Health economics outcomes research in wound care answers one question payers and manufacturers both need answered: does a product close wounds faster or cheaper than the standard of care it’s replacing, and can that claim survive an audit? HEOR is not a substitute for the pivotal trial that got a product to market. It is the evidence layer that determines whether that product gets paid for, ranked favorably in a value analysis committee packet, or flagged in a Medicare audit. This article covers what HEOR studies actually measure, where the underlying data comes from, the methods used to compare cellular, acellular, and matrix-like products (CAMPs, also called cellular and/or tissue-based products, CTPs, or “skin substitutes”) and other modalities, and where these studies commonly fail scrutiny once they leave the poster session and land in front of a payer or an IDN contracting team.
The distinction matters because the two evidence types answer different questions. A randomized controlled trial measures efficacy under controlled conditions: a defined population, a fixed protocol, a specific endpoint at a specific week. Health economics outcomes research measures what happens when that same product is used across thousands of real patients with variable adherence, comorbidities, and care settings, and it prices that outcome against alternatives. In wound care, that real-world gap is unusually wide. Chronic wounds recur, patients cycle between hospital-based wound centers, home health, and skilled nursing facilities, and a single episode of care can span months with dozens of encounters, each generating its own utilization and cost data.
That complexity is exactly why wound care is HEOR-heavy relative to other therapeutic areas. A diabetic foot ulcer or venous leg ulcer episode isn’t a single transaction; it’s a longitudinal series of debridements, offloading, compression, product applications, and imaging, often billed by different providers in different settings under different payment rules. Tracking true cost per healed wound requires stitching together data most single-site studies never capture.
Within HEOR, comparative effectiveness research (CER) and cost-effectiveness analysis serve distinct purposes. CER asks which intervention produces a better clinical outcome, holding cost aside: time to closure, wound-free days, recurrence rate. Cost-effectiveness analysis asks what that better outcome costs to achieve, and whether the incremental benefit justifies the incremental spend. For CTP/CAMP evaluation, CER typically comes first, comparing healing rates and closure times across products and against standard of care, while cost-effectiveness analysis follows to translate those outcomes into the total episode-of-care cost that payers and GPOs actually negotiate against.
Why Does HEOR Matter for CTP/CAMP Coverage Decisions?
The economics of this product category changed on January 1, 2026. Under the CY 2026 Medicare Physician Fee Schedule and OPPS final rules, CMS stopped paying for most skin substitutes as biologicals at average sales price and instead pays for them as incident-to supplies at a single national rate. CMS initially finalized that rate at $127.28/cm², then issued correction notices revising it to $127.14/cm² (before geographic adjustment). Legal challenges to the new methodology have so far been dismissed, and clinicians continue to be paid the flat rate. The CY 2027 proposed rule does not propose revisiting that methodology, and would extend the same per-square-centimeter rate to non-sheet products. CMS has also said it intends to propose different payment rates by FDA regulatory pathway in future years. When every product is paid the same, price no longer differentiates products. Evidence does.
Coverage policy is less settled than payment policy. The unified Local Coverage Determinations for skin substitutes used on DFUs and VLUs, which would have sorted products into covered and non-covered lists based on evidence, were withdrawn on December 24, 2025, days before their January 1, 2026 effective date. As a result, Novitas, First Coast, and CGS kept their existing skin substitute policies unchanged, while Palmetto, NGS, WPS, and Noridian still have no published LCD and decide coverage case by case under the “reasonable and necessary” standard. The evidence question has not gone away. In July 2026, CMS’s Coverage and Analysis Group reopened its call for clinical evidence on skin substitutes. Because coverage rules are jurisdiction-specific and still in flux, manufacturers and providers should verify current policy directly on the relevant MAC’s website before relying on it for coverage or billing decisions.
The underlying gap is the same either way: FDA marketing status does not establish that a product performs better, or more cost-effectively, than the alternatives. A 510(k) clearance means FDA found the product substantially equivalent to a legally marketed predicate device, and many products in this category, including most amniotic products, are 361 HCT/Ps that reach the market without premarket clearance or approval. HEOR is the evidence category built to close that gap.
On the defensive side, HEOR data supports the post-market evidence obligations manufacturers carry after launch, including the Post-Market Clinical Follow-Up (PMCF) required under the EU Medical Device Regulation for products sold in Europe, and it supplies exactly the kind of real-world evidence CMS is now soliciting in the U.S. When a MAC medical director or a program integrity contractor questions why a product is being used at a volume or in a population that looks inconsistent with its labeled indication, a manufacturer with an active real-world utilization dataset can respond with evidence rather than assertion. The same dataset supports coverage appeals: if a claim is denied and the provider or manufacturer can show, with cross-setting data, that the product’s real-world healing performance and utilization pattern align with its intended use, that evidence carries more weight in an appeal than a single case report. That matters because clinicians report losing appeals at the ALJ level on the grounds that a product was “experimental.”
