Tag: openai

ChatGPT for Healthcare, Now Available in Epic

Posted on by Jason Barry

The day has finally come. OpenAI just integrated ChatGPT directly into Epic, and the doomsayers were out in full force predicting the instant demise of thousands of startups. 

Here’s what happened (and what didn’t). ChatGPT for Healthcare can now synthesize notes, labs, meds, and specialist documentation to answer questions for clinicians – either by bringing chart context into ChatGPT, or by running ChatGPT in the chart itself.

  • That means that clinicians can easily summarize charts, review labs, and prep for visits without leaving the EHR. Good stuff, not earthshattering.
  • That doesn’t mean that Epic suddenly gave OpenAI access to its 325M patient records, or that ChatGPT can start updating patient records. The connection is “currently” read-only, so nothing’s getting written to the record… yet.

OpenAI didn’t stop there. A new Healthcare Public Data plugin adds structured connectors to nine official sources – including ClinicalTrials.gov, CMS Coverage, DailyMed, and PubMed – for verifying precise information like trial eligibility criteria and coverage policy versions.

  • In early testing on 4,300 responses across 27 clinical use cases, physicians rated 99.1% of the responses as safe. That was apparently good enough for UCSF to sign on as the pilot partner.

The timing talks. Epic spent UGM positioning Ergo as its intelligence layer that sits on top of the chart. Two weeks later, OpenAI began offering its own insights inside that same chart.

  • Agent Factory was also in the UGM spotlight, with 120 AI features slated for wide availability in 2027. Those features definitely aren’t all read-only.
  • Epic still hasn’t said a single word about the OpenAI partnership. 

The peanut gallery talks louder. The thing that most people seem to agree on is that every startup pitching “AI that plugs into your EHR and saves clinicians time” just got steamrolled.

  • Where’s that leave us? “You have to go really clinical.” A model that reads a chart isn’t a workflow-specific product that can act on one. It’s time to specialize and make things happen.

The Takeaway

OpenAI and Epic just officially made chart summaries a commodity. That isn’t the end of thousands of startups, but it will be if they don’t roll up their sleeves.

OpenAI o1 Outperforms Physicians on Clinical Reasoning Tasks

Posted on by Jason Barry

A landmark study in Science found that OpenAI’s o1 series outperformed human physicians at multiple clinical reasoning tasks, but that doesn’t mean it’s time to hang up the scrubs just yet.

Researchers at Harvard and Beth Israel Deaconess Medical Center designed the study to evaluate whether LLMs are ready to do what physicians do on a daily basis: review messy patient charts and use that data to determine diagnosis and next steps.

  • They evaluated o1 on clinical cases ranging from patient vignettes to second opinions on 76 real-world ED assessments, which included all the noise and incomplete information that clinicians routinely encounter in the EHR.
  • The refreshingly well-designed study also incorporated a blinded evaluation with two attending physicians at BIDMC and GPT-4.

o1 came to play. On clinical vignettes evaluating management reasoning, o1-preview scored a median of 86%. Not too shabby.

  • It outperformed GPT-4, humans with GPT-4, and humans with conventional resources like UpToDate – all of which scored below 45%.

The ED cases were even more impressive. o1 offered second opinions about the diagnosis at three points along the patient’s ED journey:

  • At triage, o1 gave an exact or very close diagnosis in 67% of cases (when information in the record dump was most limited). The two physicians hit 55% and 50%. 
  • o1 still outperformed the physicians when given all the data collected by the end of the ED encounter.
  • It was only when the physicians were given the most information possible to inform their diagnosis – at the time the patient would have been admitted to the hospital – that the scores finally converged.

The cherry on top? Physician raters couldn’t tell whether the differentials came from o1 or a human. One rater couldn’t tell in 83.6% of cases, the other in 94.4%. 

  • The authors were quick to mention that these results don’t mean AI is ready to replace human physicians. They mean it’s time for rigorous research into how AI can augment care teams, serve as a second opinion, and become a safety layer for clinicians.

The Takeaway

o1 outperforming a couple internists at triage isn’t quite Deep Blue beating Gary Kasparov at chess, but it’s a step in that direction – especially considering OpenAI’s performance jump in just the last week (let alone since o1 launched in 2024).

OpenAI Launches ChatGPT for Clinicians

Posted on by Jason Barry

OpenAI is doubling down on providers, and this time around it’s going direct-to-docs with ChatGPT for Clinicians.

ChatGPT-5.4, but for clinicians. OpenAI’s medically-tuned version of ChatGPT uses the same engine as GPT-5.4, with specialized training to optimize it for clinical workflows and administrative tasks.

  • Better yet, it’s free for any verified physician, NP, PA, or pharmacist in the U.S.

