Does Remote Patient Monitoring Reduce Acute Care Utilization?

A deep-dive on the clinical evidence for RPM-based care models and their effects on ED visits and hospitalizations

Remote patient monitoring (RPM) has emerged as a promising approach to help health care systems manage patients outside of traditional care settings. In the decades-long quest to make chronic care models more proactive, RPM technologies help fit the bill. RPM involves the use of connected medical devices to collect personal health data outside the clinical environment, allowing providers to review patient data from a different location. The technology encompasses various devices and architectures, including sensors, internet of things (IoT) devices, networking infrastructure, cellular networks, cloud computing platforms, and in some cases, artificial intelligence capabilities for advanced analytics (this is an emerging approach).

The core premise of RPM is that by enabling early detection of clinical deterioration through continuous monitoring of vital signs and symptoms, health care providers can intervene before a patient requires emergency department visits or hospitalization. However, debate continues about whether RPM consistently delivers on this promise of reducing acute care utilization.

As with most things, “it depends.”

National Trends in the Implementation of RPM Care Models

A study by Tang and colleagues study examined the growth and usage patterns of remote patient monitoring (RPM) in a large commercially insured US population between 2019-2021. The researchers found that RPM claims increased more than fourfold during the first year of the COVID-19 pandemic, with most of this growth driven by a small number of primary care providers - specifically, the top 0.1% of providers (342 doctors) accounted for 69% of all RPM claims. Among patients who started RPM, about 51% continued using it for at least six months, with an estimated average cost of $706 per patient in the first year.

Interestingly, the study found that RPM was not being particularly targeted toward patients who might benefit most from it. Among patients with diabetes or hypertension who saw high-volume RPM providers, there were only modest differences in RPM use between those with more complex conditions versus simpler cases, and patients with well-controlled diseases were just as likely to receive RPM as those with poor disease control. The researchers conclude that while RPM shows promise, more research is needed to identify which patients benefit most from it, and they recommend that payers and policymakers closely monitor RPM use and spending to ensure appropriate utilization as the service continues to grow rapidly.

The fee-for-service business model from reimbursement incentivizes practices to roll out RPM for all eligible patients. It is not to suggest that monitoring a large patient population is a bad thing, clinically, but it does have ramifications for cost of care.

The Evidence for RPM Reducing Acute Care Use

Multiple studies have demonstrated RPM's potential to decrease hospital admissions and emergency department visits. A systematic review by Taylor et al. found that across 91 studies, RPM interventions were associated with reduced hospital admissions in 49% of studies examining this outcome. The impact was particularly strong for certain conditions like chronic obstructive pulmonary disease (COPD) where RPM showed greater effectiveness at reducing emergency department visits compared to other conditions.

A Mayo Clinic study by Haddad et al. examining high-risk COVID-19 patients found that RPM-engaged patients experienced significantly lower rates of 30-day all-cause hospitalization (13.7% vs 18.0%), prolonged hospitalization (3.5% vs 6.7%), and ICU admission (2.3% vs 4.2%) compared to non-engaged patients. The RPM group also had substantially lower costs of care.

While the current use of the concept of RPM is focused on non-invasive monitoring using connected medical devices and wearables, evidence from invasive monitoring also supports the cost-avoidance hypothesis. For cardiovascular disease specifically, invasive monitoring through implanted devices appeared effective at reducing hospitalizations. A large cohort study by Piccini et al. including over 92,000 patients found an 18% lower risk of all-cause hospitalization among RPM users, with a reduction in mean hospital length of stay of approximately 3 days.

However, if you review the clinical and health services literature about RPM, you will find mixed evidence of RPM’s effect on acute care utilization.

Studies Showing Limited Impact from RPM

One study examined the effectiveness of remote patient monitoring for Medicare beneficiaries aged 65 and older with hypertension between 2018-2020. The researchers conducted a retrospective cohort study comparing 16,339 RPM users with 63,333 non-users, analyzing outcomes including mortality, hospitalizations, emergency department (ED) visits, and outpatient visits within 180 days of starting RPM. The study used propensity score matching to balance patient characteristics between the two groups.

The results showed significant benefits associated with RPM use. RPM users had a 34% lower risk of death (2.9% vs 4.3% mortality rate) and approximately 22% lower risk of both overall and cardiovascular-related hospitalizations compared to non-users. While there was no significant difference in ED visits between the groups, RPM users had higher rates of cardiovascular-related outpatient visits, likely due to the regular follow-up care built into the RPM program. These findings suggest that RPM can be an effective tool for managing hypertension in older adults, though the researchers note some limitations, including potential unmeasured confounding factors and the relatively short follow-up period of six months.

A more recent observational study examined the effects of RPM on hypertension care outcomes among Medicare patients. The researchers analyzed data from 192 high-RPM practices (with 19,978 patients) and 942 matched control practices (with 95,029 patients) between 2019 and 2021. Using statistical matching and regression analysis, they compared changes in outcomes between practices that heavily adopted RPM (defined as ≥25% of hypertension patients using RPM) versus those with minimal RPM use (<2.5% of patients).

