Using RPA vs. AI in Claims Processing

Your quality team listens to maybe five calls per agent each month. It scores each one in isolation, hands back a number, and calls that coaching. For a VP of Operations, that’s the quiet problem with call center QA sampling. The sample is too small to be fair, and it isn’t even predictive. SQM Group found that 81% of traditional QA scores didn’t correlate with customers’ own satisfaction ratings.¹ So you’re coaching agents on noise.

And the sample has a second hole. It’s almost all in English. The calls your members place in Spanish, Mandarin, or Vietnamese rarely reach a reviewer, because the people scoring calls read and speak English.

So the problem compounds. The sample is tiny, it’s graded call-by-call, and it’s almost all English. The fix isn’t a better sample. It’s no sample: score 100% of calls, in every language, and read agents on their whole body of work.

What a 1% Sample Actually Measures

Start with the math. SQM finds that most call centers evaluate five or more calls per agent a month.² Against the several hundred calls an agent handles in that time, that’s about 1% of their work, often less. So for most agents, 99% of what they do is never scored.

That alone would be a problem. The bigger one is which calls get picked, and what the score means.

Reviewers tend to grab calls that are easy to score. Short ones. Clean ones. The calls where nothing went wrong. The messy, high-stakes calls, the ones you’d most want to learn from, are the ones that get skipped.

Then each call is graded on its own. Did the agent use the greeting? Hit the compliance script? Close properly? These are real things. But they describe how one call was handled, not whether the agent is serving members well.

That’s why the scores drift from reality. SQM found that only 17% of agents believe their QA program improves customer satisfaction.¹ The people being measured can already see the gap.

And coaching inherits the gap. A supervisor pulls up two or three scored calls and builds a development plan on them. If those calls aren’t representative, the plan is guesswork dressed up as data.

The Calls Your QA Never Hears

Now add language. More than 25 million people in the United States are limited English proficient.³ Across Medicare Advantage, Medicaid, and the Marketplace, they’re a large share of who you serve.

Those members call. Their calls get handled. Then they vanish from quality review.

The reason is structural, not deliberate. Most QA reviewers work in English. Scoring a call in Vietnamese or Mandarin means finding a reviewer who speaks it, which most plans can’t do at scale. So the sample quietly narrows to English, and a whole population of interactions goes unscored.

Here’s what makes that dangerous. CMS already grades these calls, even if you don’t.

Each year, from roughly February through June, CMS places test calls to Part C and Part D call centers. It checks whether an interpreter can be reached, whether TTY works, and whether the agent answers plan questions accurately. It does this in English plus six more languages, including Spanish, Mandarin, Vietnamese, and Tagalog.⁴ Those results feed CMS’s compliance monitoring.

So CMS secret-shops your agents in languages your own QA never reviews. If you want the fuller case for why sampling leaves most of a call center invisible, we made it in Are Health Plans Really Listening to All Their Members? The point for agent performance is narrower. You can’t coach what you never hear, and you’re accountable for it anyway.

The Agents Your Sample Misses

The agents who carry the most non-English calls are, by design, the least sampled. Their calls get skipped, so their scores rest on whatever English calls happened to get pulled. Your hardest-working bilingual agents end up judged on the least representative slice of their work.

QA sampling also misattributes. When a member calls back about the same issue, a handful of scored calls can’t tell you whether the agent mishandled it or a broken process behind the agent did. SQM’s data on calls that aren’t resolved on the first try traces 49% of the errors to the organization and 38% to the agent.⁵ Coach the agent for an organization problem, and you’ve fixed nothing.

And a monthly sample rarely catches a pattern. If an agent mishandles one specific scenario, and it comes up on a small share of calls, the odds it lands in that 1% are low. The behavior you’d most want to coach is the behavior least likely to be seen.

So the agents carrying your hardest, highest-risk calls are the ones your sample is least likely to cover. That’s not a coaching program. It’s a lottery.

The difference between the two approaches comes down to how much of an agent’s work you actually look at.

How to Score Agents on Every Call

Moving off sampling isn’t about scoring harder. It’s about scoring everything. Four shifts get you there.

First, capture every call. Record 100% of interactions, in every language, and keep the transcript. SQM itself recommends recording all calls, not a slice.¹ You can’t analyze what you didn’t keep.

