The Next Evolution of Class of Trade: Why Customer Identity Is Becoming Market Access’s Hardest Problem

In pharmaceutical market access, pricing is downstream of a deceptively simple question: who, exactly, is the customer? A retail pharmacy, a hospital outpatient department, a specialty pharmacy, and a 340B-eligible clinic can each be entitled to a different price for the same drug.

Before any of those prices can be applied—or disclosed or audited—someone must correctly classify the buyer. That classification is what the industry calls Class of Trade (CoT), and it is quietly becoming one of the hardest problems in commercial operations.

An earlier article in this series argued that accurate CoT classification is foundational to pricing, contract eligibility, and compliance. This follow-up looks forward.

Four forces—healthcare consolidation, the rise of specialty pharmacy, the spread of integrated delivery networks (IDNs), and the maturation of data and analytics technology—are reshaping what CoT management has to accomplish. Together, they are multiplying both the number of customer entities a manufacturer must resolve and the financial consequence of resolving any one of them incorrectly.

A customer base that will not hold still

The structural reality underneath CoT is consolidation and its pace is striking. As of January 2024, 77.6% of U.S. physicians were employed by hospitals, health systems, or other corporate entities, up from roughly a quarter in 2012. More than 44,000 practices were acquired between 2019 and 2024.¹

The most recent analysis in the same series found the figure had climbed to about 82% by January 2026.² Hospital affiliation tells a parallel story: the share of U.S. hospitals belonging to a system rose from 56% in 2010 to 80% in 2024, and in nearly half of metropolitan areas just one or two systems now control the entire inpatient market.³

Each of those transactions is, from a CoT standpoint, a reclassification event. An independent pharmacy acquired by a hospital system may move from one class of trade to another—with different contract eligibility and a different price—on the day the deal closes, even though the storefront, the signage, and the National Provider Identifier may not change for months.

The Government Accountability Office has documented that hospital–physician consolidation can shift care to higher-priced settings, which is precisely why payers and manufacturers care which entity an account truly belongs to.⁴

Specialty growth concentrates the stakes

At the same time, the economic center of gravity is moving toward specialty medicines, where CoT errors are most expensive. Specialty drugs accounted for more than half of U.S. prescription drug expenditure in 2024, and the segment grew by nearly 12% year over year.⁵

Pharmacies dispensed an estimated $265 billion in specialty medications that year, and the three largest pharmacy benefit manager–owned specialty pharmacies generated about two-thirds of that revenue.⁶ Specialty distribution routinely bypasses traditional retail through limited networks, and a growing share flows through hospital- and health-system-owned specialty pharmacies.

High-cost therapies leave little room for error: misclassifying a single high-volume specialty account can move millions of dollars through the wrong price or the wrong rebate before anyone notices.

Integrated networks blur the category lines

IDNs are where these forces converge and where classification is hardest. A single integrated network can simultaneously operate acute-care hospitals, outpatient clinics, retail and specialty pharmacies, 340B-covered entities, and—in the “payvider” model—its own health plan.

One corporate parent can therefore span several mutually exclusive classes of trade and pricing eligibilities at once. There are roughly 1,000 IDNs in the United States, and in several states, nearly every hospital belongs to a system.⁷

The standard identifiers used to resolve accounts were not built for this. NPI, DEA, and Health Industry Numbers describe physical locations and individual prescribers, they do not encode the corporate ownership tree that determines CoT.

Wholesalers also submit these identifiers inconsistently across chargeback transactions, so the link between a transaction and the entity that actually controls the account often must be made— and can be made wrong—by hand. As ownership structures grow more layered, the gap between what an identifier says and who an account really belongs to is exactly where misclassification lives.⁸

Policy raises the cost of every error

These complications would matter less if the penalty for a wrong classification were small. It is not, and it is rising. The 340B program, where eligibility turns entirely on correct entity identification, reached a record $81.4 billion in discounted purchases in 2024. This represents a 23% increase over 2023, with hospitals accounting for roughly 87%.⁹

