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Development of a Mobile Patient Documentation System for Physiotherapists Using the Fascial Distortion Model
  1. case
  2. Development of a Mobile Patient Documentation System for Physiotherapists Using the Fascial Distortion Model

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Development of a Mobile Patient Documentation System for Physiotherapists Using the Fascial Distortion Model

zaven.co
Healthcare
Information technology

Current Challenges in Physiotherapy Documentation

Physiotherapists face inefficiencies in managing paper-based patient records, difficulty visualizing fascial distortions, and time-consuming retrieval of historical treatment data. Existing solutions lack intuitive tools for mapping treatment areas and comparing progress over time.

About the Client

A Polish-Austrian startup specializing in mobile tools for physiotherapists to digitize patient documentation and treatment tracking.

Key Project Goals

  • Replace paper documentation with a digital solution
  • Create an intuitive visual editor for mapping fascial distortions
  • Streamline access to patient history and treatment results
  • Enable visual comparison of pre/post-treatment progress

Core System Requirements

  • Interactive human body model with scalable symbols for fascial distortion mapping
  • Patient file management system with visit history tracking
  • Grid-based visualization of treatment progress over time
  • Pain level tracking and video recording integration for pre/post therapy documentation
  • Step-by-step workflow mirroring traditional physiotherapy visit processes

Technology Stack

Mobile app frameworks (iOS/Android)
Cloud storage solutions
Vector graphics libraries

System Integrations

  • Electronic Health Record (EHR) systems
  • Cloud-based video storage

Non-Functional Requirements

  • High data security for medical information
  • Offline functionality for field use
  • Scalable architecture for growing user base
  • Intuitive UI/UX design for medical professionals

Expected Business Impact

Complete digitization of physiotherapy documentation processes, reducing administrative time by 40-60%, improving treatment accuracy through visual mapping tools, and enabling data-driven treatment adjustments via historical progress visualization.

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