The Growth Channel

Studies are conflicted about remote patient monitoring—here's what we think

by Tracy Walsh

The evidence for remote patient monitoring programs is somewhat conflicting. Earlier this year, studies in JAMA and PeerJ evaluating remote patient monitoring at major medical centers found no significant difference between experimental and control conditions for the researchers’ main outcomes. Conversely, Essentia Health has used its RPM program to cut patient readmissions to less than 2% among participating patients (as a point of reference, the national average is 25%).

These results inevitably force health care providers to ask themselves, “Does tracking and monitoring patient biometrics actually improve patient care?” But the answer isn’t as simple as you might think.

The challenge with remote patient monitoring isn’t just finding the right technology platform—it’s the reality of program design and implementation. Effective programs target the right conditions, promote patient adherence to data collection, and ultimately intervene to prevent avoidable ED use or readmissions. To achieve ROI, your program needs to do these three things.

Align platform functionality with clinically relevant data collection

Many programs try to apply remote patient monitoring across a combination of several chronic conditions, often including diabetes, COPD, asthma, hypertension, CHF, and/or behavioral health diagnoses. However, not all RPM platforms are capable of tracking relevant clinical indicators across multiple conditions. And the more data you ask patients to record, the more burdensome the platform and less likely participants will reliably track their biometrics.

Moreover, the academic literature shows some conflicting evidence around the quality and cost impacts of remote patient monitoring broadly applied across chronic conditions. The best case can be made for CHF and COPD, as these conditions more easily are linked to avoidable ED use, admissions, and readmissions. In fact, some of the most successful programs limit enrollment to at-risk patients who have recently been discharged with CHF.

Target patients who are highly engaged and receptive to the technology

Low patient adherence is one of the biggest operational challenges to successfully launching and scaling an RPM program. For example, in the first cited study that found no significant benefit from its RPM program, patients submitted their biometric data less than half the time requested by researchers. In the second study, between 10% and 29% of participants did not record any of their readings.

Poor patient adherence rates may be responsible for the mixed results, and for this reason we suggest defining exclusion criteria like low patient activation/receptivity, cognitive impairment, or limited physical mobility.

Track program metrics that closely map to the organization’s broader strategic objectives

Thirty-day readmissions, patient mortality, and ED utilization are not necessarily the primary outcomes evaluated in most academic publications. For example, the primary outcome reported in the first of the two cited studies is 180-day all-cause readmission. Similarly, in the second study, the primary outcome is all health insurance claims over a six month period.

The target metrics used in remote patient monitoring programs should be easy to track, be attributable to program performance rather than random variation, and correspond to the program’s goals. Otherwise, “insignificant” findings don’t accurately convey meaningful outcomes.

3 key questions for remote patient monitoring

Is remote patient monitoring technically feasible, clinically relevant, and cost effective for your organization? Find out.

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