How 5 minutes of prior auth becomes 20
A common scenario: a midsize orthopedic practice orders an MRI for a patient with a suspected rotator cuff tear. The authorization specialist pulls the patient and coverage details, order, codes, and supporting clinical records from the EHR.
After entering the case and uploading the records, the specialist may be redirected to another portal or a phone line. The same information must be entered again until the request reaches the right channel. What should be a 5-minute submission has become 20 minutes of manual work.
This is where much of the avoidable work in prior auth hides. It is not in the clinical decision, but in carrying the same case through systems that do not carry it forward for the team.
The burden adds up. In the survey cited above, practices spent an average of 15 hours a week on prior authorization, and 71% employed at least 1 staff member exclusively for it. The hardest cases are often not the most clinically complex. They are the ones that require the same work in multiple systems.
We used to manually re-enter the same prior-auth information across multiple forms. Until Clicks Health.
Blue Cross and Blue Shield of Illinois offers a useful example. Its current provider guidance tells practices to check eligibility and benefits first because the correct authorization pathway can depend on the member and service. Some requests are handled by BCBSIL through BlueApprovR or Availity, while others go through Carelon or eviCore. See BCBSIL's current guidance for requesting prior authorization.
The routing can change. The prior-auth specialist should not have to track every pathway or re-enter the case each time it moves between systems.
From 20 minutes of staff time to zero
Payer requirements, portals, and routing paths change often, so a fixed routing map quickly becomes brittle. This is why AI can deliver what previous automation attempts did not: it can interpret what a payer requires, adapt as requirements change, and carry the case forward through the next system.
The key is that automation should fit into the way your team already works. The AI operates in the EHRs, payer portals, PDFs, and desktop applications your team already uses, so you can improve the workflow without an IT migration or a major change-management effort.
Here is what that looks like in practice:
Patient data, orders, and codesare joined with supporting records.
Portal entry and payer callsare handled in the same workflow.
Status and confirmation detailsare returned automatically.
The completed submission, status, and confirmation number are logged in the EHR automatically, giving the team a clear record without another round of manual entry.
Where to start
The best place to start is a workflow your team wants off its plate. Look for three signals:
- The team consistently describes the workflow as repetitive, frustrating, or something they try to avoid.
- The workflow happens often enough that the time savings compound.
- For most cases, the AI can use information already available in the EHR and supporting records, without asking the patient or clinician for anything else.
Not sure where to start?
Score 1 workflow against 5 signals to see whether it is a strong candidate for automation.
How to get started
You pick a workflow to automate
Show us the repetitive work.We learn it from real cases.
Clicks builds a custom agent
We map the process and define success.Then we build and train the agent.
Your team gets to focus on patients
The agent handles the repetitive work.Completed work returns to your team.
Take repetitive prior-auth work off your team's plate
Show us the workflow. We standardize it, build the agent, and guarantee the outcome.
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