From time to time, there are articles about the wide dispersal of prices in US healthcare. (One patient and health plan pays $1000, another patient and health plan pays $6000). We saw that wide dispersal of pricing in the 2016 clin lab payment data released in mid 2017 by CMS as part of PAMA market rates for lab test pricing. By August 2026, we'll have a huge update of 1H2025 clin lab prices for PAMA-II.
Here's a new case study, provided by Jason Nakka at LinkedIn. He had access to data on contracted pathology biopsy rates (CPT 88305) from Cigna. As he writes,
"A slide prepared in Washington State can be read by a pathologist in Iowa, for three times the price. The 88305 read pays median $17 in Oklahoma, and $71 in Nebraska, a 4.2X spread."
Find his dollarized article here. Find his earlier ratio-based article here.
See a commercial consultancy/vender for price data PriceMedic.Com.
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I asked Chat GPT to find 3 articles on the same topic, wide price variability (in other clinical domains). I quote below but haven't validated myself.
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Here are three strong comparators for your pathology-price-variation blog. I’d use Oakes 2024 as the closest “John with BCBS vs Tom with United” example, Whaley 2025 as the broad Transparency in Coverage / TiC-era national frame, and Cooper 2019 as the classic economics anchor. TiC = federally required payer machine readableprice files.
1) Cooper Z, Craig SV, Gaynor M, Van Reenen J. “The Price Ain’t Right? Hospital Prices and Health Spending on the Privately Insured.” Quarterly Journal of Economics. 2019;134(1):51–107. doi:10.1093/qje/qjy020.
Full link: https://doi.org/10.1093/qje/qjy020
Yale page: https://isps.yale.edu/research/publications/isps15-027
This is the classic article showing that, for privately insured patients, prices—not utilization—drive much of the geographic variation in spending, unlike Medicare. It reports threefold variation in private spending across HRRs and very large price dispersion for relatively homogeneous services, including lower-limb MRI prices varying twelvefold nationally and about twofold within HRRs. (isps.yale.edu)
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2) Oakes AH, Ikard M, Patton C, et al. “Understanding Variation in Negotiated Rates Using Novel Health Plan Price Transparency Data.” JAMA Health Forum. 2024;5(9):e243020. doi:10.1001/jamahealthforum.2024.3020.
Full link: https://jamanetwork.com/journals/jama-health-forum/fullarticle/2823759
PubMed: https://pubmed.ncbi.nlm.nih.gov/39302670/
This is probably the best direct analogy to your “same service, different payer” point. Using Transparency in Coverage data, the authors compared UnitedHealthcare and Blue Cross Blue Shield of Illinois rates for hip/knee replacement and found substantial variation within the same market and even within the same hospital across different payers; the PDF reports a mean same-hospital BCBSIL-vs-UHC difference of $5,178, about 20% of the mean negotiated rate. (JAMA Network)
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3) Whaley C, Radhakrishnan N, Richards M, Simon K, Chartock B. “Understanding Health Care Price Variation: Evidence from Transparency-in-Coverage Data.” Health Affairs Scholar. 2025;3(2):qxaf011. doi:10.1093/haschl/qxaf011.
Full link: https://academic.oup.com/healthaffairsscholar/article/3/2/qxaf011/7965202
PMC: https://pmc.ncbi.nlm.nih.gov/articles/PMC11798183/
This is the broadest current national Transparency in Coverage - TiC-based article, documenting price variation across geography, payer, and provider. A nice quotable example for your blog: the mean facility fee for a foot X-ray was $86 at Anthem vs $190 at UnitedHealth, and the authors found weak consistency across inpatient and outpatient price levels—supporting your point that commercial prices are negotiated artifacts, not natural reflections of service cost. (academic.oup.com)