Remote monitoring — from pilots to performance

‍How health systems turnRPM into repeatable, measurable care — and where to focus next
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Welby Health | By Seth Merritt, CEO

Remote patient monitoring (RPM) stopped being a gadget experiment years ago. Today it’s a real clinical service line — and the difference between a pilot that looks good on slides and a program that actually moves the needle is integration, escalation design, and honest math on ROI.

Below is a clear-eyed snapshot of where RPM and hospital-at-home (H@H) stand today, what the evidence actually tells us, and the practical moves health systems must make to shift from promising pilots to sustainable performance.

Where we are (the hard facts)

• Policy and economics are tightening. CMS preserved key telehealth flexibilities (including audio-only and H@H extensions) through September 30, 2025, but 2025 PFS base rates dropped ~2.93% — a real headwind for gross-margin economics and the ROI calculus for RPM programs.
• Hospital-at-Home is scaling. As of mid-2025 roughly 400 hospitals across 142 systems hold H@H approval, and CMS’ 2024 assessment associated H@H with lower 30-day mortality, lower readmissions, and strong patient experience versus inpatient comparators.
• The evidence is maturing — not magical. Systematic reviews and meta-analyses show RPM improves safety and adherence and trend toward reductions in admissions, readmissions, length of stay (LOS), and non-hospital costs. Sensor-alert programs report roughly 9–10% reductions in hospitalizations, with modest signals for mortality benefit. But the effect size depends heavily on program design and operational follow-through.

What works — and what doesn’t

• Design matters more than devices. Trials in hypertension make the point bluntly: sending devices or tweaking enrollment language alone rarely moves outcomes. Programs that pair measurement with workflow—EHR-anchored follow-up, clinician touchpoints, and escalation plans—are the ones that deliver clinical and economic value.
• Targeted cohorts show the strongest returns. The best evidence and largest effects are in heart failure (HF), hypertension (including postpartum HTN), and selected perioperative pathways. Home-hospital and virtual-first IV diuresis programs have shown low readmissions and improved outcomes when clinical escalation was tightly defined and operationalized.
• Safety ceilings exist, but are manageable. Home-hospital data show roughly 10% of HF home-hospitalizations may require transfer back to brick-and-mortar care; low mean arterial pressure predicted escalation. That’s not a failure — it’s a predictable safety envelope you can design for.

Selected snapshots (real-world signals)

• H@H scale & outcomes: 400 hospitals, 142 systems approved; CMS links H@H with lower 30-day mortality/readmissions and spend versus inpatient care.
• HF safety: ~10% transfer rate from HF home hospital; MAP predicted escalation.
• HF outcomes: Virtual-first IV diuresis and titration at home led to low readmissions in major centers.
• Hypertension RPM: Longitudinal programs achieved ~75% BP control at 12 months in system-level implementations, with independent evaluations showing clinical and economic gains.
• Postpartum HTN: RPM reduced readmissions and increased adherence to care standards.
• Perioperative/orthopedics: Home monitoring after joint replacement reduced readmissions and ED use in several studies.
• Community hospital HF program: AI-enabled RPM reported a 50% reduction in 30-day readmissions in one community system — promising, but dependent on local workflows and escalation protocols.

The net takeaway

RPM and home-hospital models can cut mortality, readmissions, LOS, and post-discharge spending — but only in targeted cohorts and when programs are built as clinical services, not device experiments. The strongest, most reproducible results come when you combine three elements:

1. Tight patient selection. Focus on cohorts where early intervention changes outcomes (HF, HTN, postpartum HTN, select periop).
2. Operational integration. EHR-anchored enrollment, automated but clinically meaningful alerts, and defined clinical actions for each alert.
3. Escalation and capacity. Clear escalation paths and staffed workflows that match the program’s clinical intensity (and the known safety ceiling).

Skip any of those — and your results will dilute.

What leaders need to do now (straightforward, actionable)

• Stop treating RPM as an IT project. It’s a clinical and operational redesign. Give clinical ops and nursing leadership the budget and decision authority.
• Build the escalation playbook first. Define thresholds, ownership, and transfer protocols before you press “ship” on devices.
• Anchor RPM in the EHR. Enrollment, bidirectional notes, and discrete actions inside the chart are non-negotiable if you want sustainable follow-up.
• Model ROI with tighter assumptions. Factor in CMS rate pressures, realistic device/labor costs, and the real probability of escalation. Don’t assume optimistic, pilot-level results will scale without increased marginal costs.
• Measure what matters. Readmissions, 30- and 90-day mortality, LOS, post-discharge spend, and patient experience — tracked by cohort and by escalation pathway — tell you if the program is working or just generating data.

Looking ahead: where RPM wins next

RPM won’t be a universal answer for every patient — and we shouldn’t pitch it that way. Its future is as a clinical amplifier: earlier detection, better adherence, and safer, lower-cost care in patients where remote intervention changes the clinical trajectory. Combine that with better predictive analytics and tighter home-hospital operations, and you get scalable impact rather than one-off wins.

How Welby thinks about it

At Welby we build RPM programs the way clinicians build care plans: start with the patient and the clinical decision you want to influence, then design measurement, workflow, and escalation to support that decision. That means fewer pilots that collect lots of data and more programs that change outcomes and cash flow.

If your team is still debating whether to ship more devices or redesign follow-up workflows — choose follow-up. Devices collect signals; the system translates them into outcomes. Design the system first.

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