North America Remote Patient Monitoring Systems Market Size & Share Analysis - Growth Trends and Forecast (2026 - 2031)

Desk Research

Desk research was used to set the boundaries of what counts as RPM systems and to build a realistic demand base by country (United States, Canada, and Mexico). We relied on public healthcare statistics and adoption signals from government health agencies and national statistical offices, payer and public health publications, and trade association materials related to connected health and medical devices.

To convert those demand signals into a market value, we also reviewed sources such as customs and trade statistics for relevant device categories, peer-reviewed clinical and digital health journals for use patterns, and company filings and investor presentations for product mix and pricing direction. In parallel, a paid subscription focused on company financials and another covering patents were used selectively to cross-check supplier exposure to RPM and to confirm where innovation activity was concentrated. These desk research sources are illustrative only, and many other public references were also consulted during data collection, validation, and clarification.

Primary Interviews and Surveys

Primary interviews and surveys were used to pressure-test the desk assumptions on what is being purchased as an RPM system versus a broader monitoring or telehealth bundle. We spoke with a balanced mix of device and platform stakeholders, care delivery decision-makers, and channel participants across North America, then used their inputs to confirm adoption pace by care setting and the typical pricing and replacement cycle for common RPM devices.

Distribution of primary research fieldwork respondents

Our sizing model starts with a top-down demand pool build-up where monitored patient cohorts and care program penetration are translated into expected device and system deployments by country, then into value using typical selling price ranges. The results are corroborated with selective bottom-up checks such as sampled supplier revenue exposure to RPM, channel checks on shipment momentum, and an ASP multiplied by volume approximation for common device types, which helps us adjust for over-counting and gaps.

Key inputs that shaped the model included the size of chronic disease and post-acute patient pools likely to be monitored, RPM program enrollment and adherence patterns, device replacement and upgrade timing, reimbursement and payer coverage direction, and the split between home care and provider-led settings. Because these inputs can move at different speeds, forecasting was done using scenario analysis, and the scenario weights were refined using what interviewees expected for reimbursement stability, provider capacity, and connected device uptake over the next few years. Where bottom-up checks were incomplete, gaps were handled by applying conservative coverage ratios consistent with country-level adoption and procurement feedback.

Outputs were validated by triangulating the final market totals against independent signals such as adoption indicators, reimbursement policy milestones, and the implied per-patient spending level that falls out of the model. Variance checks were run by country and by major use setting, and any sharp jumps were reviewed to ensure they were supported by a clear driver like coverage expansion or pricing changes.

Before sign-off, the work goes through multi-step analyst review so assumptions, arithmetic, and scope boundaries are consistent across the model. Reports are refreshed annually, and interim updates are triggered when material events occur, such as major policy changes or notable shifts in care delivery patterns. Right before delivery, we do a final pass to incorporate the latest available public information and any critical re-checks from follow-up calls.

Published values for North America RPM systems often look far apart because researchers do not always count the same things, and they also choose different base years and currency timing. In practice, the differences usually come from what is included as an RPM system, how bundled software and services are treated, and whether the estimate is anchored to monitored patient volumes or to broader connected-care spending.

By tracking adoption and reimbursement signals and refreshing scope cutoffs each update, Mordor Intelligence keeps the estimate focused on RPM systems where device-led monitoring data is transmitted for clinician use, instead of mixing in wider telehealth services or general patient monitoring device markets.

Benchmark comparison

The spread in published numbers is mostly explained by scope and counting rules, not only by growth expectations. When the demand pool, price logic, and inclusions are written down clearly and then checked with real-world adoption and purchasing behavior, the final market value becomes easier to trace and reproduce.