Expanding Your Population Health Data Foundation to Claims and Beyond


Post by Niranjan Sharma


Director of Engineering for Healthcare Analytics Platform & Applications, Caradigm

Healthcare is traditionally thought of as the care of patients by healthcare providers. Clinical data is generated during that care, and payers reimburse providers for the services rendered based on submitted claims. For providers engaging in population health, working solely with clinical data only tells part of the population health story. Most healthcare organizations are striving to derive more value and population insight by including claims and other types of data so that they can better stratify their populations, drive other analytics efforts, and improve care coordination among many activities. 

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Siloed Data Challenges

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The challenge is that it is complicated to ingest, normalize and model different types of healthcare data. Healthcare organizations often have many disparate information systems, and many work with partners who in turn also have many disparate systems. Most providers are still working towards harmonizing all of their data so they can view a single picture of their populations and make the best use of it in a timely manner to meet their clinical and financial goals.

 

Harmonize Data, Analyze & Compute

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One of Caradigm’s hallmarks as an enterprise population health company is that we are experts in healthcare data management infrastructure and processes. We help our customers remove the complexity and manual processes associated with data management through the Caradigm Intelligence Platform (CIP), an enterprise data warehouse designed specifically for healthcare. CIP enables organizations to harmonize their data, and then perform a rich array of analysis (e.g. predictive risk stratification, utilization), as well as computations on data (e.g. quality compliance, gaps in care, display last glucose results, display last PCP visit for a patient, etc.).

 

Modeling Claims Data Using Entities

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Caradigm has a proprietary methodology that structures data as specific healthcare entities. On the outer ring in the diagram above are examples of core payer entities that we can introduce with our customers. Seeing payer data organized in this fashion is often eye opening because it provides a harmonious view of the care delivered to patients. What is even more exciting is when payer data is combined with clinical and other data to show a complete picture that can then feed other integrated applications.

 

Lighting Up Applications With Payer Data

  • Risk Management Analytics
  • Accountable Care Organization compliance
  • Gaps in Care
  • Gaps in Billing
  • Network Utilization Analytics
  • LOS Analytics
  • Post-Acute Care Analytics
  • PMPM Analytics
  • In-Patient Analytics
  • ED Visit Analytics
  • Ambulatory Visit Analytics
  • Drug Utilization Analytics
  • Conditions Analytics
  • Bundled Payments Analytics
  • EMR Only Analytics
  • Claims Only Analytics
  • Harmonized Data Analytics

The beauty of a complete and reusable data asset is that it can light up all kinds of analytics applications. You can forecast clinical and financial risk, identify gaps in care, and analyze utilization or network steerage in order to uncover opportunities for financial improvement.

The amount of data available in our industry is growing exponentially. It is time for healthcare organizations to augment their ability to harness all of that data and realize more value. If you would like to discuss how your organization can harmonize its data and better leverage claims data as part of population health efforts, then please send us a note here.