Epic Integration for Vision Screening Medical Device

Client Industry

A medical device company specializing in ophthalmic screening technology, serving pediatric clinics, school health programs, & primary care facilities

Enhancements

  • Bidirectional device-to-Epic data pipeline
  • Real-time encounter & order retrieval
  • Patient-matched screening initiation
  • Structured observation data visible within Epic Flowsheets

Services Delivered

  • Epic FHIR API integration for encounter/order retrieval & patient demographics
  • HL7v2 Incoming Clinical Documentation Flowsheet Interface.
  • Medical device connectivity & data mapping architecture
  • Interoperability testing & Epic community-ready assessment

The Tech Stack

  • Epic FHIR R4 APIs
  • HL7v2 Messaging Protocol
  • Python / Node.js
  • PostgreSQL
  • AWS (EC2, S3)
  • Docker
  • REST APIs

Project Overview:

epic-integration-overview
Nurses spend a significant portion of their shifts documenting and retrieving patient data inside the EHR, reducing time available for direct patient care. In many clinics, vision screening results are still recorded on paper and manually entered into Epic Flowsheets later, creating documentation delays, transcription errors, and workflow slowdowns during high-volume patient visits.
For medical device companies, the challenge extends beyond workflow inefficiency. With Epic powering a large share of U.S. hospital systems, devices that cannot integrate directly into Epic often remain outside the clinical workflow where adoption decisions are made. Folio3 Digital Health developed a complete device-to-Epic integration that automated patient matching and vision screening data transfer directly into Epic Flowsheets, eliminating manual entry and making the solution deployment-ready for health systems using Epic.
Manual Data Entry

Nurses manually transcribed device readings into Epic Flowsheets after every screening

Lack of Patient-Encounter matching

No automated association between screening results and the correct patient encounter

Transcription Errors

Risk of transcription errors during high-volume screening sessions in pediatric clinics

Data Silos

Device data remained invisible to providers reviewing the patient chart within Epic

Ecosystem Distribution Barriers

The product could not be listed or distributed through Epic's App Orchard ecosystem

Missing Integration Standards

No HL7 or FHIR connectivity existed between the device software and Epic

Solutions We Delivered

Real-time Encounter & Order Retrieval from Epic

Real-time Encounter & Order Retrieval from Epic
Patient-matched Screening Initiation

Patient-matched Screening Initiation

Automated Results Push

Automated Results Push
Structured data retrieval through Epic FHIR Observation APIs

Structured data retrieval through Epic FHIR Observation APIs

Epic Community Readiness

Epic Community Readiness

Impact

epic-integration-impact

Looking to develop an AI-powered diagnostic app or scale your healthcare innovation?

Our Tech Stack

Docker

Django

Node JS

Postgres

PostgreSql

AWS

EC2

EC2

S3

S3

FHIR

Epic

Epic

HL7v2

AI/ML