Health Interventions
overview
Working with an enterprise AI software company to create a product that reduces the frequency of emergency room visits. This would save the patient money as well as health insurance companies, creating a win-win situation.
CLIENT
Enterprise AI software company
WHEN
Fall 2020 and Winter 2021
MY ROLE
I was the Lead Designer on this project. Most of the research was done prior to me taking on this project, so my role consisted mostly of the UX/UI and Visual Design for the interventions.
TOOLS USED
Figma
01–Getting Started
The Challenge
Nearly half of patients who visit an Emergency Room, could be managed by a primary care physician or urgent care. Going to the ER when it is not necessary, fills up space and expertise in the ER that could be used for life-threatening cases, and costs everyone (the patient, health insurance companies, etc.) more money.
The Opportunity
To create digital “interventions” via different platforms (i.e. health insurance apps) that gives members or patients insights into other, and better, options than the Emergency Room in non-life-threatening situations.
02–Exploration
The AI Company and our company worked together to pitch this idea to a specific health insurance provider. Our testing and data is based off of their members in order to measure success.
End Goal
The end goal is to reduce the cost of care.
Short-Term Goals
Getting the user to read the interventions and make steps towards taking action. Whether that’s selecting a PCP, going to Urgent Care, or setting up an appointment on Telehealth.
risk scores
Members of the Health Insurance company we were working with were divided into 3 “Risk” categories: High Risk, Medium Risk, and Low Risk. Risk factors are based off of several variables such as current health situation, demographics, whether or not the member has a PCP, how often the member has visited the ER in the past, etc. We then would push interventions to the top 1% of members, which the majority would fall under the High Risk category. If the user was in this top 1%, when they log into their Health Insurance app, they would receive 1 of 3 “interventions” in the form of an overlay. The intervention assigned to them would also be based off of several variables, such as if they have a PCP or not, or how severe their illnesses have been in the past.
wireframes and iterations
03–The Solution
Interventions
There are 3 overlay interventions for the 3 use cases: Selecting a PCP, finding an Urgent Care, or scheduling Telehealth. These would appear after the user logs into their health insurance app, if they are in the “top 1%” of risk scores.
example flow: primary care physician
When the user falls within the Top 1% AND doesn’t have a PCP, the PCP intervention would overlay after log-in to their health insurance app. It would allow them to see what relevant PCP’s are in their area, with the options to select as PCP, book an appointment, call, or get directions.
This project collaboration is an ongoing effort into 2021. The above was Phase 1 for the MVP. Testing and further exploration is being done during the first quarter of 2021.