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Home Perspectives

The Art in the Science of Virtual Care

Daily Remedy by Daily Remedy
February 13, 2022
in Perspectives
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The Art in the Science of Virtual Care 2022.02.15

Steve Jobs was great not because of any technical skill. He was great because he could make you fall in love with technology. This is less a science and more an art. And a lesson healthcare should heed as it seeks to integrate virtual care into mainstream models of medicine.

Jobs did not integrate product features to create a smart phone. He imbued them with feelings, giving life to what would otherwise be considered as inanimate objects. He saw the world through perceptions and experiences, and wanted Apple customers to build a relationship with their phones, almost to the point of falling love, arguably the strongest of emotions.

Russian author Leo Tolstoy described this transmission of feelings as art. An analogy similar to the one Dr. William Osler used to describe his experiences with patients. Osler saw medicine as an experience developing over time, over multiple patient encounters.

The thoughts and words conveyed and exchanged during a patient encounter form a relationship, much like the relationship people have with art or an object of affection. In virtual care, that relationship includes the experience of both the care provider and the technological interface.

Therefore, for virtual care to be considered equal to traditional in-person care in terms of patient outcomes – and eventually become standard of care – the quality of communication over technological platforms must be equal to, if not better than, the communication expressed in a clinical encounter.

Clinical communication conducted virtually must embody the same ideals – compassion, sincerity, and above all, trust. In healthcare, trust is a perception that forms over time, and the quality of trust is an aggregate of all those experiences.

We remain fond of childhood toys, regardless of our age, because we associate our earliest memories with them. And the memories of those experiences evoke particular emotions of nostalgia. Trust in healthcare is built the same way. A simple handshake from a physician is as impactful as the medicines prescribed – because both are acts of trust.

In fact, no matter how far healthcare advances, it will always be defined by perceptions of trust among patients. And if virtual care seeks to be at the vanguard of healthcare advancements, then it must prioritize trust in all facets of the patient experience.

Telemedicine, the basis for most virtual care models, was never adopted as readily as during the COVID-19 pandemic. When patients could no longer see their providers, they resorted to telemedicine. We assumed it was a simple transition from an in-person encounter to a digital one – with the experiences being much the same aside from a digital interface.

But the perceptions generated during the virtual encounter were vastly different. Scores of patients rushed online to express their fears and concerns, not only to discuss their symptoms, or perceived risk of being infected with COVID-19, but also their jobs, livelihood, and other issues not traditionally associated with medical care.

But in those moments of fear, they became medical issues. And telemedicine became the platform to express this fear, cultivating a unique patient experience in the process.

Telemedicine builds patient trust as much as it treats medical conditions, like any live patient visit, but not in the same way. The trust built is distinctly different because the experiences are unique. The growth of virtual care, it then follows, depends more on the perceptions that form than by any technological feature.

Increasing the points of engagement is not the same as improving the quality of experience. The latter is perception driven and, consequently, the driver of patient trust. These perceptions, aggregated over time, will dictate how patients will adopt virtual health models.

Accordingly, we should study the unique perceptions that develop in a virtual encounter and optimize the quality of perceptions that form – and only utilize technology that prioritizes the patient experience.

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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
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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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