Second, score consistently against defined dimensions. Apply the same rubric to every call, so an agent’s score reflects the rubric, not which reviewer they drew or which calls came up. Define what you’re measuring: member sentiment and risk, communication and empathy, compliance.

Third, include every language by default. Translation has to be built in, not a special request. If non-English calls need a separate workflow, they’ll keep getting skipped. A Tagalog call should get scored the same day, the same way, as an English one.

Fourth, coach on patterns, not anecdotes. Once every call is scored, you stop asking “how was this one call” and start asking “what does this agent do across a hundred calls.” Repeated phrasing that confuses members. A compliance step that slips under pressure. That’s coaching you can act on, and it’s the kind that moves CAHPS scores a thin sample never could.

What to Look for in a Solution

When you evaluate call center QA tools, look for five things.

1. Every call scored, not a monthly sample. Coverage of 100% of interactions, so no agent is judged on a lucky few.

2. Every language, not just English. Translation and scoring built in for all languages, so non-English calls are reviewed on the same footing as English ones.

3. Patterns across calls, not calls in isolation. The ability to group an agent’s calls and surface recurring behavior, not just grade one interaction at a time.

4. Objective scoring, not reviewer roulette. A consistent rubric applied the same way to every call and every agent.

5. Plan-owned data, not vendor custody. The scores, transcripts, and intelligence sit with the plan, not locked inside an outsourcer’s reporting.

That last one matters most. When your QA is run by the same vendor that staffs your calls, the vendor is grading its own work. Independent, plan-owned scoring is the only version you can trust.

Mizzeto’s Call Center Intelligence Tool was built for this. It scores 100% of calls across every language and evaluates agents on its Agent Empathy & Communication dimension, so coaching rests on an agent’s whole body of work, not a sample. The data stays yours.

What Changes When You Score Everything

Coaching stops being guesswork. Supervisors work from an agent’s full record, not a handful of cherry-picked calls. Your strongest non-English agents finally get credit, and your struggling ones get help you can actually target. And the CMS test calls that used to be a once-a-year gamble become something you can see coming, because you’re already scoring the same calls CMS does.

That’s the real cost of call center QA sampling. Not just unfair scores, but a coaching program built on a sliver of the truth. Scoring every call fixes the input. If you want to see it on your own calls, send us a sample. We’ll return scored transcripts before you commit to anything.

‍

‍

References

1. SQM Group. “Call Center Quality Monitoring: Best Practices.” sqmgroup.com. https://www.sqmgroup.com/resources/library/blog/call-center-quality-monitoring-best-practices

2. SQM Group. “Call Center Quality Assurance Tips.” sqmgroup.com. https://www.sqmgroup.com/resources/library/blog/call-center-quality-assurance-tips

3. U.S. Census Bureau. American Community Survey, 2019-2023 5-Year Estimates, Table S1601, Language Spoken at Home. data.census.gov.

4. Centers for Medicare & Medicaid Services. “2022 Part C and Part D Call Center Monitoring: Timeliness and Accuracy & Accessibility Studies.” December 16, 2021. https://www.cms.gov/files/document/2022partcandpartdcallcentermonitoring.pdf

5. SQM Group. “Call Center FCR Benchmark 2024 Results by Industry.” sqmgroup.com. https://www.sqmgroup.com/resources/library/blog/call-center-fcr-benchmark-2024-results-by-industry

‍

‍

A claims configuration error rarely shows up first in a report. It shows up on the phone. A benefit rule loads wrong, a fee schedule maps to the wrong code, or an authorization requirement fires when it shouldn't, and within days providers start calling. Each call is answered. Each call is logged. Each call is closed. The operation looks healthy because, ticket by ticket, it is. Every provider who called reached a person, got a reference number, and received a resolution.

What the operation cannot see is that many of those calls were the same call. They carried the same complaint, traced back to the same misconfigured rule, and were closed as separate incidents. Quality review doesn't catch this. It covers only a sample of calls, and it scores each one for how it was handled, not for what it has in common with the others. So the pattern never reaches anyone who could act on it. The root cause stays in the core system the whole time, quietly producing more denials, more rework, and more calls.

This is how claims configuration errors persist. It isn't that the claims team missed the rule. It's that the operating model around provider calls is built to handle calls one at a time, reviews only some of them, and never reads across them. This article looks at why that gap costs more than most plans measure, and what it takes to close it.

