Boost patient engagement with AI

Key takeaways:

• Artificial intelligence (AI) can help collect patient data and create personalized communications.
• AI also can choose the best specialists for referrals based on individual patient needs.

Primary care is usually a patient’s first encounter with a health care system. But efforts to maintain engagement typically falter after the initial visit.

Providers miss the chance to keep patients engaged throughout their care journeys, leaning on automated appointment reminders with limited bandwidth to share patient education information or expand on the journey to manage health proactively.

Patient engagement matters. It leads to better health outcomes and enhances their overall experience. When patients are actively involved in decisions about their health and engaged, they are more likely to follow their care plan, take prescribed medications and attend medical appointments.

But maintaining a connection with patients takes time and effort. The Association of American Medical Colleges finds that by 2034, the U.S. will face a shortage of up to 48,000 primary care physicians. As these numbers drop, practicing clinicians can only expect the volume of patients they must care for and engage with to grow.

For time-strapped clinicians, getting more patients to participate in their health may feel like another task in an already heavy workload. But with the help of artificial intelligence (AI) and generative AI, providers can engage with patients holistically — beyond the initial appointment — without adding to their administrative burden.

Engagement at the first visit

For the past decade, the health care industry has focused on providing the right care at the right time and in the right place. Now, the industry needs to go further, sending the right message, using the right language in the right tone and across the right channels to engage with patients broadly and in the way that suits them best.

As the health care system’s front door, PCPs collect data about a patient’s health history, medications and allergies during their first visit. Other data are inconsistently collected and often overlooked as they live as unstructured data in a medical record.

A simple way to start is by having medical staff members ask patients about their communication preferences. Would they rather receive information over the phone, by text or a notice in the mail? For example, there are better options for unhoused patients than receiving health information by mail. Once added to the electronic health record, all providers have access to that insight as they meet the patient at different points across the health system.

Learning more about a patient’s social determinants of health (SDOH) also guides engagement. For example, asking about their education level can help providers understand their patient’s literacy skills and shape the language used in follow-up materials. Inquiring about a patient’s cultural or religious beliefs can ensure clinicians propose a treatment plan that aligns with a person’s personal preferences.

Creating patient-centric communications

With physicians spending nearly 10% of their time on administrative work, nurturing greater engagement may seem like another task preventing them from caring for patients. Fortunately, AI excels at helping clinicians collect more patient data and tailor their communications.

AI can listen to a clinician’s free-flowing patient conversation and automatically convert the dialogue from unstructured to structured data and add it to the EHR. Clinicians can focus on the patient and on administering care rather than toggling between EHR screens.

Generative AI is a subset of AI that can use patterns in existing data to create new, seemingly original content. It can produce text, images, audio, synthetic data and more. When embedded in a health care provider’s processes, the technology can reference SDOH information to create tailored materials, follow-up notes and other resources. For example, if a patient is struggling to cover basic living expenses, AI can propose resources for discounts on transportation or medication.

Primary care offices can use generative AI to engage regularly with patients based on past behaviors and clinical needs. A person with a higher acuity issue may need more in-depth and frequent information. Some clinicians even rely on ChatGPT, another subset of AI, to generate scripts for sharing difficult news with patients with greater empathy.

Referrals that meet patients’ needs

When patients need a referral, it is common to send them to a specialist that the PCP knows. But that does not mean the specialist has the right expertise for that patient, is conveniently located near them or is covered by their insurance plan.

Faced with these unknowns, patients may choose to find a different specialist outside their current health system. Or, worse, they become disengaged and do not seek the additional care they need.

Conversely, when clinicians provide an AI-powered referral, the results are patient-centric and more likely to foster ongoing engagement. The technology considers factors such as:

• the location of the patient and the specialist;
• a specialist’s expertise and track record of successful outcomes (value); and
• the specialist’s schedule and availability to see new patients.

An AI-powered solution automatically shares this information with the patient's insurance provider and confirms the specialist is part of their care plan. The specialist's office then contacts the patient to schedule an appointment.

From the insurance coverage to the specialist's location and availability, AI tackles many hurdles that can delay or prevent patients from getting the care they need. Plus, when a patient receives a referral to a specialist with a history of successful outcomes, there is a better chance of lowering health care costs. A customized AI-generated referral can keep patients engaged in their health and their current health system.

Personalizing the patient experience

Whether it is in billing, coding or radiology, health care has the potential to use AI in many capacities. To put the technology to work on patient engagement, consider these ideas for establishing an effective AI strategy:

• Understand how the technology can impact the patient experience across the care continuum. Recognize how each step connects to the whole journey rather than focusing on single-point solutions.
• Begin with one AI use case. Ensure it is a building block on a broader technology roadmap toward the organization’s long-term goals.
• Assess the impact that implementing AI may have on other systems. Do not work in a vacuum. Find opportunities for synergies and encourage economies of scale. Work to mitigate risks.

Boost engagement, not workload

PCPs often miss the chance to collect and enhance the data that can keep patients actively involved and managing their health. With the number of physicians in the U.S. set to decline by nearly 50,000 in the next 10 years, those who continue to practice will need to find more ways to nurture patient engagement without substantially adding to their current workload.

Using AI, clinicians can tailor communications to the tone, style and channel that resonates with each patient and deliver a care experience that keeps them engaged with the health care system and their well-being.

References:

• Dall T, et al. The complexities of physician supply and demand: Projections from 2019 to 2034. https://www.aamc.org/media/54681/download. Published June 2021. Accessed Sept. 1, 2023.
• Toscano F, et al. J Gen Intern Med. 2020;doi:10.1007/s11606-020-06087-4.

For more information:

Maria Gil, MHA, specializes in how data, technology and AI can transform health care solutions as a partner with Genpact, which is a global professional services firm that serves eight of the top 10 global health care companies. She can be reached at maria.gil@genpact.com.