Dirty Little Secrets: Telling the Truth on Healthcare

Dirty Little Secrets: Telling the Truth on Healthcare

by Hannah Mamuszka

Business Health & Fitness

Season 1

Mark Cuban Gets Real on Health Insurance: The House Always Wins

Hannah Mamuszka and Lena Chaihorsky interview entrepreneur Mark Cuban about why U.S. drug and healthcare prices are so high — and what he's building to counter them. Cuban walks through the drug supply chain: brand manufacturers sell to three dominant distributors, then pharmacy benefit managers (PBMs) — the three largest of which are owned by or own major insurers — use rebates to set formulary placement, which he argues drives list prices up and can block patients from the drugs their doctors prescribe. He describes the gap between a drug's list price and its much lower "net" price after confidential rebates, and argues that opacity and confidentiality clauses keep even self-insured employers from knowing what they actually pay. His prescription: transparency and direct contracting ("if you can schedule it, you can negotiate it"), plus his ventures — Cost Plus Drugs (cost + 15% markup), Cost Plus Wellness, a Dallas plant making shortage drugs, and a proposed bank-account-based alternative to insurance (the "10 plan"). He also urges employers to run their contracts through AI tools to spot unfavorable terms. Key takeaways The drug-pricing problem is structural: three big distributors, three big PBMs vertically integrated with the three big insurers, and rebate-driven formulary placement that Cuban argues rewards high list prices over patient affordability. List price ≠ net price: confidential rebates create a large gross-to-net gap, and confidentiality clauses keep even self-insured employers (who bear the cost) from seeing real prices. Cuban's counter-model is transparency plus direct contracting — buying care and drugs at negotiated/Medicare-referenced rates rather than through opaque insurer/PBM arrangements. Practical tip he offers employers: feed carrier and PBM contracts into an AI tool to flag undefined terms and unfavorable clauses. Relevant links FTC interim staff report on PBMs (market concentration, vertical integration): https://www.ftc.gov/system/files/ftc_gov/pdf/pharmacy-benefit-managers-staff-report.pdf KFF 2025 Employer Health Benefits Survey (self-funded plan share): https://www.kff.org/health-costs/2025-employer-health-benefits-survey/ CVS Caremark's Zepbound → Wegovy formulary change (Mass.gov notice): https://www.mass.gov/news/cvs-caremark-decides-to-remove-zepbound-from-cvs-caremark-formulary Mark Cuban’s Cost Plus Drugs (15% markup, Dallas manufacturing): https://www.markcubancostplusdrugcompany.com/ FDA GDUFA generic drug (ANDA) fee rates: https://www.fda.gov/industry/fda-user-fee-programs/generic-drug-user-fee-amendments KFF on ACA Marketplace deductibles: https://www.kff.org/affordable-care-act/what-we-know-so-far-about-2026-aca-marketplace-enrollment-premiums-and-deductibles/

The Rebate Shell Game and a Different Kind of PBM, with Greg Baker, CEO of Affirmed

