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Healthcare analytics built on structured data alone miss almost 40% of documented diagnoses
HEDIS rates from claims alone ran 20 points below chart-reviewed rates, Medicare claims found 2% smokers where the survey found 10%, and only 3% of…
Sep 12
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David Talby
18
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Fact-level provenance in healthcare AI: the 42 capabilities behind an FDA-ready clinical data platform
The FDA’s December 2025 real-world evidence guidance requires provenance and accuracy at a per-fact level. Here is the full capability inventory, the…
Sep 5
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David Talby
19
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There is no partial credit in de-identification
New privacy tools score between 0.55 and 0.91 PHI F1 on clinical notes; a purpose-built pipeline holds 0.98 recall, above the two-expert consensus line…
Sep 1
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David Talby
24
1
Benchmarking AI impersonation of licensed professionals: 11 laws and 380 adversarial tests
A new red-team benchmark measures whether frontier models impersonate doctors, lawyers, and financial advisors, and whether they disclose being AI…
Aug 8
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David Talby
58
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The cognitive bias problem LLMs inherited from doctors
Take a clinical note about a 52-year-old with chest pain, and ask a frontier model what to do.
Aug 1
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David Talby
84
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A cost model for patient-level healthcare AI: $1M for locally deployed Medical LLM vs. $13M to $30M via frontier APIs
Jun 20
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David Talby
385
4
Three Healthcare AI Frameworks, one governance backbone: RUAIH, URAC, and CHAI
Jul 2
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David Talby
32
2
The cognitive bias problem LLMs inherited from doctors
Aug 1
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David Talby
84
3
4
Small, Private, and First on All Fifteen: The New Medical LLM Benchmark Results
Jul 25
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David Talby
52
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Small, Private, and First on All Fifteen: The New Medical LLM Benchmark Results
First on all 15 clinical and biomedical benchmarks, averaging 80.9 against the newest frontier releases, running on a single GPU inside your own…
Jul 25
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David Talby
52
2
What we learned building Medical LLMs that academic medical centers trust
Originally published alongside the 2025 InfoWorld Technology of the Year Award announcement, December 2025.
Jul 15
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David Talby
1
When the Title Outruns the Study: General-Purpose vs. Healthcare-Specific AI
A Brief Communication in Nature Medicine made the rounds last month under a headline that is hard to misread: “General-purpose large language models…
Jul 12
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David Talby
36
The case for bringing HCC coding in-house: what generative AI changes about the outsourcing math
Originally published in Health IT Answers and MedCity News, November 2025.
Jul 10
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David Talby
3
Three Healthcare AI Frameworks, one governance backbone: RUAIH, URAC, and CHAI
U.S. healthcare now has two AI certifications and a set of governance playbooks, but they all rest on one backbone you must sustain.
Jul 2
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David Talby
32
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The real AI governance gap isn’t missing regulation. It’s missing literacy.
Originally published in CIO, October 2025.
Jul 1
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David Talby
1
A cost model for patient-level healthcare AI: $1M for locally deployed Medical LLM vs. $13M to $30M via frontier APIs
Healthcare AI budgets break on one assumption: that per-token API pricing works at patient-population scale.
Jun 20
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David Talby
385
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Why cancer registries stay years out of date - and what regulatory-grade oncology AI changes
Originally published in Forbes, July 2025.
Jun 18
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David Talby
1
Why the 2026 Medicare Advantage rate decision raises the bar on HCC coding accuracy
Originally published in MedCity News, Rama on Healthcare, and Gene Online — June 2025.
Jun 13
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David Talby
2
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