Integrating a Remote Patient Monitoring Platform with Your EHR: Challenges & Best Practices

Understanding EHR Ecosystems: Epic, Cerner & Others

Integrating your remote patient monitoring platform into an EHR isn’t a one-size-fits-all task. Every EHR vendor has its ecosystem, development tools, and quirks. Understanding how these systems differ—and where they align—can save you months of back-and-forth during implementation.

Epic (Open.epic)

Epic’s developer environment, known as Open.epic, provides access to a set of FHIR-based APIs and some SMART on FHIR launch capabilities. It’s fairly mature, widely adopted in large hospital systems, and offers a clear workflow for sandbox access and production rollout.

However, integration approval can be slow, and custom workflows (like ingesting RPM device data directly into patient flowsheets) often require coordination with hospital IT. You’ll also need to map your platform’s output to Epic’s defined Observation resources to make the data visible in the right modules.

Cerner (Now Oracle Health)

Cerner’s Ignite APIs also support FHIR, but the experience can vary depending on whether you’re dealing with traditional Cerner Millennium setups or newer Oracle transitions. Cerner systems are more fragmented across providers, which sometimes complicates testing and support.

Cerner allows device data ingestion, but the implementation relies heavily on standardizing payloads and working closely with their developer network. You’ll often need to customize the integration flow per health system.

Other EHRs: Allscripts, Meditech, eClinicalWorks

Outside of Epic and Cerner, many RPM solutions deal with mid-market EHRs like Allscripts or eClinicalWorks. While these platforms are often more flexible, their API coverage can be limited. In some cases, you may need to work with HL7 v2 interfaces or flat file transfers, which add complexity and latency to the process.

FHIR Resources That Matter for RPM

Regardless of vendor, most successful RPM-EHR integrations revolve around a handful of FHIR resources:

• • Observation (for vitals, symptoms, device output)
  
• • Device (to identify and reference the source device)
  
• • Patient (to link data to the correct record)
  
• • Encounter (to associate readings with a specific visit or care episode)
  

Using these resources consistently helps maintain interoperability across EHR systems and allows clinical teams to find the data where they expect it.

Where Mindbowser Has Helped

We’ve worked with digital health companies that needed real-time RPM data integrated into hospital EHRs without disrupting workflows. In several cases, we’ve helped configure device ingestion pipelines that conform to Epic and Cerner’s FHIR models, using a modular approach that allows our clients to scale to multiple health systems without reworking the core architecture.

EHR Integration Best Practices for RPM Platforms

Once you understand the landscape, the next step is building the right approach. Integrating your remote patient monitoring platform with EHRs is not just about connecting APIs—it’s about making sure the data flows in a way that supports real-world clinical use. Here are the best practices we’ve found that consistently lead to smoother rollouts and better outcomes.

Use SMART on FHIR for secure, standardized integration

If you’re building a frontend experience that launches inside the EHR (like a provider-facing dashboard), SMART on FHIR offers a standard method for authentication, authorization, and embedding. It also ensures your app inherits the EHR’s security policies and patient context, avoiding extra logins and lookup steps.

Related read: Building a SMART on FHIR App for Seamless EHR Integration for Remote Care

Stick to structured FHIR resources

For RPM data—especially vitals like heart rate, oxygen saturation, or weight—use well-defined FHIR resources like Observation, Device, and Patient. Avoid pushing custom payloads or free text, which makes the data hard to query, analyze, or bill against later.

Modular integration beats monolithic setups

Break your integration into logical stages:

1. Data Sync – capture device data and clean it
2. Event Triggers – push only relevant updates (e.g., abnormal readings, threshold breaches)
3. Visualization – map the data to where clinicians expect to see it in the EHR

This modular flow keeps your system resilient and easier to troubleshoot or upgrade.

Respect audit and consent flows

Every PHI touchpoint—especially when third-party RPM devices are involved—needs proper audit logging and patient consent tracking. Build this into your system from day one. It’s not just about HIPAA compliance; it also builds trust with providers.

Test in the sandbox first, but don’t stop there

EHR vendors often provide sandbox environments for initial development. Use them, but don’t assume that sandbox success means production readiness. Always validate in staging environments with real workflows and simulated patient data.

