Other parts of this series:
When we think about the vast amounts of patient health data, it tends to be in the abstract—a complex matrix of information that is difficult for a human to decipher in a short timeframe. It is simply too much information to consider. But with AI, there is an opportunity to combine several different sets of health data, from several different sources, then analyze them for trends or patterns that can drive improved return-to-health outcomes and help prevent claims.
One example of a point at which AI captures unstructured data is during the intake process. During intake, information is provided that creates a profile of the individual and the current claim or injury—but it also comes with important meta-data such as employment information, provider information, keywords, and more.
With the right design, AI can access additional health data from sources such as diagnostic information, previous claims data, medical charts and so on. The AI is then able to combine these separate sources of information to create a structured claimant profile. Structuring this data, AI classifies it and places it alongside other claimant intake data at a large scale to create a broad view of trends and outcomes. As more and more information comes in from different individuals, more accurate trends in the profiles emerge, which allows for insurance providers to predict certain outcomes with increased accuracy.
Having the ability to structure unstructured data allows insurance providers to create actionable approaches to both prevent and facilitate claims. It benefits the claimant by helping predict potential injuries that may require long recovery and downtime from a job. It also helps identify positive treatment outcomes in other similar profiles that can then be applied to the individual, meaning a more direct pathway to recovery.
In my next post, I will take a look at the application of AI-structured data and how it is leading employers, insurance providers and the insured toward wellness practices that were previously not part of a complete health package.
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