Humana, the third largest health insurance provider in the U.S. published a synthetic data exchange platform. The aim is to unleash new insights and bring advanced products to the market. The data exchange offers access to synthetic patient data with a total of 1 500 000 synthetic records that is representative of Humana’s member population.
How can insurance companies use synthetic data?
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The data challenge in health insurance
Data sharing in a highly regulated and sensitive environment is a hard, slow and often painful process. Legal and regulatory pressures make it impossible to collaborate with external vendors efficiently. What’s more, health insurance providers want to be good shepherds of the sensitive data their patients trust them with. Synthetic data allows Humana to run faster tests and learns and to deliver better value to its members. All of this, while keeping their personal healthcare information perfectly safe.
Our favorite synthetic data innovation hub
To overcome challenges, Humana set up a synthetic data sandbox. Using these granular, high-quality synthetic datasets, the relationships between different variables of interest as well as the important context in which patient care takes place are preserved. Developers and data scientists can identify where the care journey has taken a synthetic individual, how they interacted with different sites of care and maintain the specificity of the data without being identifiable. A synthetic data dashboard gives instant access to the data. Sample datasets can be downloaded for schema and data quality exploration. Plus a comprehensive data dictionary serves as documentation. The synthetic datasets provide data on demographics and coverage details, medical and pharmacy claims, dates, diagnosis, sites of care with maintained correlations and relationships throughout. This is exactly how a synthetic data sandbox should be.
The advantages of a synthetic data sandbox
By offering easy and safe access to high quality synthetic data, Humana gives developers the most important ingredient for successful product development. This granular, as-good-as-real source of knowledge is invaluable in identifying cohorts and improving customer experience. Proof of value is also much easier to come by. A solution’s benefits and accuracy, especially of machine learning applications, will only show themselves if the data is hyper-realistic. New tools developed with realistic synthetic data assets allow the insurance provider to assess where and how to use them along the care journey.
Check out Humana’s Data Exchange and see what synthetic data best practice looks like in real life!