Providers face the same exposure. A wound center that cannot show, at the level of a payer audit, why a given CTP/CAMP was selected over lower-cost alternatives for a specific patient is relying on clinical judgment alone, which is a weaker position than clinical judgment backed by comparative outcomes data.
On the offensive side, HEOR data often surfaces something manufacturers don’t expect: their product is being used differently than their commercial strategy assumes. Utilization data broken out by setting, wound type, and applications-per-episode can reveal that a product marketed primarily for DFUs is seeing meaningful volume in venous leg ulcer or pressure injury populations, or that adoption is concentrated in home health rather than hospital-based wound centers. That pattern can represent either audit exposure, if the use falls outside covered indications, or an underexploited market opportunity, if outcomes in that off-label setting are strong enough to justify a label expansion study or a targeted commercial push.
What Data Sources Power Wound Care HEOR Studies?
The credibility of any HEOR finding depends on where the underlying data came from, and the three common sources carry different bias profiles. Claims data (Medicare fee-for-service, MA encounter data, commercial claims) offers scale and payment accuracy but limited clinical granularity: wound size, depth, and etiology are often absent or inconsistently coded, and setting transitions can be hard to trace. EHR-derived registries capture the clinical detail claims data lacks (wound measurements, comorbidity documentation, treatment sequencing), but completeness depends on structured documentation at the point of care, and single-EHR registries inherit whatever selection bias exists in the participating sites. Manufacturer-sponsored studies can be methodologically rigorous, but payers and MACs weight them lower by default given the inherent incentive to find favorable results, particularly when the study population, follow-up window, or comparator was chosen after the fact.
Setting-specific real-world data adds a dimension none of these sources fully deliver alone: visibility into how a product is actually used once it leaves the formulary and enters practice. Utilization in a hospital-based wound center, where application protocols and staff training tend to be more standardized, often looks different from utilization in a skilled nursing facility or during a home health visit, where visit frequency, wound assessment consistency, and product access vary considerably. A product ranking or comparative effectiveness claim built only on hospital-based wound center data will not generalize to the SNF population a payer is actually trying to manage costs for, and vice versa.
This is the gap cross-setting datasets are built to close. Intellicure Analytics’ Wound Care Industry Dashboard aggregates real-world utilization and outcomes data across hospital-based wound centers, SNFs, and home health, which is what allows the comparative effectiveness studies and product ranking reports built on top of it to reflect how CTPs/CAMPs actually perform across the full continuum of care rather than in one setting alone. For manufacturers and provider organizations trying to build a defensible HEOR narrative, that cross-setting completeness is usually the single biggest determinant of whether a payer or MAC takes the analysis seriously.
How Do Researchers Measure Cost-Effectiveness in Wound Care?
Most wound care cost-effectiveness work centers on a small set of endpoints that map reasonably well to both clinical meaning and payer priorities. Cost per healed wound is the most commonly cited figure, calculated as total cohort spend divided by the number of wounds that achieved closure within a defined window (equivalently, average spend per patient divided by the healing rate). The window itself (12 weeks is common for DFUs, longer for VLUs) materially changes the result and needs to be stated explicitly rather than assumed. Complete wound closure is the primary healing endpoint FDA recognizes, but time to closure and wound-free days (the proportion of a follow-up period a patient spends with a closed wound, accounting for recurrence) capture the durability dimension that a simple binary closure rate misses. Readmission avoidance and, for diabetic foot ulcers specifically, major amputation avoidance are used as downstream cost offsets, since a product that reduces amputation risk can be cost-effective even at a higher upfront price.
Quality-adjusted life year (QALY) modeling, standard in most health economics work, is harder to apply cleanly to chronic wound populations. Wound patients frequently carry diabetes, peripheral arterial disease, chronic kidney disease, and other comorbidities that independently affect quality of life and survival, which makes it difficult to isolate the utility gain attributable to wound closure itself versus the underlying disease trajectory. Utility instruments validated in general populations don’t always capture wound-specific quality-of-life burden well, and mortality competing with wound outcomes in older, comorbid populations complicates the standard QALY denominator. Researchers publishing wound-specific cost-effectiveness models generally need to disclose these limitations explicitly rather than presenting a clean incremental cost-per-QALY figure as if it were as reliable as one from, say, an oncology model.
