JAMA IM // Op Ed and Research Note on AI in Clinical Decision Support

 

1.  Consolidated AI review.

2. Op Ed abridgement.

3. Research Note abridgement.

4.  Louis Black Essay.

250 WORD AI NOTE ABOUT BOTH PIECES

(249 words, 250 requested)

The intersection of artificial intelligence (AI) and healthcare has ushered in a new era of computerized clinical decision support (CDS) tools. In an op-ed, concerns are raised about the FDA's regulation of AI/ML-driven CDS devices in critical care. The op-ed argues that the current regulatory framework is inadequate, as evidenced by a case series examining the authorization of 10 such devices. Alarmingly, only two of these devices cited peer-reviewed publications, and just one outlined safety risks. Furthermore, none provided their software code for independent validation, evaluated clinical efficacy, or assessed potential biases. This lack of transparency and evidence raises serious questions about the reliability and safety of AI/ML CDS devices. The op-ed calls for greater transparency in algorithms, rigorous preapproval studies, and a focus on mitigating biases, urging urgent reforms in FDA guidance and enforcement.

In a related research note, the study delves deeper into the authorization of AI/ML CDS devices, focusing on critical care. The study identifies 10 such devices out of 521 in the FDA's database. 

It finds that most of these devices were authorized through the 510(k) pathway, which does not require clinical data submission. Clinical evidence varied, from absent to peer-reviewed assessments, and few devices mentioned safety evaluations or AI/ML predicates. Notably, a widely implemented model lacked FDA authorization. The research note underscores the need to update regulatory requirements to align with current AI/ML practices in healthcare.

Together, these pieces highlight the urgent necessity for regulatory reforms in the AI/ML-driven CDS device landscape. Transparency, rigorous evaluation, and bias mitigation should be prioritized to ensure the safety and efficacy of these technologies, particularly in high-stakes critical care scenarios. Failure to address these issues may jeopardize patient care and exacerbate healthcare disparities.

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OP ED - WEISSMAN, PENN (AI SUMMARY)

https://jamanetwork.com/journals/jamainternalmedicine/fullarticle/2810620

The op-ed discusses the emerging era of computerized clinical decision support (CDS) tools, particularly those incorporating artificial intelligence and machine learning (AI/ML). It highlights a case series by Lee and colleagues, which examined the FDA approval process for 10 AI/ML CDS devices designed for critical care.

The key findings of concern are as follows:

• Lack of Transparency: Most companies did not disclose the algorithms, programming code, or data sets behind their AI/ML CDS devices, creating a "black box" problem where users cannot assess how the system works.
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• Insufficient Evidence: Only a few device authorizations cited peer-reviewed publications, and just one provided a detailed safety risk assessment. There is a dearth of high-quality evidence supporting the validity, safety, and efficacy of these devices.
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• 510(k) Pathway Eligibility: Some devices were approved through the 510(k) pathway despite differences from their predicates, which raises questions about the appropriateness of this regulatory pathway for AI/ML CDS devices.
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• Bias Evaluation: The FDA should scrutinize these devices for potential biases, especially those derived from data that lack diversity or perpetuate existing healthcare disparities.

The op-ed calls for urgent reforms in the regulation of AI/ML-driven CDS devices. It recommends greater transparency in algorithms, rigorous preapproval studies, postmarketing surveillance, reconsideration of the 510(k) pathway, and a focus on mitigating biases. Without these changes, it suggests that healthcare professionals and institutions should exercise caution when using these devices for critical decisions.

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RESEARCH LETTER   - GROSS, YALE (*AI SUMMARY)

https://jamanetwork.com/journals/jamainternalmedicine/fullarticle/2810619

This JAMA research note discusses the regulatory landscape and evidence behind clinical decision support (CDS) devices that use machine learning (ML) or artificial intelligence (AI) in the critical care setting. Here's a summary of the key points:

• The use of predictive CDS devices with AI or ML has the potential to improve critical care outcomes, but there is a lack of a clear regulatory framework.
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• Recent guidance from the FDA indicates that most CDS tools for critical illness will be regulated due to the urgency of the decisions they inform. However, concerns exist regarding the effectiveness and safety of current regulatory frameworks designed before advanced statistical learning methods became widely available.
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• The study examined data from the FDA's AI and ML database as of December 15, 2022, to identify devices offering CDS in critical care and assess the evidence provided for their authorization.
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• Among 521 authorizations in the FDA AI/ML database, only 10 devices were relevant to critical care. Most of these devices were authorized through the 510(k) pathway, which does not require submission of clinical data, and few mentioned safety assessments or published data.
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• None of the devices mentioned an evaluation of performance bias, and only three devices had AI/ML predicates.
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• Notably, a high-profile sepsis-focused prediction model that could serve as a CDS device did not appear to have FDA authorization.
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• The study emphasizes the need to update regulatory requirements to align with the current use of AI/ML systems in various clinical practice settings, especially for high-risk decisions in critical care.
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• One limitation of the study is that it does not account for FDA approvals through recently ended precertification pilot pathways or for other devices in widespread use not present in the FDA database.

In summary, the research note highlights the challenges in regulating AI/ML-based CDS devices in critical care and calls for updating regulatory requirements to ensure their safety and effectiveness.

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REVIEW THE ABOVE BY LOUIS BLACK

Write an essay in the satirical voice of Louis Black, harpooning the two articles (Op Ed and Reserach Note) and portraying the authors as Nervous Nellies.

ChatGPT

Ladies and gentlemen, gather 'round! It's time for a satirical rollercoaster ride through the land of Nervous Nellies and their newfound fear of artificial intelligence and machine learning in healthcare. You see, we've got an op-ed and a research note that read like the script of a "Chicken Little" reboot. Let's dive in!

First, we have this op-ed that paints a gloomy picture of AI/ML-driven clinical decision support (CDS) tools. According to these authors, we're entering a dystopian era where AI/ML might actually help doctors make better decisions! Shocking, I know. They wring their hands over a lack of "algorithmic transparency" and "evidentiary standards." Well, let me tell you, folks, transparency is overrated. Who needs to understand how these magical algorithms work when we've got doctors who can barely explain our lab results in plain English?

And don't get me started on the "bias evaluation" they're clamoring for. Apparently, AI/ML might pick up some bad habits from its human creators. Who cares if it inadvertently exacerbates biases? It's not like our healthcare system has ever been a shining example of fairness and equality.

Then we've got this research note, where they cherry-pick a few AI/ML devices and make it sound like they're about to unleash the robot apocalypse. They quiver in fear that some devices don't have enough "clinical evidence" or that they're not similar enough to their older, less advanced counterparts. But let's face it, if the older devices were so great, we wouldn't need these newfangled AI tools in the first place.

These Nervous Nellies want to slow down innovation and keep us stuck in the dark ages of medicine. Well, I say, let's embrace the future! AI and ML have the potential to revolutionize healthcare, making diagnoses faster, more accurate, and accessible to all. So, to the authors of these articles, I say, "Take a chill pill and let the robots help us out. The sky isn't falling, but your sense of humor sure is!"