Between 2019 and 2022, the number of US Medicare enrollees receiving remote patient monitoring rose more than tenfold, from about 55,000 to about 570,000. Medicare payments for it grew from roughly $15 million to about $300 million. Those figures come from a September 2024 report by the Office of Inspector General at the US Department of Health and Human Services.
The same report contained a less celebrated finding. About 43% of enrollees who received remote monitoring did not receive all three of its components: device setup and education, the device supplying data, and treatment management by a clinician. Medicare also often could not tell who had ordered the monitoring in the first place.
That combination, explosive growth and patchy delivery, is not an accident or a sign of a few bad actors. It is what you would predict from how remote monitoring is paid for. The payment system rewards the transmission of data. The clinical benefit, where it exists, comes from someone acting on it. Those are two different things, and the economics of remote monitoring are mostly about the gap between them.
What the payment actually buys
Medicare created dedicated billing codes for remote physiologic monitoring in 2019. The structure is worth understanding, because it shapes everything that followed.
There is a payment for initial setup and patient education. There is a monthly payment for supplying the device and recording data, which historically required at least 16 days of readings in a 30-day period. And there are separate payments for time spent by clinical staff on treatment management, including interactive communication with the patient.
On paper, this is sensible: the device, the data and the clinical work are each paid for. In practice, the device and data payments are the most predictable, the easiest to scale and the least dependent on scarce clinician time. A company can ship a blood pressure cuff, confirm that readings are arriving, and bill every month. Turning those readings into changed treatment requires a nurse or physician to look at them, decide something and contact the patient. That part is slower, harder to scale and the first to thin out.
The OIG finding that many enrollees lacked one of the three components is the predictable result. The report also noted that both OIG and the Centers for Medicare and Medicaid Services had raised concerns about fraud in remote monitoring.
The evidence says the response is the intervention
The clinical research on remote monitoring is often summarised as “mixed.” A more useful reading is that it is mixed along a clear line.
Take heart failure, the condition where remote monitoring has been studied most. The BEAT-HF randomised trial, published in JAMA Internal Medicine in 2016, combined pre-discharge education, nurse telephone coaching and remote monitoring of weight, blood pressure, heart rate and symptoms for older adults after a heart failure admission. It did not reduce 180-day readmissions.
Two years later, the TIM-HF2 trial, published in The Lancet, randomised more than 1,500 heart failure patients in Germany to remote patient management or usual care. The remote management arm included daily transmission of measurements to a telemedical centre staffed around the clock, which could act on the data and coordinate with patients’ own physicians. All-cause mortality was 7.86 per 100 person-years in the remote management group and 11.34 in the usual care group, a hazard ratio of 0.70.
It is not possible to explain the difference between two trials from a single feature. Populations, health systems and study designs differed. But the contrast illustrates a pattern that recurs across the field: monitoring that feeds into a responsive, well-staffed clinical team is more likely to help than monitoring that mainly generates data. The device is not the treatment. The team’s response is.
That is also what makes effective monitoring expensive. A telemedical centre staffed around the clock is a very different cost structure from a cuff and a monthly data fee.
The uncomfortable incentive
The way remote monitoring is paid for creates a quiet mismatch of interests.
For a vendor or a practice, the most profitable patient is one who transmits data reliably and needs little intervention. That patient generates the monthly device payment with minimal clinical time. The patient who would benefit most, whose readings are unstable, who needs medication changes and phone calls, is also the most expensive to manage.
This means the business model tends to select for patients who are easy to monitor rather than those who most need it. It also rewards enrollment volume. A programme that monitors thousands of stable patients can look financially successful and clinically active while changing very little about their outcomes.
The incentive also shapes where monitoring is offered. Third-party companies can partner with practices, provide devices and staff, and share the revenue. That can extend capacity to practices that could not otherwise run a programme. It can also separate the monitoring from the clinician who knows the patient, which is exactly the link that makes a response meaningful.
The strongest counterargument
Defenders of the current approach have a fair point. Before 2019, there was almost no way to get paid for remote monitoring in traditional Medicare, and very few practices did it. Separate codes for device supply made it financially possible to start. Some patients who now have regular blood pressure data at home would otherwise have had a reading once every few months in clinic. Even imperfectly delivered monitoring may improve patient engagement and self-management.
That argument partly holds. A payment system has to make a service viable before it can make it good. And rigid requirements, such as the 16-day data threshold, may have excluded patients who needed shorter bursts of monitoring.
