Patient Experiences with Remote Patient Monitoring

The typical patient journey is marked by disparate clinical visits wherein a snapshot of a patient’s condition is used by care teams to develop and manage a care plan. Patients receive, on average, 21.6 minutes of care per visit which is likely inadequate to offer robust, whole-person care. Depending on the condition and the degree of severity, these visits may occur 2, 3, 4, or 6 times a year. However, given the advancement of digital technologies and the ubiquity of  smartphones, this disparate model of care is no longer the most effective.

 

Remote patient monitoring (RPM) utilizes connected medical devices and, often, a smartphone interface that allows for daily clinical data collection from patients wherever they may be located. This data develops into a longitudinal record set that allows care teams to better manage care plans proactively. When done properly and in-line with clinical best practices, RPM programs can offer four major benefits for patients when integrated into a care team’s operations:

 

  • Patient self-monitoring of metrics
  • Patient feels a connection to the care team and has rapid access
  • Care team receives alerts from out-of-range metrics
  • Care team and patient generate better longitudinal data for care plan development

 

Remote patient monitoring is often thought of only in terms related to bullet three. However, the other three bullets are equally, if not more, important with respect to patient outcomes from chronic diseases. Marketing materials and academic literature also primarily focus on the clinical and cost outcomes from the use of RPM-based care models. It is equally, if not more important, to understand the patient experience and perspective from those that participate in RPM-based care models.

Patient-Centered Clinical Evidence

One of the primary benefits of virtual care programs is improvement in patient experience and satisfaction. More convenient and patient-centered program design frequently accompanies virtual care models, where healthcare services have traditionally lacked patient-centered design. Thus, it is important to understand the patient perspective of RPM-based models of care prior to and during implementation.

One systematic review[i] looked at 16 studies facilitated in eight different countries focused on understanding patient beliefs, attitudes, expectations, and experiences with RPM programs. The study included patients living with common chronic conditions such as COPD, heart failure, diabetes, hypertension, and end-stage kidney disease.

Four important outcome themes are important to understand from this review. Patients reported the following:

  • Gained knowledge and improved positive health behaviors (i.e., cognitive and behavioral elements of patient engagement).
  • Improved peace of mind and security from supportive monitoring (i.e., emotional elements of patient’s engagement).
  • Concerns about additional burden and work from monitoring.
  • Fear about the loss of interpersonal connections and being confused by data (i.e., illustrating the importance of human involvement).

This review suggests that patients report gaining disease-specific knowledge, proactive identification of deterioration, improved ability to self-manage their disease, and greater ability to participate in shared decision-making. These are outcomes of significant importance to chronic disease management.

Patients in the study did express concerns that RPM would take away the personal connection to their physicians and the additional burden. It is important to note that this is an important reason that effective RPM programs have a strong level of clinician interaction rather than reliance on data collection alone. Patients still require and request a strong relationship with care providers despite the digitization of some care processes.

[i] R. C. Walker, A. Tong, K. Howard, and S. C. Palmer. “Patient Expectations and Experiences of Remote Monitoring for Chronic Diseases: Systematic Review and Thematic Synthesis of Qualitative Studies.” International Journal of Medical Informatics, 124 (2019): 78–85. https://doi.org/10.1016/j.ijmedinf.2019.01.013

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