The Hidden Price Predictor in Government Data and Why You Can't Predict Surgery Cost

Medicare publishes what it pays hospitals for every procedure in America, and that data is free. Our research found those rates predict surgery costs within 17% accuracy for most procedures, tested across 21 specialties. That's more than twice as accurate as any simpler approach.

This is the second in a three-part series. Part 1 covered why healthcare prices are so hard to find. This post explains what we found, and how it powers the estimates on Sylk Health's procedure pages. Part 3 shows what it means for your decisions.

Why Do Medicare Rates Predict Surgery Costs?

At first glance, Medicare rates and cash prices seem completely unrelated. Medicare is a government program with set payment rates. Cash prices are whatever hospitals decide to charge patients paying out of pocket.

Earlier research pointed the same way. A foundational 2017 study (opens in new tab) found that changes in Medicare payments do influence private insurance rates (roughly $1.16 in private rates for every $1 change in Medicare), but the overall pricing systems seemed to operate independently.

Cash prices turn out to be different. They're posted, non-negotiated, and according to a 2021 study in JAMA Network Open (opens in new tab), set below what insurers pay at nearly half of all hospitals. Cash patients and insured patients are effectively shopping in different markets.

When we modeled the Medicare-to-cash relationship at the procedure level, the picture changed completely. Medicare rates alone explain about 80% of the variation in cash surgical prices across 424 procedures in 21 specialties.

If you know what Medicare pays for a procedure, you can make a solid estimate of what you'd pay in cash.

Why Isn't the Markup the Same for Every Procedure?

The connection between Medicare and cash prices isn't as simple as "multiply by 2." The markup varies depending on how expensive the procedure is, and the pattern makes intuitive sense.

For lower-cost procedures, the cash-to-Medicare ratio is higher. Whether a procedure takes 15 minutes or 2 hours, the hospital still has the same basic overhead. The building, the nurses, the equipment, the electricity. For a quick procedure that Medicare reimburses at $1,500, that fixed overhead represents a bigger share of the total cost. So the markup is higher.

For more expensive procedures, the ratio shrinks. When a surgery already costs $10,000 or more in Medicare terms, patients are more price-sensitive and more likely to shop around. Hospitals can't mark up as aggressively without losing patients to competitors.

Our formula captures this with different multipliers at different price levels. The logic works like a tax bracket: procedures in the lowest Medicare payment range get the highest multiplier, and it steps down as the Medicare rate increases.

This tiered approach is why the formula works so much better than applying a single ratio to everything.

How Accurate Is the Tiered Formula?

We tested the formula against simpler alternatives to make sure the added complexity actually earned its keep.

The tiered formula cuts the error by more than half compared to using a single multiplier. And the improvement held up across repeated rounds of cross-validation, where we hid portions of the data, predicted them, and checked the answers each time.

What Does Our Accuracy Look Like?

If a procedure actually costs $10,000 in the cash market, our formula would typically estimate somewhere between $8,300 and $11,700. Here's how estimates stack up across all procedures:

• About 2 in 5 are estimated within 15% of the real price

• About 4 in 5 land within 30%

• 96% fall within 50%

• Less than 1 in 25 are off by more than half

Not pinpoint precision, but a lot better than having nothing to go on. You can see how these estimates look for real procedures on our procedures page.

Does It Work Across Specialties?

One concern with any pricing formula is whether it only works for certain types of surgery. We tested accuracy across six major surgical specialties:

The formula performs best on standardized, high-volume procedures. That's exactly where patients are most likely to shop around. Interestingly, building separate formulas for each specialty actually made predictions worse. Prices vary just as much within a specialty as between them.

What Didn't Work?

We also tried approaches that sounded like they should outperform a simple formula.

Machine learning made things worse. We built a gradient-boosted tree model (similar to what powers many recommendation systems) to correct the formula's remaining errors. It actually increased the typical error from 17% to 24%. The model was trained on a broader, messier dataset and kept "fixing" predictions that were already close.

Specialty-specific multipliers backfired too. Instead of one set of multipliers for all procedures, we tried different multipliers for each specialty. Slightly less accurate, because the pricing patterns within specialties are too varied for a specialty-level correction to help.

In total, ten different approaches were tested, including:

• Single Medicare multiplier (constant ratio for everything)

• Specialty-specific multipliers

• Gradient-boosted tree correction

• Log-linear regression with additional specialty features

• RVU-enhanced models with extra cost variables

None beat the tiered formula. The formula has essentially reached the ceiling of what's possible with national averages. The remaining error comes from inherent noise in the cash price market, not from a fixable flaw in the model.

The Data Behind It

We analyzed 424 elective surgical procedures ranging from $200 to $110,000 across 21 specialties. Cash price benchmarks came from publicly available sources including healthcare pricing marketplaces like MDsave (opens in new tab) and hospital postings.

Medicare payment data came from the government's most recent (January 2026) published rates. Anyone can download it for free from the CMS website.

The formula achieves two accuracy levels:

• 17% median error for the 330 procedures estimated purely by formula

• 21% median error for all 424 procedures, including some where the formula struggles and we use directly researched prices instead

That second number is important. We identified 94 procedures in the analysis set, mostly complex reconstructive surgeries, where no formula could be accurate enough. Our team researched those prices individually. Both the formula estimates and the directly researched prices are what you'll find when you browse procedures on Sylk Health.

What Makes This Different?

Several websites offer healthcare price estimates, and they serve an important role. Our approach differs in one key way: we publish exactly how accurate (and inaccurate) our estimates are.

The full methodology is open. Every formula parameter, every test result, every limitation. Any researcher or journalist can reproduce the work and check it against their own data.

That kind of transparency is rare in healthcare pricing, where accuracy claims are typically proprietary and unverifiable. Knowing that a tool is "about 17% off on average, tends to underestimate slightly, and works best for routine procedures" gives you a much clearer picture of how much trust to place in any specific estimate.

In Part 3, we look at what this means for you: how to use an imperfect estimate to make better decisions about where to get surgery, whether medical tourism makes sense, and how to budget when you're paying out of pocket. In the meantime, our booking page

This article summarizes findings from original research on healthcare pricing currently undergoing peer review. It is not medical or financial advice and is not a substitute for professional guidance. Always consult directly with healthcare providers and your insurance company for pricing specific to your situation.