Data Science as a Service


A secure, hosted environment for payers and providers to build healthcare data science analytics using deidentified data from claims and other datasets with real-time regulatory compliance monitoring.

Gain Timely Insights 

Leverage comprehensive and timely national healthcare data spanning tens of billions of deidentified healthcare events, including diagnosis, medical procedures, prescriptions, and social determinants of health.

Develop unique analytic solutions for use with value-based reimbursement initiatives, new drug launches, and targeted advertising; determine patient adherence and compliance rates for diverse populations. 

Integrate diverse new data, such as social determinants of health, to determine how ethnicity, health literacy, household composition, and other factors impact your RWE/HEOR measures.

Improve analytic depth, timeliness, and predictive power, especially when new or diverse data is required or when compliance review is manual.

Discover unprecedented insights with granular views across geography, care settings, therapeutic areas, and reimbursement models.

Help ensure regulatory compliance with persistent, automatic monitoring of all activity, including deidentified data requirements and the enforcement of usages which inspire a better healthcare system.


Deploy Compliant Healthcare Data Science at Scale

Unique, Custom Environment

  • Secure, hosted environment lets you combine multiple pre-selected datasets for advanced data analytics and model development with a near-real time compliance determination feature.
  • Compliant healthcare analytics can be deployed with any other system, including Change Healthcare networks. Data Science as a Service supports customized uses, data, and software integration.
  • Data Science as a Service offers a dedicated instance for each client, with a wide variety of statistical, visualization, and querying tools for data analysis. 

High-Priority Use Cases for Payers and Providers 

  • Explore the intersection of health economics and social determinants of health data, leveraging your own health economics and outcomes research (HEOR) and real-world evidence (RWE) to create more effective value-based reimbursement programs. 
  • Assess patient adherence/compliance, predict lapse rates, and model and test different countermeasures for diverse populations. Compare and contrast your performance against national healthcare system data. 
  • Determine marketing efficacy by connecting ad logs and promotion history to real-world changes in patient or provider behavior. Develop new audience definitions and activate campaigns through digital and linear advertising networks.
  • Support efficient launches for new drugs by assessing claims processing and patient modalities access to identify potential rejections and eliminate obstacles to authorizations and payments.

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