States, offering details such as NPI numbers, provider names, and practice locations. It is essential for provider identification and plays a significant role in hospital billing and reimbursement processes.

What is Placekey

Placekey is an open entity matching API for places and addresses and helps with deduping, matching, syncing, and merging physical places. It helps dedupe, match, sync, and merge information about locations. The Placekey documentation provides comprehensive insights into its design, types, and how to use the API. Placekey supports different types of identifiers, including address_placekey and building_placekey, to provide granular data matching solutions.

Potential Use Cases and Insights

The joined dataset opens up numerous possibilities for analysis:

• Healthcare Compliance: Analyze compliance with CMS regulations and improve hospital operations.
• Billing and Reimbursement: Enhance hospital billing accuracy and streamline reimbursement processes.
• Patient Care Optimization: Identify opportunities to improve patient experiences and care quality.
• Machine Learning Models: Build predictive models to forecast hospital performance and patient outcomes.

Conclusion

Working with healthcare data should be easy. Joining the NPI and CMS hospital datasets through Placekey offers a simple approach to enriching healthcare data. This integration not only facilitates compliance and billing processes but also empowers healthcare providers to deliver enhanced patient care. By leveraging Placekey, organizations can unlock new insights and optimize operations effectively.