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DocStation AI Payer Prediction Model
DocStation AI Payer Prediction Model

How to choose which payer to send a medical claim to, and how to let DocStation choose for you.

Aubree Dorr avatar
Written by Aubree Dorr
Updated over 2 months ago

DocStation AI™️ uses prescription coverage details, human-in-the-loop data, and over 40 years of expertise in the healthcare marketplace to accurately predict your patients' medical coverage. Formerly a neural network machine learning model, the new large language model (LLM) assesses regional impact, subscriber ID trends, and frontline experience to help DocStation users save 20 hours per month or more on medical claim workup and submission - all with higher than 90% accuracy.

It's called the Payer Prediction model, and it enables DocStation's Automated Billing for medical claims to run seamlessly in the background of day-to-day pharmacy workflow while generating revenue for the vital services pharmacists provide.

Here's how it works.

When a DocStation Pharmacy has Auto-Billing configured, medical claims are automatically generated based on targeted medication dispenses. DocStation AI considers the pharmacy coverage to which the medication was billed and predicts up to three medical payers under which the patient is likely to have active coverage.

Then, DocStation AI™️ performs an automated eligibility check to verify active coverage with the most likely prediction first, then on to the second and third predictions as needed. When a successful coverage is determined, the claim is automatically queued to submit to that payer.

Here's what it looks like.

When the automated eligibility check determines active coverage, the payer will be set on the claim and show as Verified in the payer list.

When the automated eligibility check is unable to determine active coverage, the predicted payers will show as Recommended in the payer list.

When DocStation AI™️ is unable to verify active medical coverage, it can be due to a number of reasons that may not necessarily mean the patient doesn't have coverage with that payer. Other reasons include a missing alpha prefix on the subscriber ID, a mismatched relationship to the policy holder, or even that the medical benefit subscriber ID is different from the pharmacy benefit ID, among other things. Many of these scenarios will be addressed in the future development of Payer Predictions by DocStation AI™️, so stay tuned for more exciting news!

If you have any questions about the LLM or data used for training, please feel free to reach out to DocStation Support in the Chat.

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