Involve clinical staff early

Integration should never be done in a vacuum. Include nurses, physicians, and care coordinators when planning where and how RPM data should appear in the EHR. It’s the difference between building a tool that gets used and one that gets ignored.

Continuously test for edge cases

Plan for gaps in internet connectivity, device sync failures, delayed readings, or mismatched patient IDs. These edge cases often surface only after launch, so simulate and document how your platform handles them ahead of time.

Solution accelerators like AutoConfirm AI streamline the scheduling workflow by syncing patient confirmations with EHR calendars—reducing manual coordination and improving operational flow.

Case Example

Real-World Integration with remote patient monitoring platform and RPMCheck AI

Our one strong example of successful EHR integration comes from a remote patient monitoring platform designed for elderly care. The platform’s aim wasn’t just to collect vitals from Bluetooth-enabled medical devices but to ensure those insights were accessible and actionable for care teams, administrators, and compliance staff across various healthcare settings.

What We Built

We developed an integrated system with three components:

• A mobile app that syncs vitals from Bluetooth devices like BP monitors and pulse oximeters in real time.
• A web portal for care managers to view patient trends, flag concerns, and manage interventions.
• An admin dashboard to handle appointments, compliance tracking, and CPT billing data—all aligned with EHR formats.

Behind the scenes, the platform used FHIR-based APIs to make patient data EHR-ready. We mapped device readings to standardized observation resources and connected them with corresponding patient and encounter data to ensure every data point had clinical context.

Built-in CPT Compliance

We also implemented automated tracking of RPM usage patterns and device provisioning to support Medicare CPT codes. This allowed the client to generate documentation that could be ingested by billing modules in EHRs, saving administrative time and ensuring claims were audit-ready.

Introducing RPMCheck AI

To take it a step further, we introduced RPMCheck AI, one of our voice-based solution accelerators built under the QConnect AI framework. It enables proactive patient check-ins using conversational AI, gathering updates on symptoms, medication adherence, or general well-being. The AI agent logs structured responses directly into the RPM platform and prepares summaries that can be pushed to the EHR.

By integrating both passive (device-generated) and active (patient-reported) data streams, the system gives providers a fuller picture of each patient’s condition, all within their existing workflow.

✅ The result? Over 90% patient engagement, reduced response time from care teams, and a platform that fits neatly into the day-to-day operations of skilled nursing and home health staff.

Measuring Success Post Integration

Once your remote patient monitoring platform is integrated with the EHR, the job isn’t done. The real test is how well that integration performs over time and whether it’s improving clinical outcomes and operational efficiency without adding more friction.

Here are the key areas we recommend monitoring:

Data latency

How long does it take for a data point—say, a blood pressure reading—to appear in the EHR after it’s captured by a device? A few seconds might be acceptable. A few hours isn’t. Delays can impact clinical decisions, especially for high-risk patients.

Make sure to track:

• Average time from device capture to EHR entry
• Percentage of data delivered within expected timeframes
• Outliers that might signal sync issues

Sync accuracy

Even one mismatched patient ID or duplicated vital entry can create confusion—or worse, clinical errors. Build regular QA audits to validate that the data you push to the EHR:

• Matches the correct patient record
• Falls within expected clinical ranges
• Doesn’t result in duplication or overwrites

Some of our clients have implemented periodic “shadow logging,” where data is logged both in the RPM dashboard and the EHR for comparison during initial rollout phases.

Clinical adoption

If the care team isn’t using the data, your integration isn’t delivering value, no matter how technically clean it is. Track:

• How often clinicians view RPM entries within the EHR
• Whether they act on alerts or notes generated from RPM data
• Feedback from end users on data relevance, clarity, and placement

It’s worth holding short check-ins with clinical teams in the early weeks post-deployment. Their feedback will tell you whether the data fits into the way they work.

Dashboards and alerts

Having a visual layer that tracks the status of integration in real time—data in, data errors, data matched—can help your support team respond quickly. Dashboards with drill-down capabilities also help identify patterns like:

• Devices are consistently failing to sync
• Drop-offs in patient adherence
• Sites or teams where data isn’t being accessed

Feedback loops

Finally, integration isn’t static. Clinical workflows evolve. RPM programs scale. APIs change. You need a process in place to gather regular feedback from users and stakeholders, prioritize improvements, and revalidate integration points on a rolling basis.