Healthcare IT
A Nurse During a Hectic Shift
An empathy map for a hospital nurse using an electronic health record (EHR) system during a busy 12-hour shift.
Analysis & Interpretation
Background
This map provides a powerful and empathetic look into the high-stress world of a nurse using an Electronic Health Record (EHR) system. It reveals a user who is dedicated to their core mission (patient care) but deeply frustrated by the tools they are forced to use.
Key Strategic Insights
- The Tool vs. The Workflow: A powerful contradiction is seen between what the user ‘Thinks’ (‘This software is not designed for how I actually work’) and what she ‘Does’ (‘Copies and pastes notes’, ‘Relies on paper notes’). This shows the user is actively creating workarounds because the tool fails to support her real-world workflow.
- Cognitive Load is the Enemy: The nurse ‘Feels’ ‘Stressed’ and ‘Frustrated’, and ‘Says’ ‘Why are there so many alerts?’. This points to a massive problem with cognitive load. The EHR is adding to her stress rather than reducing it, which is a critical design failure.
- Safety is the Underlying Fear: The user’s internal thought (‘I hope I don’t make a mistake’) and worry (‘about patient safety’) reveal the high-stakes nature of her work. The EHR’s usability flaws are not just an inconvenience; they are perceived as a direct threat to patient safety.
Strategic Summary
This empathy map paints a picture of a mission-driven user who feels betrayed by her tools. The EHR system is seen as an obstacle to, rather than an enabler of, good patient care. Any attempt to improve this product must start with deep ethnographic research to understand the nurse’s actual workflow. The design goals should be to reduce cognitive load, build trust, and seamlessly integrate into the fast-paced, interruption-driven reality of a hospital shift.
How This Was Built
This empathy map demonstrates how structured thinking and AI guidance can help transform raw observations into meaningful customer insights.
AI-Fueled Observation Mapping
The AI Suggestion Engine offered ideas for what customers might Say or Do during product interactions, shaping the foundation of the empathy map.
Color and Tag Organization
Colors highlighted internal and external perspectives, while tags grouped pain points, needs, and motivations to make the information more actionable.
AI Insight Synthesis
After filling the sections, the AI Analysis Tool summarized key emotional drivers and identified unmet needs worth exploring in the next design phase.
Bring This Example to Life
Load this empathy map in the app to refine your audience understanding, visualize emotional responses, and apply AI insights to craft more human-centered solutions.