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Healthcare AI cannot deliver precision medicine without complete, interoperable medical records, which are essential for responsible AI implementation in healthcare. In this episode, recorded live at the Data First Conference in Las Vegas, Aleida Lanza, founder and CEO of Casedok, shares insights from her 35 years as a medical malpractice paralegal on why fragmented records and inaccessible data continue to undermine care quality, safety, and trust in healthcare AI.

We dive deep into why interoperability must extend beyond the core clinical record to include the full spectrum of healthcare data—images, itemized bills, claims history, and even records trapped in paper or PDFs. Aleida argues that patient ownership and transparency of their health information, a critical element of healthcare ethics, are key to overcoming these challenges and enabling ethical leadership in healthcare AI.

This episode also highlights the significant risks posed by missing data bias in healthcare AI, explaining how incomplete records prevent AI systems from accurately detecting patient needs. Aleida outlines how complete medical record transparency and safe AI collaboration can transform healthcare from static averages to truly personalized, informed care, aligning with principles of ethical AI and responsible AI deployment.

If you're involved in healthcare leadership, AI strategy, data governance, or healthcare ethics, this episode offers valuable perspectives on AI readiness, healthcare AI regulation, and the urgent need to improve interoperability for better patient outcomes.

Key topics covered

• Why interoperability must include the entire medical record
• Patient ownership, transparency, and access to health data
• The hidden cost of fragmented records and repeated history-taking
• Why static averages fail patients and clinicians
• Precision medicine vs static medicine
• Safe AI deployment without hallucination or data leakage
• Missing data as the most dangerous bias in healthcare AI
• Emergency access to complete history as a patient safety issue
• Medicare, payer integration, and large-scale access challenges

Chapters

00:00 Live from Data First Conference
01:20 Why interoperability is more than clinical data
03:40 Fragmentation, static medicine, and broken incentives
05:55 Why AI needs complete patient history
08:10 Missing data as invisible bias
10:55 Emergency care and inaccessible records
12:40 Patient ownership and transparency
14:30 Precision medicine and AI safety
16:10 Why patients should own what they paid for
18:30 How to connect with Aleida Lanza

Stay tuned. Stay curious. Stay human.

#HealthcareAI #Interoperability #PatientData

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