The ensuing article is penned by Puneet Arora as a guest contributor. Healthcare AI systems are obtaining a greater amount of clinical and operational data. That’s helpful, but merely possessing more data does not guarantee that a system comprehends current truths.
The issue becomes evident in retail pharmacies. Envision a prescription claim being denied due to the necessity of prior authorization. The pharmacy submits the required approval.
Soon, a pharmacist communicates with the payer and verifies that the matter is currently under examination. The inventory is sufficient and no additional information is needed from the patient. All events in the sequence are accurate.
An AI assistant might recommend an incorrect course of action even if it fails to correctly interpret initial rejections in light of subsequent evidence. This could lead to suggesting actions such as resubmitting claims, contacting patients, or creating new tasks when the most suitable action may be to simply monitor payer decisions.
The issue is not due to a lack of data.
