(Chat GPT 5.5, 6/2026, unedited)
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Below is a blog-ready essay draft. I verified the key source anchors, especially Phillips/Science, CMS/MedPAC CLFS mechanics, Garau/Towse/Garrison, Sireci/AMP, and the ASPE molecular diagnostics report. (Book Cafe)
Diagnostics May Create Value, But Medicare Lab Pricing Usually Does Not Price Value
In a recent Science article, Kathryn A. Phillips, David M. Horn, and Robert M. Califf argue that diagnostics are underfunded and undervalued relative to the burden of disease they can address. Their article, “Diagnostics investments and disease burden,” makes an important and timely point: diagnostics can shape care pathways, reduce uncertainty, guide treatment, avoid ineffective interventions, and sometimes produce value well beyond the cost of running the test itself.
Full link: https://bookcafe.yuntsg.com/ueditor/jsp/upload/file/20260416/1776310800792028847.pdf
Phillips et al., 2026, Diagnostic investments and disease burden. Science 392:151-3.
This argument is correct as far as it goes. But it leaves out a critical distinction. It is one thing to say that diagnostics create value. It is another thing to design a payment system that allows the developer or performing laboratory to capture that value. In the U.S. laboratory market, especially under Medicare’s Clinical Laboratory Fee Schedule, that second step is often missing.
Medicare lab pricing is not a miniature health technology assessment system. It does not ask, in any routine way, whether a test avoids a CT scan, prevents a hospitalization, substitutes for a biopsy, prevents use of a futile drug, or changes a clinical decision in a way that produces downstream savings. Instead, new laboratory tests generally enter Medicare payment through crosswalk, gapfill, or—after PAMA implementation—private-payer median pricing.
CMS describes the CLFS process directly. For most clinical diagnostic laboratory tests, Medicare now pays based on the weighted median of private-payer rates reported by applicable laboratories. For new tests, CMS uses the annual CLFS process. Crosswalking occurs when a new test is judged similar to an existing test, so an existing code or group of codes is used to set payment. Gapfilling occurs when no comparable existing test is available, in which case Medicare Administrative Contractors develop local payment amounts and CMS later calculates a national median.
CMS CLFS page:
https://www.cms.gov/medicare/payment/fee-schedules/clinical-laboratory-fee-schedule-clfs
CMS CLFS annual public meetings page:
https://www.cms.gov/medicare/payment/fee-schedules/clinical-laboratory-fee-schedule-clfs/annual-public-meetings
CMS MLN CLFS fact sheet:
https://www.cms.gov/files/document/mln006818-clinical-laboratory-fee-schedule.pdf
This is not value-based pricing. It is administrative pricing, comparability pricing, resource pricing, or market-reported pricing, depending on the route. The test may be valuable, but “value” is not the central input into the Medicare price.
MedPAC’s description of the CLFS makes the same point in more policy-neutral terms. Before PAMA, Medicare lab payments were based on historical charges and national limitation amounts. After PAMA, Medicare shifted to private-payer-based rates. For gapfilled tests, MedPAC describes the process as using information such as charges, discounts to charges, and resources required to perform the test. Again, those are not measures of clinical utility or downstream value.
MedPAC June 2021 report:
https://www.medpac.gov/wp-content/uploads/import_data/scrape_files/docs/default-source/default-document-library/jun21_ch9_medpac_report_to_congress_sec.pdf
MedPAC Payment Basics, Clinical Laboratory Services Payment System:
https://www.medpac.gov/wp-content/uploads/2024/10/MedPAC_Payment_Basics_25_clinical_lab_FINAL_SEC.pdf
The Association for Molecular Pathology’s “Molecular Pathology Economics 101” paper is also useful background. It walks through coding, coverage, and reimbursement for molecular diagnostics, including CPT coding, PLA codes, coverage determinations, CLFS pricing, PAMA, and related mechanisms. It is an excellent professional overview because it shows how much of molecular diagnostic reimbursement is determined by coding architecture, coverage policy, claims processing, and fee schedule mechanics—not by a formal economic valuation of the test’s contribution to the care pathway.
