Combining the Power of Artificial Intelligence with the Richness of Healthcare Claims Data: Opportunities and Challenges
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) ha...
| Main Authors: | , , , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
Springer International Publishing
2019
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| Online Access: | http://hdl.handle.net/1721.1/120990 |
| _version_ | 1826206339265724416 |
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| author | Sraer, David Pinheiro, Lisa Dadson, Nick Veliche, Razvan Greenberg, Paul Thesmar, David Jean Joseph |
| author2 | Sloan School of Management |
| author_facet | Sloan School of Management Sraer, David Pinheiro, Lisa Dadson, Nick Veliche, Razvan Greenberg, Paul Thesmar, David Jean Joseph |
| author_sort | Sraer, David |
| collection | MIT |
| description | 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. |
| first_indexed | 2024-09-23T13:27:37Z |
| format | Article |
| id | mit-1721.1/120990 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T13:27:37Z |
| publishDate | 2019 |
| publisher | Springer International Publishing |
| record_format | dspace |
| spelling | mit-1721.1/1209902022-09-28T14:26:28Z Combining the Power of Artificial Intelligence with the Richness of Healthcare Claims Data: Opportunities and Challenges Sraer, David Pinheiro, Lisa Dadson, Nick Veliche, Razvan Greenberg, Paul Thesmar, David Jean Joseph Sloan School of Management Thesmar, David Jean Joseph 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. 2019-03-15T18:07:53Z 2019-03-15T18:07:53Z 2019-03 2019-03-09T04:46:35Z Article http://purl.org/eprint/type/JournalArticle 1170-7690 1179-2027 http://hdl.handle.net/1721.1/120990 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 en https://doi.org/10.1007/s40273-019-00777-6 PharmacoEconomics Creative Commons Attribution https://creativecommons.org/licenses/by/4.0/ The Author(s) application/pdf Springer International Publishing Springer International Publishing |
| spellingShingle | Sraer, David Pinheiro, Lisa Dadson, Nick Veliche, Razvan Greenberg, Paul Thesmar, David Jean Joseph Combining the Power of Artificial Intelligence with the Richness of Healthcare Claims Data: Opportunities and Challenges |
| title | Combining the Power of Artificial Intelligence with the Richness of Healthcare Claims Data: Opportunities and Challenges |
| title_full | Combining the Power of Artificial Intelligence with the Richness of Healthcare Claims Data: Opportunities and Challenges |
| title_fullStr | Combining the Power of Artificial Intelligence with the Richness of Healthcare Claims Data: Opportunities and Challenges |
| title_full_unstemmed | Combining the Power of Artificial Intelligence with the Richness of Healthcare Claims Data: Opportunities and Challenges |
| title_short | Combining the Power of Artificial Intelligence with the Richness of Healthcare Claims Data: Opportunities and Challenges |
| title_sort | combining the power of artificial intelligence with the richness of healthcare claims data opportunities and challenges |
| url | http://hdl.handle.net/1721.1/120990 |
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