CARE: AI That Speeds Review Without Sacrificing the Human Touch

Prior authorization teams are under constant pressure to move faster without compromising clinical quality. Rising case volumes, increasing clinical complexity, and ongoing regulatory scrutiny have left health plans and PBMs searching for a way to support their reviewers more effectively. While the industry has explored automation for years, many organizations remain cautious—and rightly so. In utilization management, clinical judgment carries significant weight, and no AI system should replace the expertise of trained clinicians. Instead, technology should remove the friction around the review process, letting the humans responsible for care decisions stay fully in control.

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That balance is exactly what Banjo CARE (Computer-Assisted Review Engine) was designed to achieve. CARE uses AI to surface the right clinical evidence for reviewers the moment they need it, eliminating the hours typically spent hunting through faxes, portals, PDFs, and EHR extracts. The result is a review experience that feels less like a scavenger hunt and more like a streamlined, guided process—one where the reviewer is always in the driver’s seat.

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The real impact becomes clear when you look at the return on investment. In most organizations, a surprising amount of time is lost not in making the clinical decision itself but in the manual effort required to assemble the information necessary for that decision. Reviewers jump between systems, sift through long documents, and manually verify data points that are often inconsistently formatted or poorly extracted. This is where rework multiplies. Missing data leads to callbacks. Misfiled attachments cause delays. Incomplete documentation triggers manual QA loops. Every minute spent correcting these avoidable issues is a minute not spent on meaningful clinical assessment.

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CARE changes the equation by dramatically reducing the time reviewers spend searching for, interpreting, and validating information. Instead of paging through a 20-page fax packet for the patient’s diagnosis code, the required lab results, or prior trial-and-failure history, reviewers see those details highlighted and referenced for them automatically. AI does the heavy lifting of extraction and organization, but the reviewer is the one confirming accuracy and determining relevance. This approach not only speeds up individual reviews but also reduces training time, since new staff no longer need to memorize where to find information across a maze of systems.

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How CARE can Impact Your Bottom Line

For organizations looking to measure ROI, this reduction in rework is one of the clearest outcomes. When evidence is surfaced correctly the first time, reviewers avoid the back-and-forth that typically slows decisions. Fewer manual edits means fewer opportunities for error. And when reviewers can make decisions with confidence and clarity, overall turnaround time improves across the board. The operational gains compound quickly: lower labor costs per review, less reliance on overtime, and the ability to reallocate staff to higher-value tasks such as complex cases, provider education, or appeals.

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But perhaps the most important benefit is that the integrity of human clinical judgment remains fully intact. CARE never makes a determination, suggests an outcome, or automates a decision. Instead, it ensures that reviewers have everything they need to make the right call based on their expertise and the applicable criteria. This transparency supports audit readiness as well. Because CARE only surfaces evidence rather than substituting for clinical reasoning, organizations maintain a clear, defensible trail of reviewer actions and rationale. Human governance stays at the center of every decision.

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The future of utilization management isn’t about replacing clinicians with algorithms—it’s about giving clinicians tools that make their work more efficient, accurate, and consistent. When AI operates as an assistant rather than an authority, health plans and PBMs are able to modernize without compromising trust. CARE represents the best version of this partnership: technology that accelerates the process while protecting the standard of care.

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The Big Picture

With AI taking on the administrative burden and clinicians guiding every decision, organizations can offer faster, more equitable service to members and providers. And for the reviewers themselves, work becomes less about data chasing and more about applying their expertise where it matters most.

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CARE is changing the pace—and experience—of clinical review. Not by removing the human touch, but by empowering it.

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