From Arms Race to Patient Benefit: AI and Interoperability in Prior Authorization

Prior authorization sits at an awkward intersection of clinical intent, coverage policy, and administrative reality. It is often treated as a battleground where providers try to “get to yes” and payers try to “hold the line,” with each side investing in automation and AI to gain leverage. That framing is understandable, but it is not inevitable. The same technologies being used competitively can be applied collaboratively, especially as interoperability rules push the industry toward more standardized data exchange.

The current state is costly for everyone

Clinicians feel the burden most directly. In the AMA’s 2024 prior authorization physician survey, physicians and staff reported spending 13 hours per week on prior authorizations, and 93% said the process delays access to necessary care. The same survey reports that 82% said prior authorization can at least sometimes lead to treatment abandonment, and more than 1 in 4 physicians (29%) reported a serious adverse event tied to prior authorization delays, including hospitalization, permanent impairment, or death. 

Those delays also drive avoidable utilization. The AMA survey reports that physicians observed prior authorization leading to immediate care or emergency room visits (47%) and hospitalizations (33%). That pattern is not surprising: when patients cannot access the intended therapy on time, the system often pays later through deterioration and crisis-driven care.

Payers, meanwhile, face a different kind of waste that directly pressures administrative expense and, in turn, the medical loss ratio: churn in decisioning and the labor intensity of human clinical review. In Medicare Advantage, nearly 50 million prior authorization determinations were made in 2023, with 6.4% denied. Only 11.7% of denials were appealed, but among those appeals, 81.7% were partially or fully overturned. Whatever the reason for reversal, whether documentation gaps, misrouted requests, or policy nuance, that overturn rate signals avoidable rework. Each additional round of nurse and physician review adds administrative cost without improving care, stretches turnaround times, and increases abrasion for members and providers.

Interoperability rules create a practical path forward

The CMS Interoperability and Prior Authorization Final Rule (CMS-0057-F) is an important forcing function. CMS describes the rule’s purpose as increasing data sharing and reducing payer, provider, and patient burden through improvements to prior authorization and data exchange, with key provisions required beginning January 1, 2026. The CMS fact sheet sets concrete expectations, including decision timeframes of 72 hours for expedited requests and seven calendar days for standard requests, and requirements to provide specific reasons for denials and publicly report prior authorization metrics. 

This is not just compliance work. Standardized APIs and clearer timelines reduce the ambiguity that drives today’s friction, and they create the technical conduits area where AI can help both sides rather than simply accelerate conflict.

What “non-zero-sum” prior authorization looks like

A cooperative model does not require payers and providers to agree on every policy. It requires them to collaborate on the mechanics of how information moves and how decisions are made.

1) Bring in EHR-native clinical context.

Many delays come from missing or mismatched clinical context, not clinical disagreement. With modern integration, this can be handled automatically inside the EHR workflow. AI can pre-populate the prior authorization request using structured data already in the chart, attach the most relevant supporting documentation, and map each element directly to payer policy criteria before the order is signed. The CMS-0057-F rule makes this easier to scale because it pushes the industry toward standardized electronic prior authorization APIs, which reduces one-off payer portals and custom integrations. In practice, that means the request can move from the EHR to the payer and back with status updates and decisions returned into the EHR, with less manual work and fewer “missing info” cycles.

2) Automate the transaction, not the back-and-forth.

CAQH data shows how expensive manual pathways remain. In 2023, the average provider cost for a manual prior authorization transaction was $10.97 versus $5.79 for electronic, and the average plan cost dropped from $3.52 manual to $0.05 electronic. CAQH also reports providers spend substantial time even when the process is electronic or portal-based, averaging 11 minutes electronically and 16 minutes via portal. These are exactly the minutes that can be returned to patient care when automation is integrated into workflows instead of layered on top.

3) Use AI for consistency, anomaly detection, and in-workflow clarification – with guardrails.

AI should be used to reduce variance, route requests intelligently, and detect when a request deviates from expected patterns on either side. On the provider side, it can flag missing or inconsistent clinical details relative to the payer’s policy guidelines and prompt for the specific context needed while the clinician is already ordering or documenting, rather than triggering follow-up calls or faxes later. On the payer side, it can identify when a request is likely approvable but lacks key elements, or when the request truly falls outside typical criteria and should be routed for clinical review. The goal is not to replace judgment but to keep routine cases automated, pull humans into the loop only when necessary, and keep clarification inside the clinical workflow instead of out of band. CMS’s emphasis on specific denial reasons and public metrics reinforces transparency and makes these decision pathways easier to audit and improve over time.

4) Measure outcomes that matter to both sides.

Cycle time, auto-approval rate, overturn rate, and “touch time” per request are shared operational metrics, but they are best treated as leading indicators, not the goal. The goal is what those metrics improve: faster access to appropriate care, fewer abandoned treatments, fewer avoidable ED visits, and a more effective patient experience. The AMA survey’s reported downstream utilization associated with prior authorization delays reinforces that operational performance and patient outcomes are tightly linked. 

A pragmatic path forward 

Prior authorization will not disappear, and not every request can or should be auto-approved. But today’s process contains obvious, measurable waste for providers, payers, and patients. The combination of interoperability requirements and modern AI creates an opportunity to reduce that waste without shifting it to someone else.

The most pragmatic starting point is narrow: pick high-volume services, align on structured data requirements, implement standards-based exchange, and let automation handle the predictable majority. If it works, expand. In a system where delays can translate into harm and avoidable utilization, collaboration is not idealism. It is operational discipline that pays off for all parties, and most importantly, for the patient.