Less is more in healthcare: It Has Always Been About the Cost

What I keep coming back to, after over three decades in healthcare, is how thoroughly the industry has insulated itself from a principle every other competitive market figured out long ago. In most industries, the pressure to lower cost and the pressure to improve quality move together. They are not in tension. They are the same force expressed two ways. Healthcare has convinced itself the opposite is true, and that belief is costing patients their health and the system enormous sums of money, money that could be doing real work somewhere else.

The manufacturing sector worked through this in the 1980s, software in the 1990s and 2000s. In both cases, the companies that survived learned that quality and efficiency compound when you design processes around doing the right thing rather than doing the maximum thing. Toyota did not become the world's most reliable automaker by building more parts into every car. It became reliable by eliminating every step that did not add value. Amazon Web Services does not compete by giving you more infrastructure than you need. It competes by giving you exactly what you need at a price that reflects what it actually costs to deliver it well. The pattern holds across industries and time: when consumers have real choice and real price information, markets converge on better for less.

Healthcare has no such convergence. The reason is not complicated, even though the industry has invested heavily in making it seem complicated.

Don's Thought

The Doing More Syndrome Is Not a Character Flaw. It Is a System Design.

I want to be precise about what I mean here, because it is easy to read an argument like this as an indictment of clinicians. It is not. The clinicians I know are working inside a system with financial incentives, liability structures, training norms, and time pressures that all push in the same direction: do something. Order the test. Add the prescription. Schedule the follow-up. A physician who chooses watchful waiting over an additional diagnostic workup is taking on both the professional and legal risk of that decision alone, while the system around them has no mechanism for rewarding that judgment. The problem is the design, not the people working inside it.

What researchers call "flat-of-the-curve medicine" is the clinical expression of this design failure. It describes the point at which additional medical services produce no measurable improvement in health outcomes and may, in fact, produce harm through drug interactions, procedural complications, unnecessary anxiety, and cascading downstream interventions triggered by incidental findings. The Dartmouth Atlas of Health Care has documented for decades that regions with higher per-capita Medicare spending do not produce better health outcomes than lower-spending regions. In many cases, they produce worse ones. More is not better. More is often measurably worse. And yet the system continues to reward more.

Don's Thought

If patients paid out of pocket for every marginal service added to their care plan, most of those services would disappear overnight. Not because patients are cheap, but because the value proposition does not hold up when someone is spending their own money. The insulation of third-party payment is the single biggest reason the market has never corrected this behavior on its own.

Subtraction Neglect: Why Doing Less Is Harder Than It Sounds

The sharpest framing of this I have read recently comes from Siva Mohan, an interventional cardiologist and a co-founder of RazorMetrics, writing in Medical Economics this June. He calls it subtraction neglect, borrowing from Adams and Klotz's 2021 finding that people systematically overlook subtractive changes: the bias toward solving a problem by adding something rather than removing something. Physicians are not uniquely susceptible. They just practice inside a system built almost entirely around what to start, and nearly silent on what to stop.

Mohan puts the toll of medication-related harm at 250,000 to 300,000 deaths a year. Argue about the precise number if you want. The direction is not in dispute. Deprescribing (taking a patient off medications that are no longer indicated, that duplicate each other, or that carry a harm profile outweighing the benefit for that specific person) is one of the better-evidenced interventions available in primary care. It is also one of the least practiced.

That gap is the whole argument in miniature. We know what works. The system is not built to do it.

The evidence on fixing it is more sobering than the advocacy suggests, and the sobering part is the most useful thing in the literature. A systematic review and meta-analysis in JAMA Network Open (Linsky and colleagues, May 2025) pooled the deprescribing intervention studies and found moderate-certainty evidence that they do reduce the number of medications a patient is taking. The size of that effect: roughly seven patients have to go through the intervention to remove one medication. The authors were direct about why the estimate came out small, citing inconsistent results across studies, and they did not report mortality, hospitalizations, adverse drug events, or cost at all.

Read that as a failure of deprescribing and you have drawn the wrong lesson. Read it as a measurement of what happens when you bolt a good intervention onto a system whose incentives and workflow have not changed, and it becomes the most important finding in the field.

Because the reflex in our industry is to treat this as an information problem and buy a technology that puts better data in front of the clinician. Better data helps. It is not the first move.