Episode 6 — Greg Baker (AffirmedRx): The Rebate Shell Game and a Different Kind of PBM Hannah Mamuszka and Lena Chaihorsky interview Greg Baker, founder and CEO of AffirmedRx, a pharmacy benefit manager structured as a public benefit corporation which was recently named No.5 on the Inc. 5000. Baker, a pharmacist who spent years running on-site pharmacies for large employers, argues the drug-pricing system isn't broken but "working as designed" to maximize shareholder profit. He explains how the dominant PBMs make money as a percentage of drug cost, creating an incentive to favor expensive, highly rebated brands over cheaper generics, and how manufacturers must compete on rebate size for formulary placement, using Humira and Enbrel as his example. He describes what he calls a rebate "shell game," in which PBMs route rebates through offshore group purchasing organizations (Express Scripts' Ascent, in Switzerland) to obscure how much they keep. AffirmedRx, he says, charges a flat per-claim fee, passes rebates through fully, and caps executive pay. He points to recent ERISA lawsuits against employers (J&J, Wells Fargo, JPMorgan) as a turning point. A closing segment covers pharmacogenomics: why a person's metabolism affects whether a drug works, and how a cheek-swab test could reduce trial-and-error prescribing. Key takeaways AffirmedRx is a public benefit corporation charging a flat per-claim fee (not a percentage of drug cost), who says its incentives align with clients rather than favoring expensive, highly rebated drugs. The core mechanism Baker targets is rebates: manufacturers compete on rebate size for formulary placement, which he argues pushes list prices up and can force patients to switch drugs for financial rather than clinical reasons. Transparency is the throughline: Baker describes offshore rebate-aggregator GPOs (like Express Scripts' Ascent) as designed to obscure how much money PBMs keep, and urges employers to demand drug-level rebate data. Pharmacogenomics matter in many diseases, including mental-health, pain, and ADHD drugs, where using genetics to determine metabolism of drugs shorten trial-and-error. Relevant links AffirmedRx (public benefit corporation PBM): https://affirmedrx.com/ FTC settlement with Express Scripts referencing its Switzerland GPO "Ascent": https://www.ftc.gov/news-events/news/press-releases/2026/02/ftc-secures-landmark-settlement-express-scripts-lower-drug-costs-american-patients ERISA drug-benefit fiduciary lawsuits (J&J, Wells Fargo, JPMorgan) overview — Jones Day: https://www.jonesday.com/en/insights/2026/05/rising-scrutiny-of-employer-health-plan-administration-erisa-fiduciary-litigation-federal-transparency-initiatives-state Gallagher / Osceola County settlement over undisclosed commissions: https://floridapolitics.com/archives/589098-osceola-schools-settle-lawsuit-over-insurance-consultants-secret-commissions/

The Price of Drugs Is Only Half the Problem

Hannah Mamuszka and Lena Chaihorsky take on the drug pricing debate from the patient's side, where the question is not what a drug costs but whether it works for the person taking it. Chaihorsky frames it with a metaphor that runs through the episode: we argue endlessly over the price of milk while ignoring that the whole family is lactose intolerant. Mamuszka tells a story that shaped her career. As a young scientist at a small pharma company, she spent years developing a biomarker for a drug at the FDA's suggestion, only for the agency to drop the requirement and for her CEO, at the launch party, to explain that they would treat every patient the label allowed because there were investors to repay. The drug worked in roughly 38% of patients and caused serious side effects in about 40%, and the biomarker could tell those groups apart. They trace how that logic became structural, including the FDA's early-2000s move toward companion diagnostics for all targeted therapies, which collapsed under industry pushback. Chaihorsky then walks through the economics that decide which drugs patients can get when no biomarker stands in the way: PBM formularies rank-ordered by rebate rather than by mechanism of action, step therapy, and a pharmacy-versus-medical budget split that leaves no one owning the cost of being wrong. Their closing asks are simple. Patients should ask how their doctor knows a drug will work for them. Employers heading into benefits season should ask who their PBM is and what its contract rewards. Key takeaways The price of the drug is only half the conversation, whether it works is the other. Response rates are far lower than most people assume. Schork's 2015 Nature analysis found the ten highest-grossing US drugs help between 1 in 25 and 1 in 4 of the people who take them. Nothing rewards a higher response rate. A drug's price is the same whether it works in 15% of patients or 80%. PBMs are paid on rebates rather than net cost, so formularies are rank-ordered by what pays best rather than by who is likely to respond. Using biomarkers to predict response would break that model, which is a reason to expect resistance rather than a reason it doesn't work. Pharmacy and medical spend sit in separate budgets, so a wasted prescription and the hospitalization it causes are never added together, and nobody is accountable for the total. The question for patients: how do you know this drug will work for me? The question for employers: who is our PBM, and is our formulary built on rebates or on evidence? Relevant links Schork NJ, "Personalized medicine: Time for one-person trials," Nature 2015;520(7549):609–611 — the source of the "1 in 25 to 1 in 4" figure and the imprecision-medicine graphic Lena describes: https://www.nature.com/articles/520609a FTC interim staff report on pharmacy benefit managers (July 2024) — the top three PBMs processed nearly 80% of the ~6.6 billion US prescriptions dispensed in 2023: https://www.ftc.gov/news-events/news/press-releases/2024/07/ftc-releases-interim-staff-report-prescription-drug-middlemen Substack, "The Price of Drugs Is Only Half the Problem": https://hannahmamuszka.substack.com/p/the-price-of-drugs-is-only-half-the?r=4n5pb&utm_campaign=post-expanded-share&utm_medium=web