More than 30 manufacturers have implemented contract-pharmacy restrictions, and a HRSA rebate-model pilot tied to negotiated drugs was vacated and remanded by a federal court in early 2026, with each change altering the data a manufacturer must capture to adjudicate a 340B claim correctly.¹⁰

Federal pricing policy compounds the pressure. The first 10 Medicare-negotiated prices under the Inflation Reduction Act took effect January 1, 2026, at 38% to 79% below list.¹¹

And the 2024 Medicaid Drug Rebate Program final rule, alongside the elimination of the rebate cap, leans directly on entity identification, requiring managed care plans to use unique identifiers to help prevent duplicate discounts.¹² Each of these regimes ties a specific, often confidential price to a specific eligible entity.

Accurate CoT is no longer just good operational hygiene, it is a precondition for compliance.

The cost of getting it wrong

The financial signature of poor customer data is measurable. Gartner has estimated that poor data quality costs organizations an average of $12.9 million per year.¹³

In pharmaceutical distribution specifically, analyses put chargeback error rates at several percent of contractual sales. One industry estimate places annual revenue leakage from duplicate rebates, chargeback errors, and related failures at more than $15 billion across the sector.¹⁴

Against a 2024 brand-drug gross-to-net gap of roughly $356 billion—the pool from which chargebacks, 340B discounts, and rebates are drawn—even a low misclassification rate becomes material.¹⁵

Where technology fits and where it does not

The most promising response is to treat customer master data as a strategic asset rather than a back-office cost. Machine learning and, increasingly, generative AI are being applied to entity resolution: matching messy transaction records to the correct master entity, flagging ownership changes, and resolving duplicates that rule-based systems miss.

Vendors in the life sciences reference data and master data management space—including platforms such as IQVIA OneKey, Veeva OpenData and Network, Reltio, and Informatica—have moved in this direction. Published technical literature reports improved match accuracy and fewer false positives when these techniques are layered onto human data stewardship.¹⁶

The 2025 settlement and data-sharing agreement between two of the largest reference data providers signals how quickly this part of the market is itself consolidating around the entity-resolution problem.¹⁷ Technology is necessary but not sufficient.

The recurring lesson from CoT practice is that automation handles the obvious cases and surfaces the hard ones. The genuinely ambiguous classifications, such as a hospital-owned outpatient pharmacy that looks like retail or a newly acquired clinic mid-integration, still require documented rules, source-of-truth discipline, and human judgment.

Governance frameworks that pair standardized classification criteria with structured validation and scheduled review remain the backbone. AI raises the ceiling on what that governance can cover, not the need for it.

Implications for market access strategy

For pricing, contracting, compliance, and market access leaders, the conclusion is that customer-data accuracy has migrated from an operational detail to a determinant of net price and regulatory exposure.

Three priorities follow:

1. First, treat reclassification as a continuous process tied to M&A monitoring, not a periodic data refresh, because the customer base now changes faster than annual cycles can track.
2. Second, invest in entity resolution that resolves ownership, not just location, because identifiers alone no longer capture who controls an account.
3. Third, bring the people who do this work into the design of pricing and compliance controls, because they can point to exactly where classification breaks before a wrong price goes out.

None of this is glamorous and that is partly why it has been underinvested. But as consolidation accelerates, specialty spend concentrates, and policy ties ever larger sums to entity identity, the organizations that get CoT right will hold a quiet but durable advantage: their pricing, their contracts, and their compliance will rest on customer data that reflects reality, rather than a snapshot the market has already left behind.

About the Author

Manasi Salgaonkar is a pharmaceutical market access professional specializing in membership and chargebacks — the operations that underpin drug pricing, contract eligibility, and discount adjudication across the pharmaceutical supply chain. She holds a Master’s in Healthcare Decision Analysis from the University of Southern California and a Master’s in Bioanalytical Sciences, with earlier experience in clinical research. She serves as a peer reviewer for journals in the managed care and outcomes research space, including the American Journal of Managed Care, and writes on data governance, pricing, and market access for industry and policy publications.