Sireci AN et al., “Molecular Pathology Economics 101: An Overview of Laboratory Reimbursement,” Journal of Molecular Diagnostics, 2020:
https://pmc.ncbi.nlm.nih.gov/articles/PMC7267794/
This distinction—value creation versus value capture—is the missing center of the debate.
Suppose a diagnostic test costs $10 to perform and avoids a $400 CT scan. A simple value argument says the test is worth much more than $10. Perhaps Medicare should pay $100, $200, or even something near the avoided cost, because the system saves money. But the CLFS does not normally work that way. Crosswalk asks what similar tests are paid. Gapfill asks about charges, costs, resources, and payer rates. PAMA asks what private payers have paid. None of these mechanisms asks: “How much downstream medical spending did this test avoid?”
The problem becomes even sharper in an open laboratory market. Imagine Medicare, or a value assessment body, concludes that a diagnostic test produces $1,000 of system value. That does not mean the performing laboratory can actually charge $1,000. If the test is technically replicable, Quest might offer it to a payer for $900. Labcorp might bid $800. Quest might respond at $700. A regional lab might go lower still. The final price may drift toward the competitive cost of producing the service, not the social value created by the information.
This is not just a thought experiment. A 2008 HHS ASPE report on coverage and reimbursement for complex molecular diagnostics states the economic point unusually clearly. It asks the reader to imagine a test that costs $1 to run but saves $1,000 in health care costs. If many competitors can produce the test, economics suggests that the price will tend toward the cost of production. In other words, high clinical value does not automatically produce high market price.
ASPE report, “Current Issues and Options: Coverage and Reimbursement for Complex Molecular Diagnostics,” 2008:
https://aspe.hhs.gov/reports/current-issues-options-coverage-reimbursement-complex-molecular-diagnostics-0
PDF version:
https://www.twentyfirstcenturymedicine.org/wp-content/uploads/2014/02/Coverage_and_Reimbursement_for_Molecular_Diagnostics_Current_Issues.pdf
That is probably the cleanest published statement of the issue. Diagnostics may create system value, but unless the payment system has a way to assign and preserve that value, the price can collapse back toward cost, comparability, or payer-negotiated market rates.
The health economics literature has recognized parts of this problem for years. Garau, Towse, Garrison, Housman, and Ossa asked directly whether value-based pricing could be applied to molecular diagnostics. Their answer was broadly yes in principle, especially for companion diagnostics and other tests closely linked to drug use. But they also recognized that current diagnostic pricing systems are often driven by administrative practices and expected production cost. That observation remains central. Value-based pricing can be conceptually attractive, but conceptually attractive pricing is not the same thing as an enforceable payment system.
Garau M, Towse A, Garrison L, Housman L, Ossa D. “Can and should value-based pricing be applied to molecular diagnostics?” Personalized Medicine, 2013:
https://pubmed.ncbi.nlm.nih.gov/29783475/
Office of Health Economics working paper version:
https://www.ohe.org/wp-content/uploads/2014/07/369-Can-and-Should-VBP-Diagnostics-Garau-2012.pdf
The issue is especially difficult because diagnostics are not drugs. A patented drug often has a period of market exclusivity. A drug manufacturer may be able to defend a value-based price because competitors cannot immediately produce the same molecule. Diagnostics are different. Some proprietary tests have trade secrets, algorithms, FDA status, brand recognition, or evidence packages that create differentiation. But many laboratory tests are more vulnerable to replication, substitution, parallel development, or payer-driven contracting. If multiple laboratories can offer sufficiently similar information, the payer’s purchasing logic becomes competitive procurement, not value capture.
