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Home Innovations & Investing

What is Data, Really?

Daily Remedy by Daily Remedy
May 8, 2024
in Innovations & Investing
0

There is pain, and there is pain’s shadow, a demarcation defined by philosopher C.S. Lewis when describing the impact pain has upon a person afflicted.

In this context, we explore the nuances of healthcare policy and modern medical practices that govern the treatment of diseases such as Alzheimer’s, revealing the complexities of medical regulations and patient care.

In much the same vein, we must look at disease and the presentation of disease as its shadow – as we would treatment and the presentation of treatment as its shadow. The two are inextricably linked, and the interaction between the two – disease and disease presentation, treatment and treatment effectiveness – defines the quality of care, as experienced by the patient.

When the FDA recently approved a drug to treat Alzheimer’s disease, the medical community reacted in outrage. The data evaluating the effectiveness of the drug never focused on any of the symptoms of the disease, which is diagnosed through the clinical presentation of the symptoms. Instead, the drug was approved based on its ability to reduce the concentration of a protein found in the brain of those afflicted with the condition, a decision that raised healthcare policy issues and questions about the policy & politics in nursing and healthcare.

Even the study never defined a direct relationship between protein concentration and symptomatic presentation. In fact, most Neurologists specializing in neurodegenerative, age-related disorders emphasize the clinical presentation over any test or lab – advocating for the use of testing and lab work only to confirm what is suspected upon clinical presentation.

This approach underscores the innovations in healthcare that respect both the empirical and experiential aspects of medical care, aiming towards an ideal healthcare system.

So then, what are we truly treating with this new drug?

Alzheimer’s is a clinical condition, defined symptomatically, diagnosed based upon the symptoms presented.

We do not diagnose nor treat a complex neurodegenerative disease through the imaging of a protein biomarker. We diagnose and treat through the clinical presentation of symptoms.

A disease is a disease based upon how it presents. And a treatment is a treatment based upon how it treats the presentation of the disease.

The relationship is fundamentally experiential. To discern the relationship through imaging or by any other means to violate the fundamental relationship between disease and treatment, and the respective shadows.

The FDA’s decision to approve the drug based upon imaging data demonstrates a staunch movement towards analytics and data driven medicine. The reaction by the medical community demonstrates that no matter how analytical or data driven healthcare becomes, it will always remain a fundamentally subjective discipline – as much art as science.

Data can glean relationships, reveal what is related, symptom to disease or disease to treatment. But data cannot understand the nuances of these relationships.

How things relate in healthcare is far more complicated than the information provided by data. If we presume data is the answer to the questions in medicine, then we will quickly realize that the answers cannot encapsulate the full scope of the questions.

The data behind the drug’s approval focused primarily on the concentration of the protein associated with Alzheimer’s disease and secondarily on the clinical presentation of the disease itself.

Reflect upon that – in a clinical study evaluating whether a drug should be approved for the treatment of a disease, the defining symptoms were not the primary endpoints of the study.

Instead the data simply assumed that by lowering the concentration of the protein, we automatically treat the condition, a gross simplification that conflates correlation with causation – in other words, an error of logic.

Yet this was the data that the FDA evaluated and based its approval upon.

A disturbing trend towards utilizing data as the primary means of diagnosis and treatment that the pandemic should have curbed, as it was a time when we recognized that the perception of the data matters more than the data itself.

That for patients, the perceptions of fear mattered more than the rationality of clinical care.

The data is only the data. The perceptions of care and the treatment of the patient are so much more.

To distill the effectiveness of treatment for a drug – the first to be approved for Alzheimer’s disease in twenty years – down to imaging data disregards the subtle nuances of clinical presentation that initially defined the disease and its treatment.

Medicine was an art before it was a science. Then it became both an art and science.

We should not let the science overwhelm the art. For without the art, we are left with only the science, the empty data.

What is data, really?

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Daily Remedy

Daily Remedy

Dr. Jay K Joshi serves as the editor-in-chief of Daily Remedy. He is a serial entrepreneur and sought after thought-leader for matters related to healthcare innovation and medical jurisprudence. He has published articles on a variety of healthcare topics in both peer-reviewed journals and trade publications. His legal writings include amicus curiae briefs prepared for prominent federal healthcare cases.

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Videos

In this episode, the host discusses the significance of large language models (LLMs) in healthcare, their applications, and the challenges they face. The conversation highlights the importance of simplicity in model design and the necessity of integrating patient feedback to enhance the effectiveness of LLMs in clinical settings.

Takeaways
LLMs are becoming integral in healthcare.
They can help determine costs and service options.
Hallucination in LLMs can lead to misinformation.
LLMs can produce inconsistent answers based on input.
Simplicity in LLMs is often more effective than complexity.
Patient behavior should guide LLM development.
Integrating patient feedback is crucial for accuracy.
Pre-training models with patient input enhances relevance.
Healthcare providers must understand LLM limitations.
The best LLMs will focus on patient-centered care.

Chapters

00:00 Introduction to LLMs in Healthcare
05:16 The Importance of Simplicity in LLMs
The Future of LLMs in HealthcareDaily Remedy
YouTube Video U1u-IYdpeEk
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AI Regulation and Deployment Is Now a Core Healthcare Issue

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Ambient Artificial Intelligence Clinical Documentation: Workflow Support with Emerging Governance Risk

Ambient Artificial Intelligence Clinical Documentation: Workflow Support with Emerging Governance Risk

by Daily Remedy
February 1, 2026
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Health systems are increasingly deploying ambient artificial intelligence tools that listen to clinical encounters and automatically generate draft visit notes. These systems are intended to reduce documentation burden and allow clinicians to focus more directly on patient interaction. At the same time, they raise unresolved questions about patient consent, data handling, factual accuracy, and legal responsibility for machine‑generated records. Recent policy discussions and legal actions suggest that adoption is moving faster than formal oversight frameworks. The practical clinical question is...

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