Heart failure and COPD remote monitoring programs live on a mix of vitals and PROMs. Weight, blood pressure, pulse oximetry, and spirometry are the numeric side. Symptom scores like the KCCQ for HF and the CAT for COPD are the patient-reported side. The programs that survive contract renewal are the ones where both streams land in a coherent data model that a care manager can actually read at 8 a.m. The six platforms below cover the current landscape, with notes on where each one fits.
The 6 Platforms Worth Comparing
- Validic. Device connectivity is the flagship. Pipes wearable and home-monitor vitals into any downstream system with a defensible list of supported peripherals. PROMs are supported through a partner survey engine, not a first-party form builder. Where it shines is the device breadth; where it falls short is the native form logic for symptom scores.
- Rimidi. Condition-specific dashboards for HF, COPD, diabetes, and hypertension. Comes with baked-in PROMs libraries and a care-management workflow layer. FHIR export runs through an integration engine. Popular with mid-market health systems that want a hosted stack.
- Formbox. A FHIR-native forms engine that sits inside a broader Aidbox deployment for teams already running FHIR. In the RPM context, this pattern shows up when a program wants the PROMs schema and extraction to live in the same server as the vitals Observations. Systems such as Formbox rely on a terminology server such as Termbox to resolve LOINC bindings for scores like KCCQ-12 or CAT at populate time, which keeps the coding side consistent across sites. Device connectivity is handled by a separate connector layer, so the fit is best when the team owns that piece.
- CipherHealth. Engagement-first stack with a strong outbound channel mix (SMS, IVR, voice). PROMs delivery is a supported use case. Data lands in a CipherHealth-native schema with FHIR export as an add-on. Care coordination workflows are the sales draw.
- Twistle by Health Catalyst. Pathway automation with PROMs built into the messaging cadence. HF and COPD templates ship with the product. Reasonable pick for teams that already run on Health Catalyst.
- Athenahealth patient engagement module. If the practice already runs on athenaOne, the built-in module handles PROMs delivery inside the existing patient portal. The trade-off is limited flexibility on the FHIR side and a schema that lives inside Athena.
Programs that want to prototype the PROMs schema before committing to any of these can build the Questionnaire in form-builder.aidbox.app, watch the QuestionnaireResponse render, and validate the extraction logic against a test Bundle. That is a cheap way to de-risk the schema question.
The recurring pattern is that no single vendor is best at both device connectivity and PROMs. The programs with the cleanest data usually pair a device layer (Validic, or a purpose-built connector) with a forms engine that owns the Questionnaire and Observation extraction.
HF and COPD Data-Model Specifics
Heart failure programs typically want KCCQ-12 or KCCQ-23 every one to two weeks plus daily weight and blood pressure. COPD programs typically want the CAT monthly plus daily pulse oximetry and adherence checks on inhalers. Both patterns land in FHIR the same way: PROMs answers extract to Observations coded with LOINC, vitals extract to Observations coded with LOINC and UCUM units, and both link back to the Encounter or the RPM enrollment resource.
Where the programs quietly fail is on the joining logic. If the PROMs and the vitals live in two different schemas, the care manager sees two dashboards. If they live in one FHIR store keyed on the same Patient and Encounter, the dashboard is one query. That is the architectural decision that shapes everything downstream.
For adjacent context, medical form builders for US digital health 2026 buyers guide covers the underlying form-builder landscape, and 7 FHIR form builders that actually handle long-form surveys covers the long-instrument pattern that KCCQ-23 and CAT both fall into.
For the broader RPM and forms-integration context, more FHIR implementation patterns is where the adjacent evaluations sit.
The platform that fits your program is the one whose native data model matches how the care manager reads the morning queue. Everything else is negotiable.