Akido Labs: Built and designed EHR system with AI technology
Background
At Akido Labs, upon researching current EHR systems that doctors used, we noticed a critical issue: physicians spend excessive time documenting patient encounters, leading to burnout. This problem is exacerbated by inefficient data entry, poor system interoperability, and limited decision support capabilities in existing EHR systems. This often results in physicians sacrificing valuable appointment time for documentation, impacting both their satisfaction and patient care quality. To address these challenges, we work closely with doctors from the Chaparral Medical Group, collaborating to enhance data accuracy through AI-driven automation, facilitate real-time decision-making with clinical support tools, optimize workflows via UI enhancements, onboard doctors efficiently, and ultimately, improve patient encounters by enhancing usability and efficiency
Overview
Today's healthcare relies heavily on Electronic Health Record (EHR) systems, yet many doctors struggle with complex data entry and limited usability. Our AI-enhanced EHR system aims to streamline workflows, boost data accuracy, and revolutionize healthcare delivery for doctors and nurses.
My Role
As the lead designer of this project, I was in charge of designing UX and UI elements from wireframes to high fidelity screens, running user research sessions to identity user needs, leading and facilitating design sprints for major product features, working with product managers to define product strategy and roadmaps and collaborating with developers to ensure proper design implementation.
Users gathered from research and interviews
Charting out key steps in flow
Journey mapping from our research findings
Competitive Analysis and Audit of existing EMR Programs (Capella and Cerner)
Sketching early on to spark ideas
Approach
At Akido Labs, we collaborated closely with medical professionals from the Chaparral Medical Group, to develop our solution. We conducted interviews, analyzed competitors like Capella and Cerner, and created user flows to guide our development process. Our approach included building a minimum viable product (MVP) based on user feedback and industry standards. We iteratively tested prototypes, incorporating doctor feedback to enhance usability. A key feature we implemented was AI-generated notes, where doctors transcribe patient encounters and our AI summarizes them along with orders for referrals, prescriptions, procedures, and diagnostics. This feature aimed to simplify documentation and improve efficiency during appointments.
Early stage wireframes and concepts used for usability/validation testing
Key Flows
Outcome
The culmination of our efforts at Akido Labs resulted in a transformative solution for healthcare professionals. By addressing the inefficiencies identified in existing Electronic Health Record (EHR) systems, our platform streamlined documentation processes, alleviated burnout, and improved overall patient care quality. Collaborating closely with doctors from the Chaparral Medical Group and other practices, we successfully implemented AI-driven automation for data entry and decision support, significantly enhancing accuracy and efficiency. Our user-centric approach, from creating intuitive user flows to iterating based on extensive testing, led to a solution that not only met but exceeded user expectations. The integration of AI-generated notes proved to be a game-changer, revolutionizing the way doctors document patient encounters and facilitating quicker, more informed decision-making. Ultimately, our project resulted in a tangible improvement in healthcare delivery, empowering medical professionals to focus more on patient care and less on administrative tasks.
Flow for generating summary from transcript
AI Generated Orders
Signing Note