Our Bodies, Our Data
How Companies Make Billions Selling Our Medical Records
『Our Bodies, Our Data』の概要
Your medical data is being sold without your consent. "Our Bodies, Our Data" exposes the $67 billion industry trading patient records. Duke University's Dr. Washington calls it "vital" reading, revealing how pharmacies, insurers, and data brokers profit from your most intimate health secrets.
『Our Bodies, Our Data』の主要テーマ
- medical data mining
- patient privacy rights
- healthcare commercialization
- anonymized data brokerage
- pharmaceutical market intelligence
『Our Bodies, Our Data』の名言
We do not share this kind of information externally.
Pretty much everyone...has some sort of supply arrangement.
Patients came to my pharmacy.
HIPAA's scope is also limited to 'covered entities'.
IMS has historically shunned public attention.
『Our Bodies, Our Data』の登場人物
- Adam TannerAuthor and investigative journalist
- Deborah PeelPsychiatrist and patient privacy advocate
- Ray GosselinFounder of the National Prescription Audit
- Fritz KriegerEntrepreneur who monetized medical data streams
- Tery BaskinPharmacist who discovered unauthorized data sales
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この本に関するよくある質問
Our Bodies, Our Data exposes the multi-billion-dollar trade in anonymized medical records, prescriptions, and insurance claims sold by data brokers to pharmaceutical companies, insurers, and marketers. Adam Tanner investigates how this hidden industry prioritizes profit over patient privacy, highlighting risks of re-identification and the lack of comprehensive health records for actual care.
This book is essential for healthcare professionals, policymakers, privacy advocates, and anyone concerned about data ethics. It offers critical insights for patients seeking to understand how their medical information is commercialized without consent.
Yes—Tanner’s investigative rigor and clear storytelling make it a landmark work on medical privacy. It sheds light on systemic exploitation in healthcare data markets, offering a compelling case for regulatory reform.
Hospitals, pharmacies, and insurers sell anonymized records to data brokers like IMS Health (now IQVIA), which aggregate billions of patient profiles. These dossiers—stripped of names but retaining identifiers like birth year and doctor details—are monetized for drug marketing and research.
Advanced algorithms can cross-reference anonymized data with public records to reveal identities, exposing patients to discrimination, insurance denial, or employment issues. Tanner warns that purported “anonymization” often fails to protect privacy.
Tanner argues that while corporations profit from patient data, individuals struggle to access unified health records. This paradox undermines care quality while enabling unchecked commercial exploitation.
The book advocates for patient ownership of health data, transparency in data sales, and stricter regulations akin to European GDPR. Tanner emphasizes empowering individuals to control how their information is shared.
While What Stays in Vegas explores broader data commercialization, Our Bodies, Our Data focuses specifically on healthcare. Both reveal systemic privacy failures, but the latter highlights life-and-death implications of medical data misuse.
Some critics note the technical complexity of data anonymization topics, which may challenge casual readers. However, the book is widely praised for its rigor and urgency in addressing underreported privacy violations.
With AI accelerating data analysis, re-identification risks have grown since the book’s publication. Its warnings remain critical as healthcare AI and personalized medicine expand reliance on patient data.
Tanner details how brokers like IQVIA and Symphony Health operate as middlemen, compiling dossiers on 500+ million patients globally. These firms prioritize pharmaceutical marketing over scientific research, per internal industry documents.
The book critiques the tension between data’s potential for medical advancement and its misuse for profit. Tanner calls for ethical guidelines to ensure patient consent and equitable benefits from data use.
