Digital Pain Drawings: Inclusive Web App with Integration into Clinical Systems
Description:
The digital pain drawing web application innovatively records and documents patients' back pain. Using a newly developed gender-neutral, precise anatomical representation, patients can remotely draw and describe the location, spread and quality of their pain. The information is planned to be integrated directly into the clinical information system. This can lead to improved communication with professionals and contribute to more precise diagnoses and individualized treatment plans.
Primary users:
- Back pain patients: can record their pain in the app anytime, anywhere, and download their drawings as a report.
- Healthcare professionals: Receive automated reports that are integrated into the clinical information system in real time, enabling them to support therapy planning and patient care.
How it works:
- Interactive pain drawing: Patients use the intuitive app to document their pain before visiting the clinic.
- Automated reports: The system generates reports that are available for patients to download and can be accessed by professionals in the clinical information system.
- Integration into clinical workflows: Professionals use the reports directly for therapy planning and patient care.
Unique features:
- Gender-neutral anatomy: Based on iterative development with interdisciplinary feedback, a gender-neutral body outline was developed that is suitable for a broad patient population.
- Open-source basis: The anatomical illustrations and web app are made available as open-source software and can be flexibly expanded.
- Integration of standards: Linking of marked pain areas with SNOMED CT and integration via FHIR standards.
Objective:
The project aims to develop a user-friendly and inclusive solution for collecting patient-reported health data that:
- Supports better diagnostics and personalized therapies,
- Improves integration into clinical workflows, and
- Promotes data interoperability and reusability through the use of standards such as SNOMED CT and FHIR.
Project Team:
Philipp Ackermann (ZHAW), Dennis Baumli (ZHAW), Sebastiano Caprara (Balgrist), Giovanni Colacicco (UZH), Benedikt Herzog (Balgrist), Alessandro Holler (ZHdK), Christoph J. Laux (Balgrist), Yanick X. Lukic (ZHAW), Sonja Schläpfer (UZH), Reto Sutter (Balgrist), Claudia M. Witt (UZH)
Project Partners:
Zurich University of Applied Sciences (ZHAW), University of Zurich (UZH), Zurich University of the Arts (ZHdK), Balgrist University Hospital (Balgrist)