Force HT
A UX research and design study exploring how Conversational AI (CAI) can streamline documentation during hair transplantation consultations, reduce administrative burden, and improve patient-centered care.
- Role: UX Researcher & CAI Design Strategist
- Timespan: 3 Months
- Tools: Semi-structured Interviews, Workflow Analysis, Concept Testing, Affinity Diagrams, Inductive/Deductive Analysis, Figma
Administrative Burden Prevents Patient Focus
Force HT’s client’s manual documentation processes during consultations consumed valuable time away from patient care and created an administrative burden for healthcare staff. Inconsistencies in data collection also lowered documentation quality. The challenge was to streamline these workflows with CAI while ensuring reliability and patient focus.
Qualitative Workflow and Concept Analysis
We applied a qualitative, human-centered methodology. Methods included semi-structured interviews with healthcare staff, workflow analysis of existing routines, and concept testing with visual concept sketches to discuss AI integration. Data was coded inductively/deductively with support from affinity diagrams.
– Trust: The primary design requirement was system reliability and transparency (knowing when and what the AI documents).
– Flow Integration: CAI must not disrupt the crucial patient-consultant interaction; it must act as a discreet assistant.
– Structure: A simple tool was needed to ensure all necessary data categories (treatment, plan, recommendations) were consistently captured.
PATRICK: A Framework for Trustworthy AI in Healthcare
The project delivered both academic insights (12 design factors) and a practical tool for the clinic. These solutions demonstrate how CAI can transform workflows to create more efficient, patient-centered consultations.
Practical Tool: A mnemonic tool that structures consultation data around Patient needs, Analysis, Treatment plans, Recommendations, etc. This simple framework enables the CAI system to reliably capture all critical data, significantly reducing administrative time for staff.
– Goal: Transform consultation workflows by automating documentation, freeing staff to focus on patients.
– Direct Result: A validated and structured framework for ethical and reliable CAI implementation in clinical settings.
I learned that in sensitive contexts such as healthcare, trust and ethical design are the primary design requirements. CAI must act as a reliable and transparent assistant, not a replacement, in order to reduce cognitive burden for staff and gain acceptance.
To validate the positive impact on patient care, pilot testing is required where the CAI solution based on the PATRICK structure is used in real consultations to measure reductions in documentation time.