Episode-of-care cost modeling has become the more practical alternative for payer-facing analyses, and it is also the logic behind the wound-relevant “non-pressure ulcer” cost measure CMS is developing for MIPS. This approach tallies the full cost stack across an episode: product acquisition cost, application/procedure billing, visit frequency across the healing timeline, debridement and ancillary services, and any shifts in site of care (for example, a patient moving from hospital-based wound center visits to home health as the wound improves). Because it doesn’t require the same utility-weighting assumptions as a QALY model, episode-of-care modeling tends to be more transportable across payer types and easier for a value analysis committee to interrogate line by line.
What Are the Common Pitfalls in Wound Care HEOR Studies?
Confounding by indication is the pitfall that undermines the largest share of wound care comparative outcomes claims. Advanced therapies, CTPs/CAMPs among them, are disproportionately used on wounds that failed standard of care first: larger, older, more ischemic, more infected. A naive comparison showing that a CTP/CAMP’s healing rate looks worse than standard of care’s is often measuring patient severity, not product performance, and the reverse bias applies too when a product’s apparent superiority is really a reflection of it being reserved for well-selected, lower-risk patients. Studies that don’t adjust for wound duration, size, depth, and vascular status at baseline, or that don’t use propensity matching or a comparable risk-stratification method, should be read with real skepticism.
Small, single-site samples are the second recurring problem. A study of 40 patients treated at one hospital-based wound center under one clinical team’s protocols tells you something about that team’s results with that protocol. It does not tell you how the product performs across geographies, payer mixes, or care settings, and payers evaluating a national coverage question know this. Sample size alone doesn’t fix the generalizability problem either; a large single-site study still reflects one site’s referral pattern, one region’s patient population, and one team’s technique.
Selective outcome reporting and short follow-up windows compound both problems. A study that reports closure rate at 12 weeks but not recurrence at 6 months can materially overstate a product’s real value if wounds that closed reopen shortly after the study window ends. Manufacturers and researchers should be explicit about which endpoints were pre-specified versus which were selected after seeing the data, and providers evaluating a product for formulary inclusion should ask directly what the follow-up window was and whether recurrence was tracked at all.
How Should Manufacturers and Providers Act on HEOR Findings?
For manufacturers, the most direct commercial application of HEOR data is the GPO and IDN value analysis committee submission. VAC reviewers are increasingly skeptical of manufacturer-supplied efficacy claims alone and want to see comparative effectiveness data and, where available, product ranking data drawn from real-world, cross-setting sources rather than sponsor-selected case series. A submission built around independently sourced comparative effectiveness studies and utilization benchmarks tends to move faster through committee review than one built entirely on the pivotal trial and marketing materials.
HEOR findings and post-market surveillance obligations, including EU MDR PMCF for wound care products marketed in Europe, should be treated as the same workstream rather than separate compliance exercises. A manufacturer running ongoing real-world data collection to satisfy post-market requirements is, at the same time, building the evidence base needed to respond to an LCD reconsideration, a CMS call for evidence, or a coverage challenge before it becomes urgent. Waiting until a MAC opens a comment period or an auditor issues a records request to start assembling real-world evidence puts the manufacturer in a reactive position with a compressed timeline; a standing post-market and HEOR program means that evidence largely already exists when it’s needed.
The larger strategic shift is treating HEOR as continuous rather than a one-time launch deliverable. Coverage policy, payment policy, competitor entries, and site-of-care patterns all move after launch, and a comparative effectiveness position that was accurate at market entry can be stale within two or three years as new products enter the market and utilization patterns shift across settings. Manufacturers that build ongoing evidence generation into their commercial planning, refreshing utilization and outcomes data on a regular cadence rather than only at launch, are better positioned both to defend existing coverage and to identify where their product’s real-world performance supports expansion into new settings or indications.
Building an Evidence Base That Holds Up Under Review
Credible wound care HEOR does not come from a single site’s case series or a manufacturer-run registry with no external validation. It comes from cross-setting, real-world data that captures how a product actually performs across hospital-based wound centers, SNFs, and home health, adjusted for the patient severity that drives confounding by indication in the first place. Anything narrower invites the scrutiny this audience already brings to every claim: where’s the comparator, what’s the follow-up window, and does this generalize past one clinic.
If you’re assessing where your own evidence has gaps, whether that’s a coverage appeal, a VAC submission, a response to CMS’s call for evidence, or a post-market obligation coming due, start by identifying which settings and wound types your current data doesn’t cover. Comparative effectiveness studies and product ranking reports built on cross-setting utilization data are one way to close that gap without commissioning a new prospective study from scratch. Learn more about our services.