The operating model that turns handled into hidden

Provider calls are the most honest diagnostic feed a health plan has. Providers don't call to chat. They call because a claim paid wrong, a denial made no sense, or an authorization that should have cleared didn't. Each call is a precise field report on where the plan's own configuration is failing, and the provider has already done the work of finding the problem.

The trouble is what happens to that report. In most operations, and especially where the provider line is outsourced, the unit of work is the ticket. An agent takes the call, resolves or routes the immediate issue, applies a disposition code, and closes it. Volume gets counted. Handle time gets measured. The vendor reports a clean queue. No one is asked the question that matters: do the last several dozen tickets describe one underlying failure?

Leaving that question unasked is expensive, because these calls are among the costliest interactions in healthcare administration. A claim status inquiry handled by phone takes about 25 minutes of provider staff time, the most of any administrative task the CAQH Index measures. In 2023, the medical industry spent roughly $11 billion on these inquiries, and about $2.4 billion of that could still be saved through automation.¹ So the calls carry real signal at real cost. Plans pay that cost at scale, then throw away the signal the moment each ticket closes.

A configuration error you can hear before you can see it

The sequence matters. When a configuration error goes live, the provider call is where it first becomes audible. The appeal, the rework queue, and the strain on provider relationships all come later, after the error has been firing for weeks.

Consider how it unfolds. A rule change misfires on a Monday. By Wednesday, billing staff at several practices notice the same unexpected denial on claims they expected to be paid. They call, and those calls are handled and closed. Only after a practice exhausts the phone route does it file a formal appeal, and appeals move on their own slow clock. By the time the pattern shows up as a spike in appeals, it has been sitting in the call logs for a month. This is part of what overturned denials reveal about the processes behind them.

Appeals data also shows how often these denials are mistakes rather than sound decisions. When prior authorization denials are appealed, they are overturned 67 percent of the time in Medicare Advantage, 47 percent in Medicaid managed care, and 43 percent in the ACA Marketplace.² Many of those denials should never have been issued, and many likely prompted a provider call well before anyone filed an appeal. The signal was there. The plan had no way of hearing it across calls.

The scale makes the blind spot more costly. Medicare Advantage insurers alone made nearly 53 million prior authorization determinations in 2024.³ And the cost of getting authorization logic wrong is rising. CMS's Interoperability and Prior Authorization Final Rule (CMS-0057-F) tightens decision timeframes and requires plans to publicly report their prior authorization metrics, so a misfiring rule now has less time to go unnoticed and a greater chance of showing up in public data.

What One Misconfigured Rule Actually Costs

Picture a mid-sized plan where a single edit to a fee schedule quietly underpays a common outpatient code. The claims team sees nothing unusual in the aggregate, because the code still adjudicates and pays, just at the wrong rate. Providers see it immediately. Over six weeks, the plan fields dozens of calls about the issue, each one handled and closed. Every one of those calls carried the answer.

The cost builds on three fronts at once.

Rework is the most visible. Every claim that paid on the bad rate has to be found, reprocessed, and often reissued. The longer the error runs, the more claims it touches before anyone traces them to a single cause. The calls add to the bill as well. A claim status inquiry handled by phone costs the industry about $18, compared with under $4 handled electronically, and a single misconfigured rule can generate dozens of them.¹

Appeals and payment disputes are the second front. They arrive weeks after the fact and use up review time on decisions that never should have needed it, in a category already under growing regulatory and public scrutiny.⁵

The third cost appears on no operations dashboard: provider trust. Every wrong payment and every repeat call wears it down. Provider abrasion is slow, cumulative, and hard to reverse, and it eventually shows up as network friction, tense contract negotiations, and providers steering patients elsewhere. Members feel it too, since a rule that pays or denies incorrectly can leave a member with the wrong balance or a surprise bill.

A plan can absorb a configuration error. What damages the relationship is taking six weeks to notice one that every provider on the phone already knew about.

The rule lives in the core claims system, but the earliest evidence that it is wrong lives in the call center. The difference between the two operating models comes down to whether anyone reads that evidence

What to Look for in a Solution

The fix isn't more agents or a faster queue. It's a shift from handling calls one at a time to reading across them. When you evaluate ways to get intelligence out of your provider calls, look for five capabilities:

• Full coverage, not a sample. Manual quality review depends on evaluators listening to calls one by one, so it only ever reaches a small fraction of total volume. The call that first flags a configuration error is unlikely to be in that fraction. Even if it is, a single call doesn't look like a pattern. Patterns only emerge when every call is in scope.

