Discover AI in patient scheduling with Floresco.ai

Discover the reality behind AI in patient scheduling software. We clear up prevalent misunderstandings and highlight AI’s transformative role in healthcare scheduling.

As health systems advance in their digital transformation to become more efficient and patient-centric, the role of artificial intelligence (AI) is increasingly crucial. While AI is being utilised across various healthcare workflows, it has a significant impact on patient scheduling - a core component of the healthcare experience that often presents challenges for both patients and providers.

Despite AI’s transformative potential in patient scheduling software, misconceptions persist within the industry. Here, we explore five common misunderstandings regarding AI’s role in patient scheduling software and seek to address each one.

Provider Schedules and Preferences Are Too Complex for Patient Scheduling Software

Provider schedules can indeed be extremely complex, involving numerous factors such as clinician availability, specialty skills, patient needs, and regulatory requirements. Given this complexity and the inherent unpredictability of in-person care delivery, it’s understandable why some believe scheduling solutions cannot manage provider schedules effectively. However, this viewpoint underestimates the capabilities of modern AI technology.

It is precisely because of this complexity and unpredictability that AI-based patient scheduling software is so beneficial. Modern scheduling solutions excel at processing vast amounts of data and identifying patterns or solutions that humans might miss. Machine learning (ML) algorithms can analyse historical scheduling data, provider availability and preferences, patient demand patterns, and other factors to optimise schedules. Additionally, they can measure patient satisfaction when supported by digital scheduling tools compared to a patient who schedules via phone with a human representative.

Today’s AI-based scheduling software learns individual provider preferences over time and incorporates them into the scheduling process, leading to more satisfied staff and better patient care. These tools can also adapt to real-time changes. If a provider calls in sick or there is a sudden influx of patients, the scheduling software can immediately adjust schedules, considering relevant factors to find the best solution.

For instance, within the first six weeks of implementing an automated scheduling solution, one health system saw scheduled appointments for the same number of available providers increase from 5.7% to 14%, with an average of more than 400 online appointments booked per week.

AI Will Replace All Existing Staff Who Handle Patient Scheduling

AI is often viewed as a threat to jobs in various industries, including healthcare. However, this perception misses a crucial point. Deploying AI for patient scheduling is not about replacing human staff but enhancing both the staff and patient experience.

With automated scheduling software, staff can spend significantly less time making and answering phone calls and more time building relationships with clinical staff, providing a positive experience for patients and families, and ensuring patients get the care they need.

“I think about elevating work,” said a Vice President of Digital Services at a notable health organisation. “If there are tasks that are so monotonous and manual that nobody wants to do them, why can’t we automate those and have people work on more valuable tasks?”

For example, researchers at Stanford University’s Digital Economic Laboratory and the Massachusetts Institute of Technology found that customer support agents who used a generative AI assistant increased their productivity by 14% on average.

Patient Scheduling Software Using AI Will Make the Patient Experience More Impersonal

Healthcare is deeply personal, and integrating AI into the patient scheduling process might seem to contradict this. However, advanced AI technologies, such as natural language processing (NLP) and large language models (LLMs), can significantly enhance the level of personalisation providers can offer, rather than diminish it.

By analysing various sources of patient data in seconds, such as a patient’s medical record or pharmacy data, AI solutions can tailor appointment schedules to individual needs, preferences, and health conditions. This leads to more personalised care, improved patient satisfaction, and better health outcomes.

Automated Patient Scheduling Software Is Only for Large Health Systems

It’s a common misconception that AI solutions are designed solely for large health systems, assumed to have the necessary resources - financial, human, and technical - to implement AI. In reality, AI is scalable and versatile, offering significant benefits to healthcare organisations of all sizes. From solo practices to mid-sized clinics to large hospitals, all can leverage AI for efficient and effective patient scheduling.

The key is having a clear plan and specific evaluation criteria. It’s also essential to look for an intelligent scheduling solution that uses the latest technologies to automate the entire process and is flexible enough to adhere to all provider templates and preferences, ensuring that patients only schedule in the appropriate slots within a provider's calendar. Other top considerations should include:

• A collaborative partnership with IT. A partner should work cross-functionally to assess needs, determine organisational readiness, identify required resources, and build an action plan and communication strategy to stay on track.

• Minimal change management for scheduling staff. The solution should perform tasks instead of humans, significantly reducing scheduling workloads and eliminating the need for extensive training.

• Rapid deployment. Implementation or modification should occur in weeks, not months or years, regardless of the health system's size.

Patient Scheduling Software Can Only Triage Inbound Requests

Today, most healthcare scheduling is ‘inbound,’ meaning that patients search for and initiate care themselves. Often, this is due to the health system having limited resources to proactively engage patients, even when an appointment is necessary. Patient scheduling software, particularly those with intelligence at the core, can automate inbound scheduling requests and allow staff to focus their time and energy elsewhere.

Despite most patients preferring to self-schedule their care using digital tools, the latest research indicates that nearly two-thirds of patient access leaders schedule the vast majority of patient appointments via telephone. This misalignment causes frustration on both sides, as health systems need to staff call centres, and patients seek care from other providers offering more modern scheduling solutions.

Today’s leading health systems are deploying intelligent patient scheduling software that automates both inbound and outbound scheduling, dramatically decreasing no-show rates and increasing scheduling for care gap closure.

Conclusion

Floresco.ai solution is at the forefront of revolutionising patient scheduling through AI, addressing common misconceptions, and proving the immense benefits AI can bring to healthcare. By adopting these advanced solutions, healthcare providers can enhance efficiency, improve patient satisfaction, and deliver better health outcomes. Embrace the future of patient scheduling with Floresco.ai and see the transformation in your healthcare delivery.