An elderly care remote patient monitoring company needed a mobile app and provider portal built on a Medplum FHIR-native backend. ConnectHealth built the data mapping and normalization layer that turned raw BLE device output and FHIR resources into structured application data, so the engineering team could focus on the patient experience, care manager portal, and billing workflows.
Talk to Our TeamElderly care remote patient monitoring platform
Device-to-FHIR and FHIR-to-application data mapping layer
Medplum FHIR backend, BLE-connected devices, AWS customer VPC
Delivered
ConnectHealth reduced the custom mapping and normalization work needed to turn device-generated vitals into data the application layer could use.
The platform needed an elderly-friendly patient experience, centralized care management, BLE-connected devices, and CPT billing, all running on a FHIR-native backend. That created two separate mapping problems.
Blood pressure, heart rate, and other vitals arrived as raw BLE output and had to be normalized into structured FHIR Observation resources before anything downstream could use them.
Once vitals existed as FHIR data in Medplum, they still needed reshaping into the specific models the care manager portal, admin dashboard, and billing module consumed, without hand-writing mapping logic for every data type.
Built on a Medplum FHIR-native backend with a bidirectional mapping layer connecting devices, clinical data, and the application.
The elderly-optimized mobile experience, BLE device pairing, care manager portal, admin portal, CPT billing, video calls, chat, reminders, and time tracking were all built as custom application capabilities on top of ConnectHealth's mapping layer.
ConnectHealth's mapping engine normalized incoming BLE device readings, blood pressure, heart rate, and other vitals, into structured FHIR Observation resources. That removed the need for custom parsing code per device type.
ConnectHealth mapped FHIR resources, Observation, Patient, and Encounter, from the Medplum backend into the platform's internal application models. The care manager portal, admin portal, and billing module could consume clinical data without each team writing its own transformation layer.
Helix AI translated the device-to-application data flow requirements into a staged implementation plan the integration engineer could review and approve before it was built out, reducing manual workflow design time.
ConnectHealth was deployed inside the customer's own AWS VPC, keeping vitals and patient data within customer-controlled infrastructure while supporting HIPAA-ready controls.
See how ConnectHealth's mapping engine turns device and FHIR data into models your application team can use.
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