In the past, patients who were unable to travel to a physical therapist’s office after surgery might opt for in-home PT, which was not always affordable or available. Before the pandemic, only 2% of physical therapists offered virtual visits, a number that quickly rose to 47% in July 2020, after the Centers for Medicare & Medicaid Services broadened its eligibility requirements for remote telehealth services to include outpatient facility-based providers. Still, uncertainty about telehealth’s reimbursement continues to hamper its use.   

In recent years, virtual care management platforms have emerged as a viable way for health systems and ambulatory surgery centers to monitor and guide patients as they recover from injury or surgery at home. Many of these platforms rely on generic educational content, such as short pictorials that show users how to complete a set of exercises. However, research shows that patients are far more likely to engage with aesthetically pleasing, interactive platforms that incorporate personalized health information and are easy to navigate.

Virtual care management platforms are much more effective when their content is individualized to reflect the patient’s demographics, clinical circumstances and learning preferences. By delivering personalized educational content relevant to the patient’s health status and care journey, a digital platform can drive higher patient engagement — and thus better clinical outcomes. After all, while a 65-year-old triathlete may have had the same joint replacement surgery as an inactive, obese 40-year-old, the two patients require entirely different recovery paths, and will likely respond to different motivation techniques to achieve their personal recovery goals.

While individualized care is key for both improving outcomes and containing costs, such systems have traditionally been expensive to implement.  The advent of AI and machine learning provides a new methodology for scaling high-quality, standardized physical therapy education and clinician-prescribed exercises without the need to hire additional resources.  

Leveraging the continuous feedback loop  

The first generation of digital patient engagement tools merely digitized previously office-based tasks, offering patients the ability to complete registration forms or make a payment online. Next-generation tools prioritize the patient experience in their user design, and often use AI to collect data points, drive messaging timing and delivery, and motivate behavioral change.

An AI-enabled virtual care management platform repeatedly engages the patient in her episode of care, capturing a wealth of input data that then informs the machine learning algorithm in a continuous feedback loop. Even before the pandemic, 83% of physicians believed that increased patient-generated data from connected devices would enable more effective care plans in the future. Now, the continued growth of virtual care management tools seems likely to transform how both patients and providers experience healthcare.

On a next-generation platform, the patient’s profile encompasses all relevant demographic data, including clinical conditions, comorbidities, and medication history. With the addition of social determinants of health data, an AI-enabled platform can also predict how the patient is likely to respond to treatment and can provide timely content that helps the patient prepare for anticipated roadblocks.

AI-driven adaptive education: Following the patient’s lead

By using AI to capture patient input data, virtual care management platforms can precisely tailor a patient care plan to reflect their current needs, much as a physical therapist would during an in-person session. Adaptive patient education uses a patient’s ongoing participation input data to trigger more effective care pathways.

Consider a patient who struggles to complete an exercise video, noting afterwards that she cannot lift her leg very high due to excruciating pain in her hip. An AI-enabled platform can collect this input in real time and prompt the patient to provide more information. The platform may deliver a questionnaire regarding the patient’s recent activity, inquire about the patient’s adherence to her medication regimen, or use interactive pop-ups to evaluate her swelling.  

When the patient logs in the next day, the next set of exercises offered will be easier to complete. Her care path will continue to adapt to reflect her current level of progress. Depending on the patient’s feedback, she may be prompted to watch a video on rest periods following physical exertion, or to complete a quiz on alternating anti-inflammatory medications for better pain relief.

Expanding the reach of an overburdened care team  

AI-enabled care management platforms can also issue provider alerts when necessary, functioning as a virtual extension of the patient’s care team. Depending on which workflows are enabled, the platform could notify the care team when a patient hasn’t logged on in days, or when a patient is experiencing high levels of frustration or new mobility challenges.

An AI-enabled virtual care management platform can use data patterns, patient-reported outcomes and demographic data to identify patients in need of extra attention. Instead of devoting hours of time to the basics of postoperative education for all their patients, care teams can focus on those patients who are at risk for unnecessary complications.  When a patient’s progress deviates from the expected progression, care teams can proactively intervene to get the recovery back on track.

By giving clinicians the insights they need to monitor and guide patients from afar, AI-enabled virtual care platforms help providers offer a more personalized, effective care experience despite the burden of higher case volumes. When patients are encouraged to develop sustained, long-term engagement in their own care journeys, results are higher patient satisfaction, lower costs and better clinical outcomes.  

Bronwyn Spira is a physical therapist and the founder and CEO of Force Therapeutics.