Project Overview

The Problem:

Over 50% of patients are non-adherent and do not take their medication, causing $100 billion in lost revenue and harming patient health. With the use of med-ALs, a machine learning algorithm, clinicians can view the likelihood of a patient’s non-adherence and see the top contributing factors for their non-adherence. Because this algorithm is newly developed, it has not yet been integrated into any electronic medical records for clinician use.

The Solution:

I created a proof-of-concept prototype that shows med-ALs’ information and adds appropriate patient education tools to an already-existing electronic medical record over the period of twelve weeks. The project workflow included two parts: the first part included user research, such as a literature review, comparative analysis, multiple modeling techniques, personas, and workflows. The second part pivoted to user design and rapid iterative test evaluation (RITE) testing, which allowed for an agile redesign process.

My Role:

Client kickoff, literature review, competitive analysis, information architecture, flow modeling, personas, user flow, mock ups, wireframes, prototyping, usability testing, RITE testing

Tools:

Sketch, Invision, Excel