Wearable Device Integration Services

Most teams start by asking which API to call. The harder questions come later: how consent is captured and revoked, what happens when a user changes phones, how late-arriving data is reconciled, and how a heart rate sample from one device is distinguished from the same reading synced through a second app. A production integration answers these explicitly.

We treat a wearable integration as a small data platform with defined inputs, a canonical internal model, and documented outputs. That structure is what lets you add a second or third device source without rewriting the downstream logic each time.

Device choice drives most of the architecture. Apple HealthKit is on-device only: there is no Apple cloud API, so you need an iOS app that reads HealthKit and uploads to your backend. Google Health Connect is also on-device Android storage with per-data-type permissions, and apps that read health data must complete a health permissions declaration in Play Console. The older Google Fit APIs are deprecated and should not be the basis of new work.

Cloud APIs from vendors such as Fitbit and Garmin let your server pull or receive data without your own mobile app, but they come with their own approval steps. Fitbit's Web API uses OAuth 2.0, and server applications that need intraday data must request access from Fitbit. Garmin's Health API requires an approved business developer application before you can build against it. We help you plan around these lead times so they do not block a pilot.

For clinical programs that need regulated measurements, consumer wearables are often paired with FDA-cleared devices such as cellular blood pressure cuffs, scales and pulse oximeters. See remote patient monitoring integration for how those device types fit into an RPM program.

Raw wearable data is inconsistent in ways that matter clinically. One source reports weight in pounds, another in kilograms. One stores sleep as staged intervals, another as a nightly summary. Timestamps may be UTC, local time without an offset, or device time that drifted. The same step count can appear twice when a watch syncs to both a vendor app and HealthKit.

We map incoming data to a canonical model with UCUM units, explicit timezone offsets and source metadata recording which device, app and platform produced each value. Duplicate samples from overlapping sources are resolved with documented rules rather than silently summed. When data goes to an EHR, each measurement type is mapped to an appropriate LOINC code so it lands as a structured FHIR Observation rather than a free-text note.

Clinicians rarely want every sample. A cardiology team may want resting heart rate trends and flagged irregular rhythm events; an RPM nurse wants today's blood pressure readings and who has not transmitted. We design the summarization and alerting layer with your clinical stakeholders so the EHR receives what is useful rather than a firehose.

Our EHR wearable integration work covers FHIR R4 APIs where the EHR supports writing Observations, HL7 v2 interfaces where it does not, and SMART on FHIR apps for in-context review. The approach depends on your EHR, your interface team's capacity and the workflows you want to support.

Wearable data tied to a patient is protected health information once it enters a covered entity's workflow. We design pipelines with HIPAA-aligned controls: encryption in transit and at rest, scoped service credentials, audit logging of access and changes, data minimization, and retention rules you can configure.

Technical controls are only part of compliance. Whether a deployment meets HIPAA requirements depends on your overall compliance program, your policies, your risk analysis and the business associate agreements in place with each vendor that handles the data. We document the data flows and controls so your privacy and security teams can assess them. More detail is on our HIPAA-aligned wearable integration page.

Work usually starts with a short discovery phase to confirm devices, data types, destinations and regulatory context. From there we produce an integration design, build a working pipeline for one device source end to end, and then extend to additional sources and destinations.

We can build the integration for your team to own, extend an existing platform, or review an architecture you have already started. Before a first call, the integration requirements checklist helps you gather the details that shape scope.