The study found that patients at high-RPM practices had improved medication management may have reduced acute care utilization, but higher health care costs in other places. Specifically, these patients saw a 3.3% increase in hypertension medication fills, used more unique medications, but had 9.3% fewer hypertension-related emergency department visits and hospitalizations. However, they also had 7.2% more primary care visits and a $274 increase in total hypertension-related spending per patient. The benefits were most pronounced among patients with poor baseline medication adherence. The researchers concluded that while RPM shows promise in improving hypertension care outcomes, its current implementation may need refinement to improve cost-effectiveness.

This study shows that RPM does produce the desired effects in a hypertension patient population, but may not lead to net cost savings for Medicare or other payors. This issue can be solved by ensuring providers are operating the program effectively and “not just billing,” being more targeted to patients who can benefit most, and increasing or decreasing the intensity of the clinical services based on patient condition. RPM-based care models are being explored across a wide range of conditions where cost-effectiveness and acute care avoidance may be stronger or weaker.

How RPM Care Models Lead to Outcomes: the Theory

There are a few key components that lead to the theorized and actual effects of RPM care models:

• Early Detection: Continuous monitoring allows providers to identify concerning trends before they become emergent situations requiring hospitalization.

• Rapid Response: When combined with clear escalation protocols, RPM enables swift intervention when problems are detected. This is a very proactive form of care rather than waiting for the patient to show up at the office or in the hospital.

• Patient Engagement: Regular monitoring can increase patients' awareness and involvement in their health management. Patients do report better self-monitoring behaviors and adherence to treatment when monitored.

• Care Coordination: RPM provides a structured framework for ongoing communication between patients and care teams. The process of monitoring and reviewing data can lead to more consistent patient health review and communication.

• Data-Driven Care: Access to RPM data allows for more informed clinical decision-making and preventive intervention. Physicians and other clinicians have longitudinal data instead of cross-sectional data to make better dosage and treatment decisions. This is really important for diabetes and hypertension care in particular due to the number of medications to choose from in these conditions, but is also relevant for heart failure patients wherein diuretics may need to be carefully dosed.

Quality and Implementation Matter

The mixed evidence points to an important reality: not all RPM programs are created equal. The effectiveness of RPM in reducing acute care utilization appears highly dependent on both program design and implementation quality. Key differentiating factors include:

• Monitoring Intensity: Programs vary significantly in the frequency and comprehensiveness of data collection. More intensive monitoring may enable better early detection, but must be balanced against patient burden and alert fatigue.

• Clinical Response Protocols: The presence of clear protocols for responding to concerning data trends is critical. Without defined intervention pathways, monitoring alone may not translate to improved outcomes.

• Integration with Care Teams: RPM is most effective when well-integrated into existing clinical workflows and care team structures rather than operating in isolation.

• Patient Selection: Careful selection of appropriate patients most likely to benefit from RPM is important for program success. A selection bias does occur where patients who are more likely to care about their health opt-in to RPM, but may not be those at highest risk of future deterioration.

• Technology Platform: The specific capabilities and usability of the RPM technology platform can significantly impact both patient and provider engagement. The quality of device data, the ability to integrate into electronic health records, and the ability to support workflows are critical.

• Support Services: Complementary services like patient education, regular check-ins, and technical support appear important for maximizing RPM effectiveness.

The findings point to the conclusion that RPM can reduce acute care utilization, but success requires thoughtful program design focused on these key elements rather than just technology deployment. Programs that combine appropriate technology with robust clinical protocols, care team integration, and patient support services are most likely to demonstrate meaningful reductions in hospital and ED utilization.

Collecting the data for the sake of billing for the remote physiological monitoring CPT codes is not going to result in positive clinical outcomes (although there are self-care benefits on the patient side from the monitoring alone).

Future Directions for Remote Patient Monitoring

As RPM technology continues to advance and adoption grows, particularly accelerated by the COVID-19 pandemic, health care organizations have an opportunity to build on lessons learned about effective implementation. Future research should focus on identifying which program elements and patient populations offer the greatest potential impact on acute care utilization.

Additionally, economic analyses considering both the costs of RPM program implementation and potential savings from reduced acute care use will be important for healthcare systems evaluating these initiatives. While current evidence suggests RPM can reduce costly hospital stays and ED visits in well-designed programs, the overall return on investment requires careful analysis.

In conclusion, while RPM shows promise for reducing acute care utilization, realizing this potential requires careful attention to program design and implementation. The evidence suggests RPM can decrease hospital admissions and ED visits when properly executed, but success depends more on the quality of the surrounding clinical program than on the monitoring technology alone. As health care systems continue expanding RPM initiatives, as medical device manufacturers add IoT technologies to their devices, focusing on evidence-based best practices for program design will be critical for achieving meaningful reductions in acute care use.