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A Clinical Touch of Text

Daily Remedy by Daily Remedy
February 20, 2022
in Contrarian
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A Clinical Touch of Text

Funny how clinical data fail to capture the patient experience – that by aggregating information on patient outcomes, we derive trends that fail to capture an individual patient experience.

Yet this is the nature of data, embedded with a logical fallacy that we continue to fall for. We collect information until we produce an outcome, and then we use that outcome to predict future information, as though the complexity of healthcare can be distilled into a cause and effect, which can somehow reverse upon command – making an effect a cause and a cause an effect. Logically, this makes no sense. But we continue to believe it.

The academic journal, Nature, published results from a relatively small study that analyzed the value of text messaging among primary care patients. The study evaluated whether continuous text messaging would improve patient engagement, and accordingly, patient outcomes.

After monitoring patients for nearly a year, the study conclusively determined that, “tailored text messages [generated by a computer algorithm] were ineffective in increasing use of primary care but increased ED [emergency department] utilization.” The implication being text messaging is not cost-effective care.

In the increasingly hi-tech world of modern healthcare, this comes as a welcomed conclusion. Of course we need the latest telemedicine widget, a simple text message is not enough – the study proves as much.

But like any outcome, it fails to tell the full story, the actual patient experience. In the study, only 31% of the eligible patients responded once. About 30% opted out of the study and 18% were excluded due to an invalid phone number. This means only one out of five participants provided multiple text messages – in a study that monitored patients for a year.

Clearly, the study failed to engage patients in a meaningful way. But rather than emphasize the limited engagement, the study focuses on poor outcomes despite any lack of consistent follow-up.

The conclusion of the study does not reflect the reality of modern healthcare, in which patient experience is paramount. We live with our phones. They are veritable appendages in digital form. When we receive a text that we want to respond to – we respond. Just look at the number of drivers who turn their heads from the road to their phones all in the name of providing a timely text response.

What this study concludes is that patients will not respond to text messages generated by a computer algorithm. Why the study used a computer instead of a personalized text messages was never explained. But according to the authors, an automated text messaging system, “allows for a relatively lower cost, but still a ‘higher touch’ and personalized experience.”

Correlating the all-too-familiar relationship between cost and engagement – a rubric that has failed time and time again, yet continues to be repeated. We need new methods of determining what works and does not work in healthcare. And to conclude from a small sample size of disengaged patients that text messaging is not an effective means of communication is simply wrong.

Text messaging is the most cost effective technology available. It provides unprecedented access and is simple enough for the most technological adverse in society. But in dismissing it based on a study that could not even engage the participants properly, we fail to understand how a simple, accessible form of engagement could improve the patient experience.

It may not influence the cost to engagement ratio. But it will do something else. It will provide information about patient behavior in moments where healthcare is the last thing on their minds. This information may not fit conveniently into an algorithm or a predetermined metric, like hospitalization rate.

But it reveals much of what patients think of when they are not thinking about healthcare. And that is worth something. Maybe that is all the information we really need.

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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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BIIB080 in Mild Alzheimer’s Disease: What a Phase 1b Exploratory Clinical Analysis Can—and Cannot—Tell Us

BIIB080 in Mild Alzheimer’s Disease: What a Phase 1b Exploratory Clinical Analysis Can—and Cannot—Tell Us

by Daily Remedy
February 15, 2026
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Can lowering tau biology translate into a clinically meaningful slowing of decline in people with early symptomatic Alzheimer’s disease? That is the practical question behind BIIB080, an intrathecal antisense therapy designed to reduce production of tau protein by targeting the tau gene transcript. In a phase 1b program originally designed for safety and dosing, investigators later examined cognitive, functional, and global outcomes as exploratory endpoints. The clinical question matters because current disease-modifying options primarily target amyloid, while tau pathology tracks...

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