• Every language, not just English. Non-English provider calls are the least likely to be reviewed, which makes them the easiest place for an error to hide. Coverage should never depend on the language of the call.

• Root-cause grouping, not ticket disposition. A disposition code tells you a call was handled. It doesn't tell you that dozens of calls share one cause. The system should group calls by the failure behind them.

• Early warning, not after-the-fact reporting. Each pattern should be tied to the specific claims or authorization rule behind it, and it should surface while that rule can still be fixed, before the rework and appeals arrive.

• Plan ownership, not vendor custody. If your call data and analysis live inside a vendor's platform, you're renting insight into your own operation instead of owning it.

Where Mizzeto Fits

Mizzeto’s Call Center Intelligence Tool was built to close this gap. It audits 100 percent of provider calls, in every language your providers use. Its Provider Operational Issues scoring groups those calls by root cause rather than by ticket, so a shared configuration or authorization failure surfaces as one pattern instead of dozens of closed incidents, early enough to correct the rule before the appeals land. And because the plan owns the data and the analysis, that intelligence stays with the plan rather than in a vendor's queue.

The Cost of Listening One Call at a Time

Configuration errors aren't a crisis. They're a routine part of running a claims operation, and they'll keep happening. The real damage comes from the weeks a plan spends unaware of an error that every provider on the phone had already reported. For a claims leader, the question is whether your operating model turns each error into a single pattern you can act on, or into dozens of closed tickets no one ever connects.

References

1. CAQH. 2024 CAQH Index Report: From Transactions to Trust. Claim status inquiry data reflecting 2023 activity: average provider time of 25 minutes per phone inquiry, the highest of any measured transaction; approximately 11 billion dollars in medical claim status inquiry spend, with a 2.4 billion dollar annual savings opportunity; and per transaction industry cost of 18.18 dollars manual versus 3.68 dollars electronic. https://www.caqh.org/insights/caqh-index-report

2. KFF. Prior Authorization Metrics Provide New Insights Into Insurer Practices, but Gaps Remain. August 13, 2026. Analysis of 2025 prior authorization data posted by insurers. Share of denied standard requests overturned upon appeal by market. https://www.kff.org/patient-consumer-protections/prior-authorization-metrics-provide-new-insights-into-insurer-practices-but-gaps-remain/

3. KFF. Medicare Advantage Insurers Made Nearly 53 Million Prior Authorization Determinations in 2024. Volume of prior authorization determinations in Medicare Advantage. https://www.kff.org/medicare/medicare-advantage-insurers-made-nearly-53-million-prior-authorization-determinations-in-2024/

4. Centers for Medicare and Medicaid Services. Interoperability and Prior Authorization Final Rule (CMS-0057-F). Published in the Federal Register, February 2024. Requirements for prior authorization decision timeframes, transparency, and API based data exchange. https://www.govinfo.gov/content/pkg/FR-2024-02-08/pdf/2024-00895.pdf

5. KFF. Claims Denials and Appeals in ACA Marketplace Plans in 2024. Context on the scale of claims denials and appeals in the individual market. https://www.kff.org/patient-consumer-protections/claims-denials-and-appeals-in-aca-marketplace-plans-in-2024/

‍

A claims configuration error does not announce itself. When a benefit rule is loaded incorrectly during a new plan build, nothing breaks on screen. The rule sits quietly inside the adjudication engine and waits. The first place it becomes visible to a human is a phone ringing: a member asking why a covered service was denied, a provider calling to dispute a payment that came out wrong. By the time anyone traces that call back to the rule, the plan has already absorbed the cost many times over.

This is the part most plans miss. The call center is the earliest and most honest detection system a plan has for its own configuration errors. Every misloaded rule eventually produces a predictable pattern of calls, and that pattern is a precise map of what is broken upstream. But a plan that reviews only a small sample of its calls never sees the map. This piece follows a configuration error from the rule to the call it creates, and makes the case that your call center is where you will see the problem first, before it ever surfaces in the claims system, if you are equipped to listen.