Ending Trial-and-Error Medicine

Hannah Mamuszka and Lena Chaihorsky interview Kristine Ashcraft, a molecular biologist who has worked in pharmacogenomics (PGx) since 2000, first at Genelex, one of the earliest labs to offer the testing, and later as founder of the clinical-decision-support tool YouScript. Ashcraft traces the field's slow adoption despite strong evidence, explaining how most people carry gene variants affecting how they metabolize common drugs, using a "liver highway" analogy: some people have fewer or more "lanes" (enzyme activity), and drugs, foods, and other medications can shut lanes down. YouScript's clinical studies showed large reductions in hospitalizations, ER visits, and deaths, and the European PREPARE trial's 30% drop in adverse drug reactions. A recurring theme is misaligned incentives — she describes a hospital CFO explaining they make money from the very hospitalizations that PGx would prevent. The conversation covers the Right Drug Dose Now Act, DPYD testing in oncology (where the wrong genotype plus a common chemo drug can be fatal), and practical advice: get tested once, log dangerous drugs as "allergies" so they follow you, and advocate for yourself. Key takeaways Pharmacogenomic variation is nearly universal; most people carry at least one clinically actionable variant affecting how they process common drugs, and yet testing still isn't routine, largely because of misaligned financial incentives and gaps in clinician education. The evidence base is strong: PGx-guided prescribing has produced large reductions in hospitalizations, ER visits, and adverse drug reactions in both U.S. studies and the multi-country European PREPARE trial. Some drug-gene interactions are life-or-death: DPYD testing before 5-FU/capecitabine chemotherapy, now backed by FDA boxed warnings and NCCN guidelines, can prevent fatal toxicity. Practical self-advocacy: pharmacogenomic testing is a one-time, low-cost test; logging a dangerous drug-gene result as an "allergy" helps it travel across fragmented medical records. Relevant links PREPARE study — 12-gene panel, 30% reduction in adverse drug reactions (The Lancet, 2023): https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(22)01841-4/abstract YouScript home-health RCT (52% fewer readmissions, 85% mortality reduction), PLOS ONE: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5289536/ CPIC guideline for CYP2D6/CYP2C19 and SSRIs (citalopram/escitalopram dosing): https://pmc.ncbi.nlm.nih.gov/articles/PMC4512908/ FDA codeine boxed warning (ultrarapid CYP2D6 metabolism): https://www.ncbi.nlm.nih.gov/books/NBK100662/ NCCN/FDA DPYD testing before fluoropyrimidine chemotherapy: https://www.fda.gov/drugs/resources-information-approved-drugs/safety-labeling-update-capecitabine-and-fluorouracil-5-fu-risks-associated-dihydropyrimidine Right Drug Dose Now Act (H.R. 2471, 119th Congress): https://www.congress.gov/bill/119th-congress/house-bill/2471/text

