The U.S. will face a shortage of up to 86,000 physicians by 2026. While AI has been touted as an ideal solution to this problem, adoption in the healthcare industry has been lagging.

This certainly is not a new problem, but it is one that many experts believe can no longer be pushed off.

Elena Branche, product director at Druid AI, an AI agent technology company, works closely with healthcare provider organizations and believes not knowing where to start with AI is oftentimes the root of adoption resistance.

We spoke with Branche to talk about how healthcare leaders can cut through AI hype to identify systems that will immediately make an impact, the foundational first steps hospitals and health systems should take when looking to adopt AI, how AI can be used to free up time and fight burnout for staff, and what an AI task force is and why this is important to have in place.

Q. How can leaders at hospitals and health systems cut through the hype to identify AI technologies that will immediately make an impact?

A. The healthcare industry has been slower to embrace digital transformation than others. However, hospitals and health systems are at an inflection point when it comes to AI adoption. With the U.S. expected to face a shortage of up to 86,000 physicians by 2026, the time to embrace AI is now.

In fact, research shows the global market size for AI in healthcare is expected to reach $31.3 billion by 2025, with a compound annual growth rate of 41.5% from 2020 to 2025.

However, with so many buzzwords surrounding AI, it's becoming increasingly difficult to cut through the noise and find which systems will have the greatest impact. Considering providing a positive and consistent patient experience is how health systems can distinguish themselves and meet patients' expectations.

The overarching goal of improving patient care can be achieved through AI integration both internally and externally as well as an understanding of which AI systems will have an immediate and profound impact.

Well-designed agentic AI is one of the most powerful technologies to improving and streamlining healthcare experiences for both staff and patients. These technologies not only enhance the quality of healthcare services, recognize patterns and save time, but also complement the necessary human touch of healthcare workers.

Conversational virtual agents ultimately save time for the internal team and the patient, leading to a streamlined patient experience, and more time for the internal team to focus on higher-value tasks.

I have four use cases that cut through the hype and have been proven time and again to have an immediate impact on patients and healthcare workers.

Healthcare personal assistant. Agentic AI can help facilitate patients' access to their data, medical history, test results, and payment and billing details. There are considerable advantages to leveraging AI to answer these questions, including higher patient satisfaction through a simplified customer experience, and more time for staff to focus on higher-value tasks.

Appointment scheduling. Appointment scheduling is a critical operation in healthcare facilities but can be a time-consuming operation. Agentic AI can allow patients to easily schedule, reschedule or cancel appointments without the frustrations of a complicated interface or waiting times in a call center.

Symptom checking. Today's patients expect to have their health-related questions answered in a timely manner. Agentic AI can be used for symptom checking and medical triaging to provide personalized care. By guiding patients through questions and allowing them to share their symptoms, AI can give quick and accurate diagnoses and schedule a follow-up appointment with the appropriate specialist.

Health tracking. Agentic AI also can help collect and analyze patient health data. Take for example a patient with diabetes who can leverage these systems to track their blood sugar levels, insulin dosages and other related metrics. The assistant can provide personalized feedback on managing an array of health scenarios as well as suggest lifestyle changes or adjusting medication dosages.

Q. What are foundational first steps healthcare organizations should take when looking to adopt AI?

A. Oftentimes, the root of adoption resistance comes from not knowing where to start with AI. The most important foundational first steps are establishing the use case you want to start with, ensuring you have set metrics to define success and how you are measuring ROI, and understanding what AI system to choose.

When it comes to use cases, pinpointing the day-to-day activities that weigh heavily on healthcare staff is a good place to start. In addition, it's important for healthcare institutions to listen to patient feedback to determine the obstacles they face. Only with this understanding can hospitals decide which use cases make the most sense to start with.

Once these use cases are decided on, healthcare organizations must put a strategic approach in place to ensure the maximization of opportunities and enable healthcare organizations to learn from their initiatives and improve them. In fact, measuring the success of agentic AI relies on several essential quantitative metrics.

This includes a measure of user satisfaction, which reflects how well the agent meets the needs and expectations of patients. This can be done by conducting post-interaction surveys or sentiment analysis so healthcare organizations can identify how they are performing.