The call center is where a configuration error becomes visible

Configuration quality is decided at auto adjudication, and it stays hidden there unless someone reads what happens after. Industry benchmarking commonly places well run auto adjudication around 80 percent, with first pass rates varying widely by plan complexity.¹ The 15 to 20 percent of claims that fall out to manual review are where cost concentrates,² and configuration is the lever that decides how large that bucket is. Practitioners estimate that system configuration alone can move auto adjudication rates by 15 to 25 percent.¹

The fallout does not stay in the claims system. A denied claim that should have paid, or a payment that came out wrong, does not stay in a queue. It travels to a phone. Every configuration error has a call attached to it, usually more than one, and the call center is where that error stops being an abstract data point and becomes a person asking why.

What one wrong rule sets in motion

Follow a single bad rule downstream and the cost compounds at every step, and almost every step runs through the call center.

It becomes a pend or a denial. A misloaded rule either denies a clean claim or kicks it out of auto adjudication into the manual queue, where pended claims pile into a backlog examiners clear by hand. In the ACA Marketplace, where CMS requires disclosure, insurers denied 19 percent of in network claims in 2024, with individual insurer rates ranging from 3 to 36 percent.³ In that same data, administrative reasons accounted for 25 percent of in network denial reasons and medical necessity for only 5 percent,⁴ meaning most denials turn on process and paperwork rather than clinical judgment, a category that includes the kind of error a misloaded rule creates on the payer side.

Then it rings both phone lines at once. A member calls, confused about why a covered service was rejected or billed wrong. A provider calls to dispute it. A manual claim status transaction costs the industry an estimated 15.96 dollars every time,⁵ and automating claim status alone would return provider time equivalent to as much as 18 minutes per patient visit now spent chasing answers by phone.⁶ Each of those calls costs the plan money and tells the plan something, if anyone is reading them.

Unresolved, it turns into an appeal and rework. A national hospital survey put the average denial rate near 15 percent and the average cost to rework a single denied claim at 57.23 dollars, with billions in denial related expense judged potentially unnecessary.⁷ Fewer than 1 percent of denials are appealed by members,⁸ which is exactly why the call matters more than the appeal. Most configuration errors never become a clean appeal a plan can track. They become calls, and if the calls are not read, the error stays invisible.

It becomes a provider you lose. Every incorrect denial and slow reprocess erodes the plan’s credibility with its network, and providers who fight the same avoidable errors grow reluctant to participate.

The pattern is audible, if anyone is listening

The call center works differently from every other place a configuration error shows up. A single call is an anecdote. The same call repeating, week after week, is a specification of the rule that is wrong. When the same service triggers the same denial and the same member confusion on a loop, that is not a run of bad luck. It is a configuration, and anyone reading the calls together can name it.

The problem is coverage. Call centers that rely on manual review, including those run by and for health plans, evaluate only about 2 to 5 percent of their calls,⁹ leaving over 95 percent unheard, and non-English calls are the least reviewed of all. At that sampling rate the pattern that would point straight at a misconfigured edit is statistically invisible. The plan hears a handful of unrelated complaints, not the signal underneath them. A configuration error that a full read of the calls would surface in a week can run for months, quietly generating denials, pends, and phone volume, because no one is listening at the scale required to hear it.

That gap is widening right now. Carriers are redrawing benefit designs and service areas for 2027 under tight margins, with Humana alone exiting plans that cover roughly 600,000 members in its second consecutive year of market exits.¹⁰ Every discontinued plan and trimmed benefit is a new configuration built under deadline, which means more chances for error, more members and providers with questions, and more call volume landing on a call center that is already reading only a sliver of it.

What to look for in a solution

When evaluating how to catch configuration errors before they compound, the question is whether you can hear what your claims are doing to your members and providers.

• Read every call, not a sample. A 2 to 5 percent QA sample is built to grade agents, not to find the configuration pattern driving the calls. Look for review of 100 percent, member and provider.

• Trace calls to root cause. Scoring a call is not the same as knowing why it happened. The goal is to link a spike in calls back to the rule, edit, or utilization management step that caused it.

• Every language, automatically. Non-English calls hide the same configuration errors as English ones, and they are the calls least likely to be reviewed.

• Payer owned call data. The calls, and the patterns in them, are your operational record. They should stay with the plan, not inside a vendor’s black box.

• A fast path from signal to fix. Detection only pays off if the plan can act on it. Owned, auditable configuration that can be corrected in days closes the loop the calls open.

