20 Jul Top Five AI Use Cases for Health Payers

For health payers, determining the most effective AI use cases for driving innovation investments has become a rapid and critical priority in 2023.

To help health payers CIOs gain a fuller picture on the possibilities and priorities in AI, Gartner recently published its “Infographic: Artificial Intelligence Use Case Prism for the U.S. Healthcare Payer Industry.” Click here to access the report. (Gartner subscription required).

Following are the top five AI use cases for health payers from the report:

#5 – Payment Integrity/Repayment: An analysis of a claim, prior to payment, to evaluate the likelihood that the claim is fraudulent. The output is a risk score that can be used to trigger an automated “pend” of a claim prior to payment.

#4 – Automated Data Management: An automated analysis of data feeds from internal and external sources to ensure consistency and fidelity of payer enterprise data.

#3 – Service Chat/Web or App: A natural language interpretation and generation via a digital chat experience (web, app-based) to accomplish typical payer customer service needs (e.g., questions about a bill, requesting an ID Card, finding a doctor).

#2 – Authorization/Case Abstraction: A medical concept abstraction algorithm that reviews several sources that together represent everything available to the payer about the merits of an authorization request for a certain medical service. These sources may include structured fields in the submission workflow, as well as unstructured data in the form of PDF medical charts, lab reports, or correspondence.

#1 – Chronic Condition Decision Support: An analysis of member data, plus IoT and event streams, focused on supporting daily decision-making in living with a chronic disease.

For any health payers, AI success is contingent upon the overall quality of all clinical data – especially for the Automated Data Management and the Chronic Condition Decision Support use cases.

In this new frontier, we continually point out that any new AI solution could potentially provide insights that are incorrect, and potentially be harmful to patients. This is why we are performing comprehensive benchmarking studies to assess the validity of using AI generated data compared to the data provided by the Perfect Search technology behind our solution.

We will be sharing this information in the near future, and hope that it will further guide health payers on their journeys into AI safely and effectively.

In the meantime, got questions about AI for health payers? Our team of experienced health informatics experts is ready to assist. Contact us today.