We work in a specific order at Canton: the operator first, then the process, then the technology. Applied here, the operator problem is that a clinician who chooses to do less absorbs the professional and legal risk alone and gets paid nothing for the judgment. The process problem is that subtraction has no workflow. There is a visit type for starting a medication and none for stopping one. Only after those two are addressed does the third layer, real-time patient-specific data, actually change behavior. Deploy the technology on top of an unchanged operator and an unchanged process and you get a dashboard nobody acts on. That sequence is not a stylistic preference. It is the difference between a pilot that converts and a pilot that stalls.

The Patterns That Keep This Problem Alive

In my work, I have watched the same failure patterns repeat with remarkable consistency. The clinical culture piece is real, but it sits on top of structural problems that culture alone cannot solve.

What Other Industries Tell Us

The standard objection to comparing healthcare to manufacturing or software is that healthcare is different because the stakes involve human life. I have heard this argument many times, and I understand why it resonates. But I think it is backward. The stakes involving human life are the argument for doing less unnecessary care, not more. Unnecessary medical interventions carry real harm profiles. Drug interactions kill people. Surgical complications kill people. Iatrogenic infections kill people. Toyota, Amazon, the semiconductor sector, and the airlines got serious about quality improvement precisely because the stakes were high enough that getting it wrong had catastrophic consequences. The high stakes were the argument for rigor, not for exempting themselves from accountability.

Don's Thought

The argument that healthcare is different because the stakes are higher is used to justify exempting it from exactly the kind of disciplined quality thinking that high-stakes industries outside healthcare treat as non-negotiable. I have never found a version of that argument that holds up when you push on it for five minutes.

Here is the comparison that I think matters most. In competitive markets with real price transparency, consumers systematically choose lower-cost options when the quality difference between options is negligible or nonexistent. They do this because they are spending their own money and they have information. Neither condition holds in most of American healthcare. Patients are not spending their own money in any direct sense, and they have little or no price information. As a result, the market signal that would otherwise correct overtreatment never arrives. The Doing More Syndrome is not an anomaly. It is the predictable outcome of those two structural conditions operating together for seventy years.

What changes the picture is not a single product. It is changing what the operator is paid and protected for, giving subtraction an actual workflow, and only then putting the patient-specific signal in front of the clinician at the moment of the decision. A small group of companies is working on that third layer. RazorMetrics is one. MedsEngine is another, approaching chronic disease control with the same conviction: that the evidence has to arrive at the point of care, at the moment the decision is actually being made. The third layer matters. But an organization that buys the third layer and skips the first two has bought a report, not a result.

The Commercial Argument for Getting This Right

For health tech companies building in this space, the argument I just made is not only clinical; it is commercial. The organizations that will win in healthcare over the next decade will demonstrate, with specificity, that their product reduces unnecessary utilization without degrading outcomes. That is the claim a medical director wants validated. That is the claim a CFO will pay for. Most health tech vendors cannot make that claim, because they have not built the evidence infrastructure or the data systems to support it.

Mohan's piece is a good example of that discipline. It is not a product announcement. It is a clinical argument published in a physician trade outlet, which is what the people who make these decisions actually read. It shows a company that understands the problem at the level of the physician's workflow rather than the population health dashboard, and that is where buying decisions in value-based care actually get made. Most vendors in this category cannot produce that, because the thinking has never been written down in a form anyone can read.

Don's Thought

Companies that publish nothing, say nothing publicly, and rely entirely on direct sales will lose to companies that build market authority through the quality of their thinking. In value-based care, your chief medical officer's voice is a commercial asset. Use it that way.

 

The Canton Perspective

If your market position is built on doing the right thing, prove it in public every week.

The health tech companies that will own value-based care over the next five years are the ones building market authority now, through published thinking, clinical credibility, and commercial discipline. Most of them already have the raw material. It sits in the head of a chief medical officer who has never been given the time or structure to get it out. Canton works with companies in exactly this category, the ones trying to get evidence-based care into the decision process at the point of care, and turns that expertise into content, positioning, and sales infrastructure that opens doors at the health system and payer level. Same order every time: the operator, then the process, then the technology. The idea is not complicated. Execution separates the companies that grow from the ones that stall.

Don McDaniel

CEO, Canton Growth Partners