References

1. Physicians Advocacy Institute / Avalere Health. “COVID-19’s Impact on Acquisitions of Physician Practices and Physician Employment 2019–2024.” Reported in Healthcare Dive, April 12, 2024. https://www.healthcaredive.com/news/doctor-corporate-ownership-growing-hospital-insurer-pai-avalere/712988/
2. Physicians Advocacy Institute / Avalere Health, January 2026 update. Reported in Chief Healthcare Executive, December 2025. https://www.chiefhealthcareexecutive.com/view/corporate-groups-pass-hospitals-in-ownership-of-physician-practices
3. KFF. “One or Two Health Systems Controlled the Entire Market for Inpatient Hospital Care in Nearly Half of Metropolitan Areas,” 2024; American Hospital Association, AHA Fast Facts, 2024. https://www.kff.org/health-costs/one-or-two-health-systems-controlled-the-entire-market-for-inpatient-hospital-care-in-nearly-half-of-metropolitan-areas/
4. U.S. Government Accountability Office. “Health Care Consolidation: Published Estimates of the Extent and Effects of Physician Consolidation,” GAO-25-107450, September 22, 2025. https://www.gao.gov/products/gao-25-107450
5. American Hospital Association. “Putting 340B Program Growth in Context,” December 16, 2025 (citing IQVIA data on specialty share of drug spend). https://www.aha.org/news/blog/2025-12-16-putting-340b-program-growth-context
6. Fein AJ. “The Top 15 Specialty Pharmacies of 2024.” Drug Channels Institute, April 2025. https://www.drugchannels.net/2025/04/the-top-15-specialty-pharmacies-of-2024.html
7. Definitive Healthcare. “Integrated Delivery Network (IDN)” and “How many IDNs are in the U.S.?” Accessed 2026; Symplr, “Integrated Delivery Networks as Payviders.” https://www.definitivehc.com/resources/glossary/integrated-delivery-network
8. Relasoft. “Customer Identifiers in Pharmaceutical Chargebacks (EDI 844)” and “Pharmaceutical Chargebacks Processing: EDI 849 Error Codes.” Accessed 2026. https://relasoft.net/pharmaceutical-chargebacks-processing-edi-849-error-codes/
9. HRSA Office of Pharmacy Affairs, 2024 Covered Entity Purchases; analysis by Avalere Health Advisory and Drug Channels Institute, December 2025. https://advisory.avalerehealth.com/insights/340b-purchase-data-highlights-continued-program-growth-2
10. HRSA, 340B Rebate Model Pilot Program; American Hospital Association et al. v. Kennedy et al., U.S. District Court for the District of Maine, 2026; Federal Register RFI, February 17, 2026. https://www.hrsa.gov/opa/340b-model-pilot-program
11. Centers for Medicare & Medicaid Services. “Medicare Drug Price Negotiation Program: Negotiated Prices for Initial Price Applicability Year 2026.” https://www.cms.gov/newsroom/fact-sheets/medicare-drug-price-negotiation-program-negotiated-prices-initial-price-applicability-year-2026
12. CMS, Medicaid Drug Rebate Program final rule, Federal Register, September 26, 2024 (effective November 19, 2024). https://www.federalregister.gov/documents/2024/09/26/2024-21254/
13. Gartner. “Data Quality: Why It Matters and How to Achieve It” (citing Gartner research, 2020). https://www.gartner.com/en/data-analytics/topics/data-quality
14. ZS. “Optimizing Revenue Leakage with AI.” Accessed 2026. https://www.zs.com/insights/optimizing-revenue-leakage-with-ai
15. Fein AJ. “340B Hit $81 Billion in 2024.” Drug Channels Institute, December 2025 (gross-to-net analysis). https://www.drugchannels.net/2025/12/340b-hit-81-billion-in-2024-23-why-cms.html
16. Informatica. “10 Ways AI Improves Master Data Management”; ZS, “Generative AI and Master Data Management.” Accessed 2026. https://www.zs.com/insights/generative-ai-and-master-data-management
17. Veeva Systems. “No Data Restrictions” (IQVIA–Veeva settlement and data agreement), August 2025; reported in MobiHealthNews. https://www.mobihealthnews.com/news/iqvia-veeva-systems-partner-and-resolve-years-long-legal-disputes