How AI-Enabled RPM Can Improve Healthcare Delivery

By Rosemary Kennedy, PhD, RN

By now, everyone is familiar with the Triple Aim of healthcare: improve the care experience, enhance health outcomes, and reduce costs. It’s a frequent topic of conversation across the industry, but many healthcare leaders struggle to find consensus on how to achieve these admirable goals.

Fortunately, artificial intelligence (AI) offers healthcare organizations an opportunity to utilize their existing data infrastructure to redefine the traditional care delivery model in a meaningful way for their patients, while getting them closer to achieving the vaunted Triple Aim.

One clinical tool enabled by AI is remote patient monitoring (RPM). RPM is a healthcare delivery method that uses digital technologies to remotely monitor and analyze a patient’s vitals and other health data outside of a traditional healthcare setting. This technology securely and non-intrusively transmits health information between patients and providers to enable more informed clinical decision-making, earlier interventions, and more preventative care. RPM enabled with AI can go a step further by supporting practices with patient enrollment, engagement, and education to ensure adherence and reduce administrative burden. 

There are three major areas at the intersection of AI and RPM: clinical efficiency, health outcomes, and cost of care. Unsurprisingly, they mirror the Triple Aim. 

Promoting Clinical Efficiency

A study published in NPJ Digital Medicine in 2018 found that “passive gathering of data may also permit clinicians to focus their efforts on diagnosing, educating, and treating patients, theoretically improving productivity and efficiency of the care provided.”

Industry leaders strive toward a system like this—one in which clinicians don’t have to spend nearly as much time requesting health status information from patients or waiting until the next office visit to review the data and calibrate the patients’ care plan.  

AI-enabled RPM promotes clinical efficiency by continuously transmitting critical health data and bringing the most critical cases to the forefront, therefore enabling a more preventative and personalized approach to care.

Delivering Better Outcomes

When it comes to improving patient outcomes, look no further than RPM’s ability to shift healthcare from reactive treatment-based care toward value-based preventative care.  For providers, the continuous access to data and information received in-between visits with RPM lays a foundation for a better care delivery model by eliminating the gaps and barriers that exist within standard care. This can often be critical for patients with chronic diseases such as hypertension, heart failure, diabetes, and obesity that require daily adherence to medication, exercise, and nutrition care plans.

Research published by the American Heart Association demonstrated that remote patient monitoring (RPM) was able to substantially reduce systolic blood pressure (SBP) and diastolic blood pressure (DBP) compared to usual care and self-monitoring alone.  

A recent study in Hypertension found that remote monitoring may cut heart attack and stroke rates by 50% for individuals with uncontrolled hypertension. 

Further research examining the effectiveness of AI-enabled RPM demonstrated its ability to significantly help lower blood glucose levels in diabetic patients, decrease blood pressure in hypertension patients and reduce weight in obese patients. In addition, AI-enabled RPM has been shown to increase patient adherence by up to 36%. 

By arming clinicians with these tools, they can see trends over time and in-between visits, enabling changes in the plan of care that result in better health outcomes for patients.

Reducing Costs

As the healthcare industry continues to face increasing rates of chronic disease and soaring costs of care, technologies such as AI-enabled RPM are paving the way for the future of healthcare delivery largely due to their ability to effectively address the Triple Aim.

A recent cost-utility analysis published in JAMA highlighted promising research suggesting that remote monitoring could potentially be associated with 87% fewer hospitalizations, 77% fewer deaths, and reduced per-patient costs of $11,472 over standard care and gains of 0.013 quality-adjusted life-years.

Elsevier researchers cited estimates that AI could reduce US healthcare costs by $150 billion in 2026, due largely to “changing the healthcare model from a reactive to a proactive approach” and “focusing on health management rather than disease treatment.”

The latter part of Elsevier’s analysis is key to the nature of AI-enabled RPM: a forward-facing technology that seeks to address health conditions before they become problematic.

Achieving the Triple Aim

Together, AI and RPM can improve the timeliness of care enabling earlier detection of clinical deterioration and quicker interventions that result in fewer unnecessary emergency room (ER) visits and hospitalizations. This technology provides support to clinicians and significantly improves patient outcomes while helping to boost the bottom line and address some of the most complicated healthcare challenges.

Rosemary Kennedy, PhD, MBA, RN, is the chief health informatics officer for Connect America, with expertise in delivering innovative, value-based healthcare by utilizing health information technology and process redesign to improve quality, safety, costs and performance.

At ATA2022, Janet Dillione, Connect America’s CEO, will deliver a featured presentation, Reimagine Digital Health to Empower Graceful, at Home Aging in a Growing Senior Population, on May 3 at 9am. Be sure to stop by the Connect America booth (#2722) on the ATA2022 Exhibit Floor.