In addition, response accuracy is a critical tool in determining the agent's effectiveness in interacting with patients. High accuracy ensures users receive relevant and helpful responses and AI systems are creating positive experiences.

Both of these indicators should be regularly monitored, measured against set KPIs and fine-tuned to enhance accuracy over time.

While these quantitative metrics are important, truly assessing conversational AI success requires an appreciation for the human touch and an understanding of user engagement. Conversational data can be analyzed to help healthcare organizations gain a deeper understanding of what works and what doesn't, and further tailor these interactions accordingly.

Being able to recognize emotions and respond empathetically to users' feelings is incredibly important to the success of a system in the healthcare field.

In order to ensure AI performs in a way that will reach these metrics, there are some important criteria to evaluate when choosing the right system for your healthcare institution.

Timely, accurate response – every time. Making sure you choose a system not at risk for hallucinating and able to give patients a timely and accurate response is critical in any industry but especially in healthcare. To ensure this, making sure the system you choose leverages training data that is accurate, timely and of the highest quality is critical for these systems to operate as error-free and bias-free as possible. In addition, it's important healthcare organizations robustly test AI systems before they are consumer-facing.

Scale to meet your future needs. It's not only important your AI systems meet your organization's needs today, they also must be able to scale to meet your evolving needs down the road. Healthcare is constantly changing, and so are your patient and staff needs. Systems should offer a track record of seamless tech stack integrations and a broad solutions library to enable this.

Protect your data at all costs. Data privacy and security is arguably the most important feature to look for in an AI system. When it comes to handling sensitive patient information, the system you choose must provide transparency around data governance, compliance and privacy standards. These systems should also grant robust control to help healthcare leaders build confidence in these systems.

Q. How can AI be used to free up time and fight burnout for clinical and administrative staff?

A. Burnout is a major problem in healthcare, which is greatly contributing to the staffing shortage we are experiencing today. In fact, nearly half of healthcare workers experience burnout on a consistent basis. When it comes to retaining current healthcare staff and improving their day-to-day roles, agentic AI plays an important role both on the administrative and clinical front.

The biggest impact agentic AI can have on clinical and administrative staff is freeing up their time to focus on more meaningful activities as well as eliminating what is known as app fatigue. Healthcare facilities face an endless stream of daily administrative tasks that need attention, and employees often need to switch between a variety of different applications, search for forms and contact various departments to get patients the information they need.

In addition to this being unnecessarily time-consuming, this constant context switching can be overwhelming. By providing employees one unified access point to relevant systems, agentic AI helps to reduce staff's mental load and helps reduce burnout. In addition, these systems alleviate tedious tasks like scheduling, offloading call volume through automated self-service for patients and providing patients 24/7 assistance.

With agentic AI able to successfully handle these interactions, administrative staff can take care of other, more valuable issues and have a more direct impact on patient care. This is not only helpful for their morale but improves the experience for patients as well.

Q. You say hospitals and health systems need an AI task force. What is this and why is this important to have in place for healthcare environments?

A. When it comes to implementing AI for the first time, embracing an AI task force is something every business or institution should consider. Improving the bottom line is a top concern for healthcare leaders and implementing a task force ensures the entire executive bench has a clear understanding of the institution's goals with AI, how they define the ROI and how they can collaborate seamlessly to bring these goals to fruition.

In addition, an AI task force is not only critical in uniting healthcare leaders on the mission behind AI integrations but serves to ensure this is being handled responsibly. When it comes to healthcare use cases, AI is given access to incredibly sensitive data.

As a result, the task force is instrumental in putting proper guardrails in place to ensure that all stakeholders feel confident in data privacy and security. As the regulatory landscape around AI continues to evolve, this task force will also be important in keeping up to date with new rules and regulations and ensuring that the healthcare organization remains informed and compliant.

Lastly, an AI task force should include a variety of members across the healthcare organization. Considering the fact AI is rarely a single touch point, but instead interacts with multiple back-end systems, leveraging different perspectives and backgrounds is important when adopting a technology that is meant to benefit all. As both an external and internal-facing system, having representation across different stakeholders is key.

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