The stratified medicine literature has described this problem in another way. Trusheim and colleagues have emphasized that diagnostic developers often face lower reimbursement and weaker protection than drug manufacturers, even when their tests are essential to the value of a therapy. The diagnostic may be the gatekeeper for the right drug, the right patient, and the right timing, but the economic surplus is often captured elsewhere—by the drug manufacturer, the payer, the provider system, or the patient—not by the diagnostic developer.
Trusheim MR et al., NBER working paper, “An Overview of the Stratified Economics of Stratified Medicine”:
https://www.nber.org/system/files/working_papers/w21233/w21233.pdf
Trusheim MR et al., “The clinical benefits, ethics, and economics of stratified medicine,” Personalized Medicine, 2015:
https://pubmed.ncbi.nlm.nih.gov/26542060/
This creates a policy paradox. The diagnostic may be essential to value-based care, but the diagnostic itself may be paid under a commodity-like laboratory fee schedule. A $5,000 drug decision can depend on a $500 test. A $100,000 oncology regimen can depend on a molecular profile. A costly Alzheimer’s disease care pathway may depend on a biomarker result. But if the lab payment system prices by crosswalk, gapfill, or private-payer medians, the price of the diagnostic is not naturally linked to the value of the downstream decision.
Phillips, Horn, and Califf are therefore right to argue that diagnostics deserve more attention in health policy. Diagnostics can be a neglected infrastructure for better medicine. But the hard part is not only proving value. The hard part is designing institutions that convert diagnostic value into durable payment.
Several mechanisms could, in theory, do this. A payer could create a shared-savings arrangement in which a test developer receives part of the downstream savings. A bundled payment model could include diagnostic-informed management and reward the provider group for choosing high-value tests. A coverage-with-evidence-development model could pay more during a defined evidence-building period. A companion diagnostic could be valued jointly with the therapy it enables. A public payer could create special statutory payment rules for certain high-impact diagnostics. A procurement system could award exclusive or preferred status in exchange for evidence, access commitments, and price discipline.
But without some such mechanism, “value-based pricing” is mostly a slogan. The open market will not necessarily preserve a value price. Payers seek discounts. Laboratories seek volume. Competitors enter. Fee schedules normalize. PAMA collects market prices and feeds them back into Medicare rates. The system can take an initially high-value test and gradually re-express it as a code, a crosswalk, a weighted median, or a contract line item.
This is why the simple phrase “diagnostics should be reimbursed based on value” can be misleading. It compresses three separate questions into one.
First, does the diagnostic create clinical and economic value? Often yes.
Second, can that value be measured credibly? Sometimes yes, sometimes no, depending on the evidence base, timing, comparator, and downstream assumptions.
Third, can the payment system allow the test developer or performing laboratory to capture an appropriate share of that value? That is the hardest question, and in many cases the current answer is no.
The Medicare CLFS is particularly ill-suited to this task. It is a fee schedule, not a value-capture engine. Its logic is administrative, procedural, and code-based. It can assign a payment amount, but it does not typically model the test’s value in the care pathway. Nor does it protect that payment amount from later market erosion when private-payer rates are collected under PAMA. In fact, PAMA can make the problem circular: private market discounts influence Medicare rates, and Medicare rates then influence the broader market.
That does not mean value-based diagnostic payment is impossible. It means it requires explicit policy design. If the goal is to reward diagnostics for avoided costs, better outcomes, reduced uncertainty, or improved targeting of therapy, then those goals must be built into the payment mechanism. Otherwise, value remains a narrative used in coverage arguments, investor decks, and policy essays, while the actual payment amount is determined by crosswalk, gapfill, private-payer medians, or competitive contracting.
The most precise formulation may be this: diagnostics often create value, but laboratory payment systems usually price services. Value creation and service pricing are not the same thing.
Phillips and colleagues have performed a useful service by elevating diagnostics as a neglected category of medical innovation. But the next article needs to go one layer deeper. It should ask not only whether diagnostics are valuable, but how a fragmented and competitive laboratory market can preserve a value-based price. Without that answer, policy may continue to celebrate diagnostic value while reimbursing diagnostics as commodities.
