Hopena Health builds digital adaptations of evidence-based clinical practice guidelines — standards-based decision support that runs inside the electronic health record systems already deployed in LMIC facilities.
A clinical guideline is only as useful as the workflow that delivers it. In settings with limited informatics capacity, the distance between a published recommendation and a clinician acting on it at the point of care is wide — and it's where preventable harm accumulates.
Hopena Health closes that gap by building digital adaptations of clinical practice guidelines: machine-readable, executable artifacts that surface the right recommendation at the right moment in the patient encounter. The work is built on FHIR and CQL, deployed into the EHR platforms already used in LMIC settings, and designed so the underlying guideline logic stays transparent, inspectable, and shareable across jurisdictions.
Clinical decision support shouldn't be locked inside any single EHR — especially in settings where deployments are heterogeneous and resources are scarce. Every technical choice prioritizes openness, portability, and transparency.
HL7 interoperability resources
Clinical Quality Language
PlanDefinition / ECA rules
WHO Digital Adaptation Kits
HL7 FHIR implementation guides
Dan Heslinga is a primary care physician and health IT developer focused on computable clinical decision support using FHIR and CQL.
His current work, aligned with the WHO SMART Guidelines initiative, implements the WHO cervical cancer screening and treatment guidelines (2021) as FHIR R4 decision support — a concrete instance of the broader bet that LMIC guideline adoption can be accelerated by treating guidelines as software.
Before this work, he spent 20+ years in clinical practice (emergency medicine and family medicine) while progressively building clinical reminder and care plan systems — first customizing commercial EMRs, then building standalone systems, eventually moving to standards-based approaches with CDS Hooks and CQL. The consistent thread has been the same problem: getting evidence-based guidelines to the point of care in computable form.