How AI-Enabled Remote Patient Monitoring Is Improving Patient Adherence and Outcomes

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By Janet Dillione

Throughout the pandemic, the ability to deliver essential care to at-risk individuals in their homes has been not only critical, but also lifesaving. At the outset of COVID-19, with healthcare resources stretched thin and nonessential appointments deferred, healthcare organizations looked to remote technology solutions to help manage patient care outside traditional care settings.

The rapid shift toward telehealth accelerated the adoption of remote patient monitoring (RPM) and played a significant role in making at-home care a reality. This new care delivery model helped to reduce the spread of COVID-19 among the most vulnerable and allowed providers to deliver the full continuum of care for patients with acute and chronic illnesses.

While the pandemic may have driven the swift adoption of RPM, a wide body of evidence has shown it can effectively enhance and improve care. By incorporating RPM into a patient’s care plan, clinicians can monitor a patient’s vitals and health data in between visits, allowing them to intervene promptly and make changes to treatment before a patient’s condition deteriorates or requires a costly trip to the emergency department (ED). Equipped with this critical health data, providers can make more informed clinical decisions and deliver more efficient and effective care.

Evidence has demonstrated that RPM can significantly improve health outcomes, and when combined with the power of artificial intelligence (AI), its potential is even greater. One example is an AI-powered virtual health assistant that uses natural language processing and machine learning to extract data and information from conversations, thereby understanding and processing those conversations accordingly.

The use of AI and RPM in this application can increase patient adherence, boost clinical efficiency, and improve outcomes. The following are four ways that AI-enabled RPM is improving care delivery:

  • Increases patient adherence and self-management: One of the challenges hindering widespread adoption of RPM is patient adherence. Many patients lack the support and motivation to utilize RPM effectively, and most practices do not have the time to ensure patients are staying compliant. With AI-enabled RPM, a virtual health assistant sends patients smart text-based communications on behalf of the practice reminding them to take their readings and providing education and support. This increases patient adherence and leads to higher patient retention.
  • Boosts clinical efficiency: Higher patient adherence results in more regular readings and leads to more accurate and meaningful data for the provider. Armed with this information, providers can make more informed care decisions and better calibrate treatment in response to their patients’ needs. Without this continuous communication between the patient and provider, a practice may go months before engaging with the patient again.
  • Fosters better patient outcomes: Patients with chronic diseases such as hypertension, heart failure, diabetes, and obesity often require daily adherence to medication, exercise, and care plans. By utilizing AI-enabled RPM, providers gain the ability to see health trends over time and between visits, which results in earlier interventions, fewer hospitalizations, and improved patient outcomes. Research has demonstrated measurable improvements to patient health metrics with the use of AI-enabled RPM, including significant reductions in blood pressure, blood glucose, and weight. In an analysis of more than 18,000 Medicare patients across nearly 350 practices using RPM, researchers found:
    • -4.7 mmHg average decrease in blood pressure for hypertensive patients within 180 days
    • -7.5 mg/dL average decrease in blood glucose for diabetic patients within 180 days
    • -8.2 lb average 90-day weight loss for patients whose starting weight was more than 286 pounds
  • Lowers care costs: By supporting earlier detection of clinical deterioration and more timely care, AI-enabled RPM technology may reduce unnecessary ED visits and inpatient utilization, which can ultimately lower care costs.

A recent cost-utility analysis published in the Journal of the American Medicine Association highlighted promising research suggesting that RPM could be associated with 87% fewer hospitalizations, 77% fewer deaths, and reduced per-patient costs of $11,472 compared to standard care.

While the pandemic may have expedited the rise of RPM, the technology’s potential to improve care and outcomes is evident. There is little doubt that at-home care will grow post-pandemic, and AI-enabled RPM will help make it a reality for more patients.

Janet Dillione is CEO of Connect America.