Empowering Nurses: How AI Enhances Healthcare

Empowering Nurses: How AI Enhances Healthcare

In a recent interview on TheRegister.com, Brandon Vigliarolo posed a crucial question: Is AI truly revolutionizing frontline healthcare? As the co-founder and Chief Product Officer of Thoughtful, I firmly believe it is. The integration of AI in healthcare represents a pivotal moment in the healthcare industry's evolution, one to be highlighted for decades to come. As is, the healthcare industry is constantly playing catch-up, especially when it comes to patient experience and operational efficiency, and a thoughtful use of AI proposes solutions that can benefit providers and patients alike.

In this interview we go beyond the backend automations that Thoughtful.ai is known for, and address AI in the healthcare industry as a whole, from Chatbots to Nursing solutions. Below are some snippits from the interview. See the full interview on TheRegister.com.

Brandon Vigliarolo questions wether or not AI serving in frontline healthcare is a positive revolution.

  • Our take: This industry is continuously playing catch-up, especially across patient experience and the operational administration side of healthcare, which has shown a material degradation of the patient experience driven by an underlying staffing issue. Our belief is that adding capacity via AI will ultimately result in a better patient experience, faster services, and impact the affordability of healthcare.

Next, Vigliarolo questions the existing frustrations patients are experiencing utilizing AI.

  • Our take: While we agree that current uses of AI within Chatbots and Interactive Voice Response (IVR) systems, for example have proven frustrating for patients, in the name of innovation, the further integration of AI needs to be managed delicately. As long as we're smart about the entry points and scopes, we have to continue to move forward and ongoingly improve our tools.

Vigliarolo notes AI as notoriously error-prone, citing a current lawsuit against United Healthcare for making medicare decisions and questions what systems are in place for making current decisions.

  • Our take: With the amount of backlog and growing demand within the healthcare industry, the industry can't afford to wait until AI is flawless to implement solutions, but what we can do is carefully select use cases. Our AI Agents are trained in very specific decision-making processes, which are low-risk use cases to mitigate that risk. Our RPA processes are supported by human-in-the-loop, which allows for human reviews and checks and balances, which offers providers both speed and autonomy.

Next we dive into how we’re able to ensure that AI is making appropriate decisions.

  • Our take: AI currently works best with use cases that have standard operating procedures, recurring workflows, and the most standardization that leaves the AI with the least room for interpretation. Data exchanges tend to be the best place to start. This also makes the AI Agents easier to train, leaving fewer permutations, more guardrails, and lower risk. These are also easier to detect anomalies, which is usually where we look to start, and is why we’ve focused our AI Agents heavily in the areas of Eligibility Verification, Claims Processing, and Payment Posting.

The best use cases for us are places where there are decisions about what the next steps need to be in a workflow, refining the nuance of what the next best steps are based on a variety and spectrum of inputs and complex "if-this-then-that" scenarios. We're able to get a lot of lift for healthcare networks using Large Language Models (LLMs) and other foundational models.

Vigliarolo rightfully acknowledges the frustrations patients may experience utilizing current AI implementations, pointing to the future of patient chat bots, which can currently be very frustrating.

  • Our take: In a case where a model or AI Agent has previous contextual data, you can get a lot of efficiencies with chatbot approaches, especially when enhanced by LLMs, which are great at sense-making of unstructured data. With some fine-tuning and constraints, the LLMs can properly make sense of user inputs and make processed-based decisions, allowing them more flexibility in the kinds of inputs it can interpret from the human, and allowing patient experiences with AI to be less confined. While there’s room for this use of AI to be further developed, there’s a bright future for IVR systems with the implementation of LLMs and other foundational models.

Next he approaches “a big sticking point” within the introduction of AI into healthcare - AI Nurses are currently offered by Nvidia and Hippocratic AI for $9 an hour, a fraction of the cost of a nurse, and questions wether nurses jobs are at risk to test this technology.

  • Our take: We have to look at the big picture — We have a perfect storm developing in our healthcare system, and we're starting to see some of those symptoms now. One of the inputs being the growing demand for healthcare, with our baby-boomer generation moving into older age, we're expecting $4.5 trillion in healthcare spending to raise upwards of $6.8 trillion by the year 2030. A second input being that the healthcare job shortage is expected to increase, causing a growing discrepancy between the demand for services and the talent supply gap. There’s an opportunity for us to fill the gap with technology, without which, the storm would grow beyond our control.
  • If anything, what it will do is improve the nurses' experience, and potentially evolve what the job is, getting the nurses out of doing some of the mundane tasks related to the job, and allowing them to focus on more engaging and fulfilling parts of the work. The forecasted result is a boost in productivity, followed by an increase in wages.
  • If we continue these types of technological investments, it could put the healthcare industry in a much better place.

At Thoughtful, we view AI not as a threat, but as a catalyst for positive change within healthcare. The current landscape presents a stark reality: a decline in the patient experience due to staffing limitations, and an urgent need for solutions that can enhance capacity and streamline services. This is where AI steps in, offering a viable solution to augment capacity and enhance overall patient care.

While the integration of AI in healthcare at scale is not devoid of challenges, Thoughtful AI’s particular sector has found great success in using AI Agents by starting with repetitive tasks driven by rules-based decisions, making them easy to automate, and offering large benefits with minimal risk.

As we navigate the evolving landscape of AI in healthcare, one thing remains certain: the future holds immense promise for both patients and healthcare professionals alike. Our interview delves deeper into these topics, exploring the transformative potential of AI within the healthcare ecosystem.

In conclusion, the integration of AI in healthcare represents a pivotal moment in the healthcare industry's evolution, one to be highlighted for decades to come. By embracing innovation and prioritizing patient-centric approaches with AI, we can create a better, faster, healthier future for healthcare professionals and patients alike.

Check out the original article

here.

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Published On:

May 20, 2024

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