ChatGPT for Clinicians includes:

  • Access to GPT-5.4 and OpenAI’s other models (increased limits for clinical tasks).
  • Skills for repeatable workflows (like drafting referral letters and patient instructions).
  • Clinical search based on “millions of peer-reviewed sources” (details were sparse).
  • Optional support for HIPAA compliance (through a BAA for eligible accounts).

ChatGPT for Clinicians doesn’t include:

  • Connectors to the CMS Coverage Database, NPI Registry, or ICD-10. Not impossible.
  • Broader platform advantages like integrated drug information or telehealth.
  • Evidence from big name partners that’s contextualized to the encounter.
  • HIPAA compliance out-of-the-box.

All that said, the performance talks. ChatGPT for Clinicians was launched alongside HealthBench Professional, OpenAI’s new benchmark built from real clinical conversations.

  • It grades models on chat tasks across three use cases (care consults, documentation, and medical research), with physician-authored scenarios and rubrics, as well as scoring designed to reflect real-world performance.
  • As you might expect, OpenAI’s new tool did great on OpenAI’s new benchmark. ChatGPT for Clinicians outperformed Claude Opus 4.7, Gemini 3.1 Pro, and even specialty-matched physicians with unlimited time and web access.

What happened to ChatGPT for Healthcare? OpenAI launched ChatGPT for Healthcare just a few short months ago to help health systems with enterprise-wide deployments, but now it’s taking “the next step” by bringing ChatGPT straight to individual clinicians so that “AGI benefits all of humanity.”

The Takeaway

Whether OpenAI is pursuing an altruistic mission or hedging slow progress in the enterprise arena, millions of clinicians already use ChatGPT to support their care, and now they have a fine-tuned version that won’t break the bank.

Anthropic and OpenAI Set Sights on Providers

Posted on by Jason Barry

Digital health has some fresh competition. Less than a week after OpenAI launched ChatGPT Health, Anthropic crashed the party with the grand debut of Claude for Healthcare. 

Player 2 has entered the fight. Anthropic’s headlining feature for consumers is identical to ChatGPT Health – the answers are grounded in the patient’s own medical history.

  • Claude for Healthcare lets patients securely upload their health records and app data to unlock the same wide-ranging benefits as ChatGPT Health, such as spotting trends, preparing for visits, interpreting lab results… so on and so forth.
  • The two even share some overlapping partner apps like Function and Apple Health, but the similarities end there. 

Claude for Healthcare gets providers in on the action. Unlike OpenAI’s shiny new patient-facing solution, Claude for Healthcare comes with a suite of “Connectors” that enable it to support previously out-of-reach workflows. The list includes:

  • Prior auth reviews and coverage verifications [CMS Coverage Database]
  • Medical coding and billing accuracy [ICD-10]
  • Provider verification and credentialing [NPI Registry]

OpenAI hasn’t taken any days off. It followed up last week’s big ChatGPT Health news with the launch of ChatGPT for Healthcare – similar names, very different products.

  • ChatGPT for Healthcare is OpenAI’s enterprise solution to the Anthropic problem. It brings new provider-facing capabilities like care path management, referral letter generation, and clinical search (tough break for Doximity and Wolters Kluwer).

The fun doesn’t end there. OpenAI added to its hot streak by picking up Torch, a four-person startup building “a medical memory for AI.” The Information pinned the price tag at $100M. 

  • Torch feeds scattered records into a context engine that connects the dots between visit notes, lab results, wearable data, and any other medical info you can think of. 
  • That pitch rhymes perfectly with ChatGPT Health’s value prop, and the Torch team will now be helping boost the new solution’s medical memory across its inaugural cohort of partner apps.

The Takeaway

What a week for our little corner of the industry. OpenAI and Anthropic are diving in head first, and their tech, ambition, and pockets might even be deeper than the choppy legal waters.

OpenAI Jumps Into Healthcare Arena With ChatGPT Health

Posted on by Jason Barry

If OpenAI wasn’t already a major healthcare player, the launch of ChatGPT Health definitely just made it one.

It’s the gamechanger everyone saw coming. OpenAI even teed up the launch with a report showing that 40M people are already using ChatGPT for healthcare advice on a daily basis. 

ChatGPT Health is about to take that a massive step further. 

Here’s a look at the core features:

  • ChatGPT Health operates inside a dedicated health environment with additional privacy layers (conversations aren’t used for model training, optional two-factor authentication).
  • Users can securely upload their complete medical records (courtesy of b.well).
  • Users can connect apps to inform answers (Apple Health, Function, MyFitnessPal).
  • The model uses longitudinal health data, labs, and visit summaries to help spot trends.

OpenAI is moving beyond general health advice. The extra clinical context gives ChatGPT Health the ability to give better answers at scale, and that’s good news for patients.

