Leadership1 distinct publisher3 min readPublished
Nathan Frank's team is deleting coordination work that Aetna members had been absorbing themselves. The arithmetic underneath explains why the results took four years to arrive. It also leaves open what happens to the nurse hours freed.
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The order of operations in Frank's account matters more than any single number in it. The enterprise data platform and the Clinical Data Repository were built during the pandemic, before generative AI became an executive priority, and Frank is explicit that the predictive and proactive work would not run at all without the data organised first [10][11]. Everything downstream, including nurse summarisation and the outreach engine, draws on a bill settled years earlier. That is also why the newest-looking piece is the least durable: Aetna says it was the first payer to deploy Rich Communication Services, with engagement above 80 percent and opt-outs under half the SMS level [14][15], and a messaging channel is procurable by any competitor inside a quarter.
The usage figures deserve a harder read than they will get. Frank, speaking to Forbes, puts use below 10 percent under the old cost-estimation model and near 70 percent "among people using the capability before a procedure" [8][16]. Those are not self-evidently the same denominator, since the second is conditioned on members who already reached for the tool. That comparison could be read as flattering the rebuild, but Aetna reports running A/B tests and then tying digital interactions to care costs, prior authorisation automation and outcomes [9], which is the measurement discipline that would eventually settle the question. The version that travels in a board deck, ten to seventy, stays incomplete until the base is stated.
Where the nurse figure came from is more interesting than its size. The prior workflow had a nurse navigating multiple systems and hundreds of pages of clinical documentation before a conversation with a member facing a cancer diagnosis [12]. Ninety minutes is a bit under a fifth of an eight-hour shift [2], and it was going into retrieval. Summarisation before the call, ambient listening during it and organisation afterwards amounts to a search problem solved at the desk, in the same spot where the clinician had been doing the searching by hand [12], rather than a clinical intervention in itself.
The economics explain why this agenda should survive a cost review, which is a different question from whether it is popular. Frank says that when he took the role about four years ago, peers at other insurers were putting their biggest bets on utilisation, cost management and cloud transformation, and he chose member experience instead [6]. But the scorecard he describes asks whether a feature helped someone obtain preventative care or avoid an emergency room visit [9], which is utilisation management approached from the consumer side. The segment carries $143.4 billion of revenue against 26.6 million medical members, roughly $5,390 per member per year [3][5], and it accounts for about 36 percent of CVS Health's 2025 revenue [2][4]. When the payer holds the medical cost, removing the member's homework and lowering the claim are the same project, and the alignment is what makes the spend defensible in a lean year.
An operator with a comparable estate can copy the sequence in Frank's account long before copying any of its outcomes, because the consolidation work sets the ceiling on everything reported after it.
Ranked by verification strength, evidence, and original report placement.
Nathan Frank is Chief Digital and Technology Officer of Aetna and has made eliminating friction in the healthcare experience the central aim of his technology agenda.
Aetna is the health benefits business of CVS Health, which generated $402.1 billion in revenue in 2025.
CVS Health's Health Care Benefits segment, which includes Aetna, generated $143.4 billion and served 26.6 million medical members at year-end.
Frank leads roughly 6,000 technologists supporting a couple thousand platforms, with a remit spanning experiences for members, providers and colleagues, platform modernization and the expansion of artificial intelligence.
Frank said: "There is no other industry where we assign homework to the customer." Healthcare has historically been organized around payers, providers and health systems rather than consumers.
Aetna rebuilt a cost-estimation product covering more than 20,000 medical services, letting members use natural language and AI to estimate the cost of both simple and complex procedures before receiving care.
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forbes.com
1 article · August 30, 2026
Evidence-backed comparisons of source perspectives and observed adoption signals. Read the methodology
Which Builder, Operator, and Investor concerns the observed source mix emphasized—not a truth score.
Evidence, demonstrated adoption, hype gap, incentives, and confidence are assessed independently, each on its own current evidence. How these are measured.
Every metric arrives in the same voice
The 70 percent estimator usage, the 90 nurse-minutes, the 80 percent RCS engagement and the payer-first claim all reach the reader through one sentence pattern — Frank said. Forbes does not disguise that, but an interview cannot check itself, and no filing, nurse, member or competitor appears to corroborate a single operating number. The exception is the corporate scale: $402.1 billion in company revenue, $143.4 billion and 26.6 million members in Health Care Benefits, figures that live in reported results and hold up to arithmetic. Descriptions of what exists — the estimator across 20,000 services, the data platform, the nurse workflow — are specific enough to be credible as deployments; the performance attached to them is not evidenced at all.
Shipped at real scale, scored by the shipper
What lifts this above vapor is size and specificity. Ambient listening and case-note summarization are described as in daily use across more than 15,000 care-management nurses, the estimator spans over 20,000 services, and both sit on a data platform built years before generative AI became fashionable — that is production infrastructure inside a segment serving 26.6 million members, not a pilot. What holds it down is that every usage figure is issuer-side and conveniently bounded: the estimator's 70 percent counts only members who reached for it before a procedure, and RCS engagement is reported without saying across how many campaigns. Real deployment, unaudited uptake.
Bounded numbers, unbounded implications
The overstatement is not in the products, which sound real; it is in how the numbers are cut. "Below 10% to nearly 70%" describes members who already chose to price a procedure, a group whose size we are never told, and the sentence is built to read as though most members now check costs. Ninety minutes a day per nurse — at least 22,500 nurse-hours across the team — is offered without a measurement method, then immediately reassured about, which is how a productivity figure becomes a talking point instead of a result. "First payer to deploy RCS" is asserted, not sourced. Set against that, the data-foundation-before-AI argument is if anything undersold: it is the least glamorous and most checkable thing here.
The subject is also the sole source
A sitting technology chief describing the four-year bet he personally chose, in a headline that declares the bet worked, with no counterparty in the room. Frank's account also does the competitive work of saying rival insurers were busy with utilization and cloud while Aetna picked members — a comparison flattering to the speaker and unavailable for checking. Two sensitive areas sit adjacent to material the story does not pursue: prior authorization automation, named as a success metric in a business where automated denials are contested ground, and a 90-minute efficiency gain in a 15,000-person nursing workforce, pre-emptively decoupled from headcount. Neither is evidence of bad faith; both are reasons the numbers deserve a second source.
Clear about what it is, silent on what we'd need
We are confident in the diagnosis because the story's structure is unambiguous: one interview, one voice, attribution visible on every operating figure, and the corporate arithmetic — 36 percent of revenue, about $5,390 per member, 18.75 percent of a shift — checking out cleanly. Where confidence falls is anything requiring a denominator: how many of 26.6 million members touched the estimator, what share of nurses saw the 90 minutes, whether another payer beat Aetna to RCS. A second account, an outcome disclosure or a nurse's description of the workflow would move this materially in either direction.