Mizzeto built Claro to read exactly this signal. Claro audits 100 percent of a plan’s calls across every language and scores them against dimensions including Member Sentiment & At-Risk Identification and Provider and Operational Intelligence, so the member confusion and provider disputes a configuration error creates surface as a visible, traceable pattern rather than unread call volume. A plan that can see the pattern this clearly can trace it back to the rule, and fix it, days after it starts rather than months after it shows up in a compliance report.

You cannot fix what you cannot hear

A configuration error you cannot hear is a configuration error you cannot fix. It will keep denying claims, pending work, and ringing both phone lines, and the only record that it is happening lives in calls most plans throw away. The plans that treat the call center as an instrument rather than overhead find the rule behind the pattern while it is still cheap to correct. The 2027 redesign cycle is about to make that difference count. To hear what your claims configuration is doing to your members and providers, send us a sample of your calls and we will show you the pattern.

References

1. HealthCare Information Management. Understanding Auto Adjudication. 2025. Auto adjudication benchmark near 80 percent; configuration can shift rates by 15 to 25 percent.

2. HealthEdge. How Improving Auto-Adjudication Rates Can Enhance Health Plan Performance. 2025. Roughly 15 to 20 percent of claims still require manual processing.

3. KFF. Claims Denials and Appeals in ACA Marketplace Plans in 2024. 2026. Insurers denied 19 percent of in network claims in 2024; insurer rates ranged 3 to 36 percent.

4. KFF. Claims Denials and Appeals in ACA Marketplace Plans in 2024. 2026. Administrative reasons accounted for 25 percent of in network denial reasons; only 5 percent of denials were based on medical necessity.

5. CAQH. 2023 CAQH Index. 2024. A manual claim status transaction costs an estimated 15.96 dollars.

6. CAQH. 2024 CAQH Index Key Takeaways. 2024. Automating claim status inquiries returns time equivalent to as much as 18 minutes per patient visit.

7. Premier. Claims Adjudication Costs Providers 25.7 Billion. 2025. Average denial rate near 15 percent; average 57.23 dollars to rework a denied claim.

8. KFF. Claims Denials and Appeals in ACA Marketplace Plans in 2024. 2026. Fewer than 1 percent of denied claims are appealed by members.

9. SQM Group. Call center quality assurance benchmarks. Health plans typically review an estimated 2 to 5 percent of calls.

10. Healthcare Dive. Humana to exit more Medicare Advantage plans in 2027. 2026. Humana exiting plans covering roughly 600,000 members for 2027, about 8 percent of its 7.2 million Medicare Advantage members, in a second consecutive year of market exits.

‍

Ask a health plan how much of its member service call volume actually gets reviewed and you will hear some version of a small sample. Ask the same question about the provider line and often there is no answer at all, because no one is really looking. The provider call center is the call center most plans forgot they own. It is treated as a cost center to be managed down, a queue measured by how fast calls end rather than by what they reveal.

That is a mistake, because provider calls are the most honest diagnostic feed a plan has. A provider does not call to chat. They call to dispute a denial, to chase an authorization that has been sitting for a week, or to ask why a claim was paid wrong. Each of those calls is a precise report on where the plan’s own configuration and utilization management are failing, delivered for free, and it lands in the same blind spot as the member calls no one reviews. The provider line is an intelligence asset, and the way most plans run it guarantees they never see the signal.

A desk measured by handle time, not insight

The volume behind these calls is not small. Physicians and their staff complete an average of 39 prior authorization requests per week and spend roughly 13 hours on them, and two in five practices now employ staff who work exclusively on prior authorization.¹ More than nine in ten physicians say prior authorization delays care.¹ Every one of those friction points is a reason to pick up the phone and call the plan.

The calls cluster around a handful of operational failures: authorization status, claim denials, eligibility mismatches, and payments that came out wrong. Only about 35 percent of prior authorizations are conducted fully electronically, which pushes the rest onto portals and phones,² and a single manual claim status check costs the industry an estimated 15.96 dollars every time.³ Read one at a time, they are just tickets. Read in aggregate, they point straight at the rules, the queues, and the configurations that produced them.

Two patterns recur. The first is repeat authorization confusion: the same service, the same policy, the same question surfacing call after call because the criteria behind it are unclear or applied inconsistently. The second is claims that generate predictable rework, a class of claims that denies or pays wrong the same way every cycle, each instance producing a dispute, a reprocess, and a call. Neither pattern is visible from a single interaction. Both are obvious the moment someone reads the calls together, which is exactly what almost no plan does.

