Combining the Power of Artificial Intelligence with the Richness of Healthcare Claims Data: Opportunities and Challenges
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Author(s)
Sraer, David
Pinheiro, Lisa
Dadson, Nick
Veliche, Razvan
Greenberg, Paul
Thesmar, David Jean Joseph
Date Issued
March 2019
Journal
PharmacoEconomics
Publisher
Springer International Publishing
Citation
Thesmar, David, David Sraer, Lisa Pinheiro, Nick Dadson, Razvan Veliche, and Paul Greenberg. “Combining the Power of Artificial Intelligence with the Richness of Healthcare Claims Data: Opportunities and Challenges.” PharmacoEconomics (March 8, 2019). © 2019 The Authors
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Final published version
Abstract
Combinations of healthcare claims data with additional datasets provide large and rich sources of information. The dimensionality and complexity of these combined datasets can be challenging to handle with standard statistical analyses. However, recent developments in artificial intelligence (AI) have led to algorithms and systems that are able to learn and extract complex patterns from such data. AI has already been applied successfully to such combined datasets, with applications such as improving the insurance claim processing pipeline and reducing estimation biases in retrospective studies. Nevertheless, there is still the potential to do much more. The identification of complex patterns within high dimensional datasets may find new predictors for early onset of diseases or lead to a more proactive offering of personalized preventive services. While there are potential risks and challenges associated with the use of AI, these are not insurmountable. As with the introduction of any innovation, it will be necessary to be thoughtful and responsible as we increasingly apply AI methods in healthcare.
MIT Department
Sloan School of Management
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DOI of Published Version
https://doi.org/10.1007/s40273-019-00777-6
