Patient Charting Experience

Creating an AI-powered patient charting experience that streamlined how doctors capture and manage patient data in real-time. Increasing pro user growth by 300% in 9 months. It started here…

Disrupting the Patient Charting Experience

As the Lead UX Designer at NextGen Healthcare, I led a team of three designers to create a groundbreaking patient charting experience tailored for healthcare providers. This project spanned across three distinct teams, focusing on integrating advanced ambient AI dictation tools, SOAP notes, and comprehensive management of diagnosis, medications, orders, and office visit codes—all within a unified and efficient workflow.

Our goal was to streamline how doctors capture patient data in real time, leveraging AI-powered assistance to enhance accuracy and reduce administrative burden. This new system is transforming the way healthcare professionals interact with patient data, making charting more intuitive, faster, and contextually aware.

My Role

As the lead designer, I established the initial design direction and operational delivery, laying out strategic workflows and core interaction models before involving my team in higher-fidelity work. My role was to ensure the design vision was coherent and aligned across all three projects. I managed design strategy, ideation, and early conceptualization, ensuring our solutions addressed user needs effectively. After setting a clear direction, I guided my team through the detailed design phases, ensuring quality and consistency.

Product Goals

• Increase User Adoption: Boost engagement and active usage of the charting app by providing a more intuitive and seamless experience across platforms.

• Enhance Efficiency: Reduce the time it takes for doctors to complete charting and data entry by integrating AI-powered tools like ambient dictation and automated suggestions.

• Deliver Real-World Value: Validate the design solutions through user testing and field research, ensuring that the system meets the needs of healthcare providers in diverse clinical settings.

What was our process?

• Navigating Ambiguity
  The project began with a high degree of uncertainty around user needs and technical constraints. To address this, we used an iterative approach—rapidly building low-fidelity prototypes to explore different solutions.

• Balancing Speed with Quality
  In a fast-paced product environment, we needed to balance the urgency of delivery with the depth of user research. We utilized quick, iterative cycles to create prototypes that were immediately tested with real users.

• Adapting to Evolving Requirements
  As product requirements and priorities shifted, the we maintained flexibility by working in short sprints and refining concepts based on continuous feedback loops.

• Embracing a Fail-Fast Mentality
  The team adopted a fail-fast approach, rapidly discarding ideas that didn’t perform well in testing and iterating on promising ones. This minimized wasted effort and ensured that we focused on the right outcomes.

Outcome

Our new charting experience is currently being adopted across several healthcare practices, receiving positive feedback from doctors and clinical staff. Early results show increased efficiency, reduced charting time, and higher accuracy in patient data capture. Additionally, our redesign led to a 20% increase in app usage within six months and a 300% growth in professional users, establishing a strong foundation for future enhancements and AI-driven innovation.

Design Documentation

Research & Discovery

To begin, we conducted a series of stakeholder and user interviews and shadowed a doctor to map their current charting workflows and journey. This research uncovered key pain points and opportunities, which informed our early concepts.

Tools Used: Interviews, Field Research, User Journey Mapping, Workflow Analysis

Ideation & Concept Design

Using our findings, I sketched initial concepts and wireframes, focusing on creating an AI-assisted workflow that simplified routine tasks like SOAP note entry and medication updates. I led the team in establishing the core interactions before handing off to my designers to further refine and build out high-fidelity screens.

Tools Used: Sketching, Wireframing, Interactive Prototyping, Design Reviews

Design System Integration

Implementing a new design system was a critical task. We set up a comprehensive component library and usage guidelines that ensured visual and functional consistency across teams. This allowed for scalable design and streamlined handoff to development. I did not lead the design system efforts but contributed by building initial components and ensuring that our systems meet the needs of the interfaces.

Tools Used: Figma for Component Design, Confluence for Documentation, Team Workshops and Facilitation

High-Fidelity Prototyping

We created high-fidelity prototypes that included complex interactions for dictation, AI suggestions, and smart data entry, which were tested rigorously with providers to ensure usability and alignment with real-world scenarios. I led most of the user research efforts and developed the initial low-fidelity concepts and designs. As the work progressed, I helped transition these concepts into high-fidelity prototypes, then refined and polished the final designs while collaborating closely with my designers and the product team to ensure a seamless user experience and strategic alignment.

Tools Used: Figma, Usability Testing with Providers using Teams or Usertesting.com

Cross-Functional Collaboration

Throughout the process, I facilitated design reviews with product managers and development leads to align on technical feasibility and roadmap priorities. I worked closely with these teams to manage scope and address any implementation challenges.

Tools Used: FigJam for Collaboration, Jira for Project Management, Teams for Communication

Validation & Iteration

We initially conducted over 20 user tests remotely via Teams, gathering valuable feedback and iterating rapidly based on provider input. Finally, we validated our designs through an on-site visit in Savannah, GA, where we observed a provider using the ambient AI assistant in live patient scenarios. The insights gained from these real-world interactions led to crucial refinements that further enhanced the user experience and ensured our solution met the practical needs of clinicians.

Tools Used: Field Testing, User Feedback Analysis, Iterative Design Updates

Next Steps

By establishing a strong design foundation and building a cohesive vision for the future of patient charting, I led my team to deliver a product that is not only innovative but also impactful in everyday clinical practice. Our efforts were instrumental in significantly boosting user engagement and satisfaction, paving the way for continued success and growth.

Next steps include refining each area of the charting experience based on ongoing feedback and insights. We will also focus on implementing a new “Super Favorites” feature, allowing users to create customized groups of frequently used orders and charting elements, further enhancing efficiency and personalization in their workflows. There is also a goal to incorporate an additional view using the problem-based charting method.