This is where provider abrasion stops being a soft relationship metric and becomes a hard operational risk. Providers who fight the same avoidable denials and chase the same unanswered authorizations grow less willing to participate. Sustained abrasion drives provider attrition, and attrition threatens network adequacy, which for Medicare Advantage and Medicaid plans is a CMS compliance obligation, not a preference. The provider call center is an early warning system for a network problem that otherwise shows up on a compliance report months later, once it is expensive to fix.

Why your vendor will never surface the root cause

Here is the uncomfortable part. If your provider call center is run by an outsourcing vendor, that vendor is paid to close calls, not to eliminate the reasons for them. It reports handle time, closure rate, and service level. It does not report that a fifth of this week’s denial calls trace to one misconfigured edit, because finding and fixing that would shrink its own call volume and its own revenue. A vendor priced per call or per FTE has no incentive to make itself smaller.

This is the core of it. Outsourcing the labor of answering provider calls can be a perfectly reasonable choice. Outsourcing the intelligence inside those calls is not. When the vendor owns the process knowledge, the plan is left renting insight into its own operations and getting back only the metrics the vendor chooses to surface. The signal that would let the plan fix the upstream cause stays locked in a black box, because the party holding it benefits from the problem continuing.

The appeals data shows what that costs. Prior authorization denials are overturned on appeal 67 percent of the time in Medicare Advantage, 47 percent in Medicaid managed care, and 43 percent in the ACA Marketplace.⁴ A denial that gets overturned was a denial that should not have happened, and most of them generated a provider call first. The pattern was audible on the phone long before it reached appeal.

What to look for in a solution

When evaluating how to get intelligence out of your provider calls, the criteria are less about the phone and more about the data behind it.

• Full coverage, not a sample. Sampling a small share of calls, the industry norm sits around 2 to 5 percent,⁵ guarantees you miss the patterns that matter. Look for review of every call, member and provider.

• Every language, automatically. Non-English provider and member calls are the least reviewed and the most invisible. Coverage should not depend on the language of the call.

• Root cause, not just scoring. The goal is not a cleaner scorecard. It is the ability to see which configuration and utilization management failures drive the calls and route that back to the teams who own the fix.

• Payer owned data. The analysis, and the institutional memory it builds, should stay with the plan regardless of who staffs the phones.

• Independence from the labor model. The intelligence layer should sit on top of any call center, in house or outsourced, so you are never choosing between staffing help and visibility.

Claro by Mizzeto was built to close exactly this gap. It reviews 100 percent of a plan's calls, in every language, applying the same rubric across every dimension it scores, and on the provider line that means surfacing the denial, authorization, and payment patterns driving the calls. The plan can trace the pattern back to its cause instead of just answering the same symptom again and again, and the data stays with the plan regardless of who is staffing the phones.

The signal is already on the line

Your provider call center is already telling you where your operations break, and where your network is quietly starting to fray. The only question is whether anyone on your side is listening, or whether that signal is being answered, closed, and thrown away by a vendor with no reason to change it. Plans that start treating the provider line as intelligence rather than overhead find the same errors their appeals unit and their network team have been fighting for months, sitting in plain sight in the call log. To hear what your provider calls are saying, send us a sample and we will score them and show you the patterns.

References

1. American Medical Association. 2024 Prior Authorization Physician Survey. Survey of 1,000 physicians, December 2024. Average of 39 prior authorizations per physician per week; roughly 13 hours of physician and staff time weekly; 40 percent employ staff dedicated to prior authorization; more than 90 percent report prior authorization delays care.

2. CAQH. 2024 CAQH Index. 2025. About 35 percent of prior authorizations are conducted fully electronically.

3. CAQH. 2023 CAQH Index. 2024. A manual claim status transaction costs an estimated 15.96 dollars.

4. KFF. Prior Authorization Metrics Provide New Insights into Insurer Practices, but Gaps Remain. 2026. Prior authorization denials overturned on appeal in 67 percent of Medicare Advantage cases, 47 percent in Medicaid managed care, and 43 percent in the ACA federally facilitated Marketplace.

5. SQM Group. Call center quality assurance benchmarks. Health plans typically review an estimated 2 to 5 percent of calls.

‍