Medicare appears to have taken that criticism on board. In its payment rule for 2026, finalised in late 2025, it added a new code for device supply when data is collected on 2 to 15 days in a 30-day period, paid at the same rate as the existing 16-day code, effective from January 2026.
That change will make monitoring more flexible. It may also widen the gap described above. If a device payment is available for as few as two days of data, the minimum threshold for generating revenue falls, while the requirement to act on the data is unchanged. Whether that improves care or simply expands billing will depend on how closely payers watch the treatment management component.
A worked example: two programmes, same revenue
Imagine two practices, each enrolling 500 patients with hypertension in remote blood pressure monitoring.
In the first, a vendor supplies cuffs and a dashboard. Readings flow in. A medical assistant checks that patients are transmitting and sends reminders to those who are not. Once a month, a physician glances at a summary. Most patients’ readings are similar to last month. Medication is rarely changed between visits.
In the second, a nurse reviews readings weekly against agreed thresholds. Patients above target get a call within days. A pharmacist, working under a protocol, adjusts doses. Patients who remain uncontrolled are brought in sooner.
Both programmes can bill for the device and data. The second bills more for treatment management, but it also spends much more on staff time. Unless the practice shares in savings from avoided strokes and admissions, which under fee-for-service it mostly does not, the first programme may be the more profitable one.
Only the second is likely to change blood pressure. That is the economics of remote monitoring in a single comparison.
Second-order effects
The incentive mismatch has consequences beyond individual programmes.
One is who gets monitored. Patients with smartphones, stable housing, reliable connectivity and the confidence to use a device are easier to enrol and more likely to transmit data every day. Patients with unstable lives, limited digital skills or language barriers take more staff time to onboard and support. A programme optimised for device-days will drift toward the first group, even though the second often carries more uncontrolled disease.
Another is what happens to trust. When patients receive a device, send readings for months and never hear anything back, they reasonably conclude that nobody is watching. Some stop measuring. Others keep measuring and assume that silence means their numbers are fine, which may not be true. Either way, the next programme, including a good one, starts with a more sceptical patient.
A third is the data itself. Millions of home readings that were never acted on could still be valuable for research and for understanding real-world disease control, but only if they are captured in a form linked to the clinical record. Much of it sits instead in vendor dashboards, which quietly reproduces the interoperability problem in a new place.
What this means for different players
Payers should tie payment more closely to demonstrated clinical response. Options include requiring documented treatment management to bill device payments beyond an initial period, auditing the share of enrollees who receive all components, and recording the ordering clinician, as OIG recommended. In value-based contracts, remote monitoring can be judged on outcomes such as blood pressure control or admissions rather than on enrollment.
Health system leaders should resist judging programmes by enrolment and device-days. The useful metrics are how quickly abnormal readings get a response, how often treatment changes as a result, and whether clinical outcomes improve. A programme that cannot report those numbers is probably not measuring them.
Clinicians should be wary of monitoring that arrives without the staffing to act on it. Unreviewed data can create liability as well as noise. If an alarming reading was transmitted and nobody responded, the record shows that it was available.
Ministries and insurers outside the United States looking at remote monitoring should notice what the US experience shows. Paying for devices and data is the easy part to design and the easiest part to scale. Paying for response, and ensuring it happens, is where the value lies and where most of the design effort should go.
Funders and investors should ask companies not how many patients they monitor but how many they have helped reach a clinical target, and at what staffing cost.
What to watch next
Three things will reveal whether remote monitoring matures or stays stuck in the data business.
First, how the new short-duration codes are used in 2026. A sharp rise in device billing without matching growth in treatment management would be an early warning sign.
Second, whether oversight follows the OIG’s recommendations, particularly on identifying who ordered monitoring and whether all components were delivered.
Third, whether remote monitoring becomes embedded in risk-bearing arrangements, where organisations are paid for outcomes. In those settings, the incentive to act on data is built in, and the economics start to line up with the clinical logic.
The takeaway
Remote patient monitoring is not a scam, and it is not a miracle. It is a service whose payment design rewards the cheap, scalable part of the work and leaves the expensive, valuable part to goodwill and staffing levels. The growth in Medicare spending tells us that paying for data works: you get more data.
If health systems want better outcomes, they have to pay for, staff and measure the response. Otherwise remote monitoring will keep doing exactly what it is paid to do, which is to transmit numbers to a dashboard that nobody has time to read.
If your organisation runs remote monitoring, what share of abnormal readings get a clinical response within a week, and do you know the number? We’d like to hear from programmes that track it.