Diagnostics are the GPS of the Healthcare System We Refuse to Use

Hannah Mamuszka and Lena Chaihorsky make the case that diagnostics — not just drugs — are the key to controlling healthcare spending, and that the U.S. systematically underuses them. They lay the groundwork for the series: primary diagnosis (what's actually causing your symptoms), the "diagnosis of exclusion" trap, and two kinds of tests that determine whether a prescribed drug will work for you — pharmacogenomic tests (how your genes affect drug metabolism) and response-predicting diagnostics (whether you'll respond at all). The recurring villain is economics: insurers balk at a $200 test to protect a $10 prescription, ignoring the clinical and downstream costs; physicians skip testing to spare patients surprise bills; and because most drugs work in only a minority of patients, the resulting churn is profitable. They argue this is why response-predicting tests in areas like rheumatoid arthritis exist but aren't covered — using them would upend rebate-driven formularies. The through-line: we'll pay almost anything for a drug, but won't pay to find out if it will work. Their closing prompt for listeners: ask your doctor how they know this drug is right for you. Key takeaways Diagnostics are the "GPS" of care: without an accurate diagnosis and the right tests, treatment becomes expensive trial-and-error — yet the U.S. spends a small fraction on diagnostics relative to drugs. Two kinds of tests can tell you whether a drug will work before you take it: pharmacogenomic tests (how your body metabolizes a drug) and response-predicting tests (whether you'll respond at all). The economics are backwards: a cheap test that prevents a wrong prescription is often refused because the savings and harms are downstream, while the churn of failed prescriptions is profitable. The patient's question — for any new prescription — should be: "How do you know this drug is right for me, and is there a test that would tell us?" Relevant links Check to see if your drug has a pharmacogenomic test associated with prescription: https://www.clinpgx.org/ Diagnostic errors in the U.S. — overall error rate and harms (NIH/National Academies review): https://www.ncbi.nlm.nih.gov/books/NBK588113/ How effective are common medications — realistic drug-efficacy meta-analyses (BMC Medicine): https://link.springer.com/article/10.1186/s12916-015-0494-1 Genetic determinants of warfarin dose (VKORC1, CYP2C9) — PLOS Genetics: https://journals.plos.org/plosgenetics/article?id=10.1371%2Fjournal.pgen.1000433 Inadequate response to first-line anti-TNF therapy in RA (~30–40%): https://journals.sagepub.com/doi/10.1177/1759720X221114101 FDA approval standards and the absence of comparative-effectiveness requirements (NEJM): https://www.nejm.org/doi/full/10.1056/NEJMp0906490

Why We're Doing This: The Financial Misincentives Behind U.S. Healthcare

In the debut episode of Dirty Little Secrets, Hannah Mamuszka and Lena Chaihorsky introduce themselves and the podcast's central thesis: that the U.S. healthcare system is built on financial incentives that reward treatment over prevention and volume over value, systematically blocking patients from the best data-driven care. Mamuszka, a molecular biologist who moved from cancer drug development into diagnostics, and Chaihorsky, who came to the field through math and finance, each recount early-career moments when validated science was undervalued by the payment system — a high-risk-pregnancy test reimbursed at $11, and a urine test that could spare men unnecessary prostate biopsies but was resisted by urologists whose income depended on the procedure. They argue that patients meet the system at their most vulnerable, unable to shop as empowered consumers, and that misaligned incentives — including the ACA's medical loss ratio, which they contend removes insurers' incentive to cut costs — keep prices climbing. Citing research that rising premiums have eroded decades of middle-class wage gains, they make the case for a more consumer-driven, data-personalized system and invite listeners to start asking harder questions. Key takeaways The podcast's throughline: U.S. healthcare pays generously for treatment (surgery, drugs, hospitalizations) but poorly for the information — diagnostics, screening, risk data — that would let patients be treated as individuals rather than averages. Fee-for-service can create perverse incentives: the hosts describe a validated test that could reduce unnecessary prostate biopsies going unused because biopsies are a revenue source — a systems problem, not a critique of individual doctors. The ACA's medical loss ratio (insurers must spend 80–85% of premiums on care) is framed as a misincentive: since profit is a slice of a bigger pie, there's little reward for lowering total costs. Rising premiums have quietly consumed middle-class wage growth, which the hosts argue should reframe healthcare from an abstract cost into a personal, paycheck-level issue. Relevant links ACA Medical Loss Ratio and rebates — CMS: https://www.cms.gov/marketplace/private-health-insurance/medical-loss-ratio "A Decade of Health Care Cost Growth Has Wiped Out Real Income Gains for an Average US Family" (Auerbach & Kellermann, Health Affairs 2011): https://www.healthaffairs.org/doi/10.1377/hlthaff.2011.0585 Employer premium growth and wage stagnation/earnings inequality (JAMA, 2024): https://pmc.ncbi.nlm.nih.gov/articles/PMC10792464/ Exo mdx urine test to help men avoid prostate biopsy (Harvard Health): https://mdxhealth.com/exo-mdx-for-physicians/ "Unintended Consequences of the ACA's Medical Loss Ratio Requirement" (Health Affairs Forefront): https://www.healthaffairs.org/content/forefront/unintended-consequences-aca-s-medical-loss-ratio-requirement