A few of the most obvious benefits for patients include:

  • Empowering them to take a more active role in their care.
  • Helping them uncover trends in their overall health.
  • Reducing confusion around test results.
  • Reinforcing care plans between visits.
  • The list could go on for a while.

ChatGPT Health isn’t actually HIPAA compliant. Then again, it doesn’t need to be.

  • Consumer health apps like ChatGPT Health aren’t covered by HIPAA, and to OpenAI’s credit it appears to have done a great job with the necessary disclaimers.
  • The dedicated health environment was also developed with input from 260+ physicians, and it leverages a physician-authored framework for safety, clarity, and escalation.

The question now is, who’s accountable when things go wrong? Millions of patients are about to start showing up to visits armed with advice from ChatGPT Health, which means its AI fingerprints will be all over their questions, concerns, and even clinical decisions. The tech might be ready. The governance isn’t.

  • When ChatGPT Health mentions an unproven treatment and a patient follows through, or interprets a worrying lab value as benign, who carries the liability?
  • OpenAI? The physicians who authored the safety framework? The patient who followed the advice? It’s tough to say, but providers – and their patients – still need a clear answer.

The Takeaway

Everyone wants a doctor in their pocket, and ChatGPT Health just filled that role for millions of patients… even if OpenAI explicitly told them it wasn’t up for the job.

OpenAI Delivers Largest-Ever Study of Clinical AI

Posted on by Jason Barry

Hot on the heels of launching its HealthBench medical AI benchmark, OpenAI just delivered results from the largest-ever study of clinical AI in actual practice – and let’s just say the future’s looking bright.

40,000 visits, 106 clinicians, 15 clinics. OpenAI went big to get real-world data, equipping Kenya-based primary and urgent care provider Penda Health with AI Consult (GPT4o) clinical decision support within its EHR.

  • The study split 106 Penda clinicians into two even groups (half with AI Consult, half without), then tracked outcomes over a three month period. 

When AI Consult detected a potential error in history, diagnosis, or treatment, it triggered a simple Traffic Light alert.

  • Green – No concerns, no action needed
  • Yellow – Moderate concerns, optional clinician review 
  • Red – Safety-critical concerns, mandatory clinician review

The results were definitely promising. Clinicians using AI Consult saw a:

  • 16% reduction in diagnostic errors
  • 13% reduction in treatment errors
  • 32% reduction history-taking errors

The “training effect” is real. The AI Consult group got significantly better at avoiding common mistakes over time, triggering fewer alerts as the study progressed.

  • Part of that is because Penda took several steps to help along the way, including one-on-one training, peer champions, and performance feedback.
  • It’s also worth noting that there was no recorded harm as a result of AI Consult suggestions, and 100% of the clinicians using it said that it improved their quality of care.

What’s the catch? While AI Consult led to a clear reduction in clinical errors, there was no statistically significant difference in patient-reported outcomes, and clinicians using the copilot saw slightly longer visit times.

The Takeaway

Clinical AI continues to prove itself outside of multiple choice licensing exams / clinical vignettes, and OpenAI just gave us our best evidence yet that general-purpose models can reduce errors in actual patient care.

OpenAI Dives Into Healthcare With HealthBench

Posted on by Jason Barry

OpenAI is officially setting its sights on healthcare with the launch of HealthBench, a new benchmark for evaluating AI performance in realistic medical scenarios.

HealthBench marks the first time the ChatGPT developer has taken a direct step into the industry without a partner to hold its hand.

  • Developed with 262 physicians from 60 countries, HealthBench includes 5,000 simulated health conversations, each with a custom rubric to grade the responses.
  • The conversations “were created to be realistic and similar to real-world use of LLMs,” meaning they’re multi-turn and multilingual, while spanning a range of medical specialties and themes like handling uncertainty or global health.

Here’s how current frontier models stacked up in the HealthBench test.

  • OpenAI’s o3 was the best performing model with a score of 60%
  • xAI’s Grok 3 ranked second with a score of 54%
  • Google’s Gemini 2.5 Pro followed close behind at 52%

All three leading models outperformed physicians who weren’t equipped with AI, although physicians outperformed the newer models when they had access to the AI output.

  • The paper also reviewed other LLMs like Llama and Claude, but unsurprisingly none of them scored higher than OpenAI’s model on OpenAI’s own test.

Even the best models came up short in a few common places, AKA areas that developers should focus on to improve performance.

  • Current AI models would rather hallucinate than withhold an answer they aren’t confident on, obviously not a good trait to bring into a clinical setting.
  • None of the leading LLMs were great at asking for additional context or more information when the input was vague.
  • When AI misses, it misses bad, as seen in the sharp quality dropoff with the worst 10% of responses.

The Takeaway

Outside of giving us yet another datapoint that AI is catching up to human physicians, HealthBench provides one of the best standardized ways to compare model performance in (simulated) clinical practice, and that’s just what the innovation doctor ordered.

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