Mad is not a strategy: The CPA who makes the case pharmacogenomics

Hannah Mamuszka and Lena Chaihorsky talk with Jane Cheshire Gilbert, a CPA who spent two decades running the health plan for the Teachers' Retirement System of Kentucky (TRS) and became an unlikely pioneer in pharmacogenomics. Serving tens of thousands of retired teachers — many in their 80s and 90s, on an average of 15 medications — Gilbert treated genetic testing not as a clinical curiosity but as a fiduciary tool: if a plan is paying full price for a blood thinner or antidepressant a member's body can't use, everyone loses. She recounts building a program with Coriell Life Sciences and the Know Your Rx Coalition, testing roughly a third of the Medicare-eligible population, and a published study showing meaningful per-member savings and fewer hospitalizations. The conversation is candid about the rebate machine (which she used dollar-for-dollar to hold premiums down), why insurers wouldn't pay for testing that saved them money, and her prescription for the next generation of purchasers: end direct-to-consumer drug advertising, require comparative-effectiveness research, and make real prices visible through reference-based pricing. Her closing line summarizes the whole show: "Mad is not a strategy." Key takeaways A fixed-budget purchaser has nowhere to hide costs, which is exactly why pharmacogenomics made sense here: paying full price for a drug a member's genetics won't let them use is pure waste, clinically and financially. The program has real evidence behind it — a published study of the TRS/Coriell program documented significant per-member savings and reduced hospitalizations across thousands of Medicare-eligible retirees. The incentives are backwards: the insurer that captured most of the savings wouldn't pay for the testing that produced them, because under a fully insured arrangement those savings were its margin. Gilbert's three systemic fixes — ending direct-to-consumer drug ads, requiring drug-vs-drug (not drug-vs-placebo) comparative-effectiveness research, and reference-based pricing tied to Medicare — are areas where purchasers across the political spectrum tend to agree. Relevant links Published study of the TRS Kentucky PGx + medication-management program (Journal of Personalized Medicine, 2022): https://www.mdpi.com/2075-4426/12/3/421 Coriell Life Sciences' TRS Kentucky case study: https://www.coriell.com/resources/trs/ Clopidogrel (Plavix) and CYP2C19 genotype — NIH Medical Genetics Summaries: https://www.ncbi.nlm.nih.gov/books/NBK84114/ CPIC clopidogrel/CYP2C19 guideline (2022 update): https://ascpt.onlinelibrary.wiley.com/doi/10.1002/cpt.2526 Direct-to-consumer drug advertising — U.S. and New Zealand only (USC Schaeffer): https://schaeffer.usc.edu/research/should-the-government-restrict-direct-to-consumer-prescription-drug-advertising-six-takeaways-from-research-on-the-effects-of-prescription-drug-advertising/