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Predictix_Cover(Figma).png

A MedTech Platform for Treating Anxiety

Project Overview

Predictix is an innovative MedTech product from Taliaz Startup in Israel, enhancing medication prescription accuracy for patients with anxiety and depression through statistical algorithms and machine learning.

  • 80% of antidepressants are prescribed by Primary Care Physicians with limited success tools.

  • Selection from multiple antidepressants.

  • Limited consultation time of 10-15 minutes.

  • Prescription accuracy ranging from 30% to 49%.

Traditionally, finding the right medication takes months of trial and error, causing side effects, rapid changes, and eroding trust in the medical team

Taliaz solution focused on

  • Enhancing prescription accuracy

  • Reducing the time required to find the right medication

  • Equipping doctors with data tracking and insights for educated data-driven decisions

My Role

User Experience Consultant (Research & Strategy)​

When

2021​

Team

Inhouse Team: VP Product, Outsourced Development Team, Data Analysts Team

Product Designer: Anat Ganot

Tools used

  • Asana

  • Miro

  • Figma

PerdictiX_Proposal - Work Process (will be spread on Scheduled Gant).jpg

My mission

  • Research the needs and motivations of Potential Design Partners for initial launch.

  • Help the team Develop and test a working MVP for doctors treating patients with anxiety and depression.

Project Planning

In this dynamic process, I ensured early clarity by aligning stakeholders through a project strategy that would follow the research stage.

This was vital as we conducted Research, created Wireframing, and defined UI guidelines simultaneously with third-party branding of the company. 

We used Asana to build a road map and create a clear path toward the completion of the project.

Reseach

The research involved three key steps:

1. Collect: Gathering team assumptions and requirements
2. Validate: Gaining insights through Qualitative Research to confirm we address the right problems
3. Explore: Investigating existing solutions and current practices

PerdictiX_Proposal - System Information Architecture.jpg

1. Collect

When the customer came for help, they had a working but complex platform that Doctors felt frustrating to use.

Based on my experience with startups, I know the importance of not reinventing the wheel.

I mapped the current POC, pinpointed usability issues, and provided insights for moving forward

Where are the critical pain points?

I used User Journey mapping to move the conversations from a list of screens to a flow,
with tasks and motivations. 

Who is this for?

After mapping the POC and integrating PRD insights, we dove into understanding our users. Using proto-personas, the VP and CEO filled out templates, and in a session, we explored their needs via an empathy map.

PredictiX - User research - Thematic analysis - 1. Team Assumptions - Initial Segmentation
PredictiX - User research - Thematic analysis - 1. Team Assumptions - Protopersonas.jpg
PredictiX - User research - Thematic analysis - 1. Empathy map.jpg

By mapping team assumptions, we crafted a focused research plan, addressing key validation points for product and interface improvements, and providing valuable business insights.

Research_Analysis_process.png

2. Validate

With this in mind, I crafted a research plan. I analyzed recorded conversations with Doctors who were Design Partners and MVP testers.

I also conducted additional 1:1 interviews for deeper insights.

Here is what we've learned

After validating pain points and opportunities, I provided key insights: 

* Doctors lack time for questionnaires; prefer pre-session patient input.
* Initial doctor-patient conversation crucial; questionnaires confirm severity.

I streamlined the system architecture and recommended a user-friendly, clear user journey.

PredictiX - Content Hierarchy and User Flows - Users Flows - 1st batch - Adding patient +
PredictiX - Content Hierarchy and User Flows - Users Flows - 1st batch - Adding patient +

By validating and debunking the Team's assumptions about the users

we could move forward creating an improved flow for the platform and the journey of users in it, because we built trust

PredictiX - Research - Competitors.jpg

3. Explore

My exploration research focused on two main needs: 

Functionality & Terminology:
where we explored how various actions for doctors are presented in similar systems to verify best practices. 


Reports and Statuses:
We looked for reports and dashboards for doctors which provided answers regarding medication for patients.

Brainstorming and Ideation

We worked alongside the Product VP and Dev team to discuss possible flows

and layouts for each screen in the flow

I love working with Miro or other collaboration tools since it allows me to open a whiteboard and sketch the Low Resolution wireframe, together with my team

But Wait... It's Not All Smooth Sailing

Sometimes you need to improvise

While working on a report screen,

the team disagreed on organizing data in the table for doctors.

I invited my team to a "Card Sorting" session, where we broke down the table's content and actions, sorted and prioritized them individually,

and then converged as a group to make decisions.

Card_sorting_Each_team_member.png
Test list - Card sorting - Exercise Summary.jpg
Patient Dashboard_tabs+table.png

After 1 Hour of collaborative work with a bit of Design-Thinking 

we got to an agreement and were able to move forward

🤩

User-Centered Design in Action

For this project, I teamed up with a colleague. She was responsible for the Design part and I was the owner of the Strategy, Research and UX deliverables.

Entry point to the platform

Adding a new Patient to the system

In a health-focused platform, we navigated regulations and addressed patient consent forms. Clear micro-copy, friendly errors, notifications, and user choice created a complex yet accessible path for our Doctors.

Intake questionnaire

To ensure precise medication recommendations, Doctors completed a diagnostic questionnaire following standard practices for anxiety and depression diagnosis.

 

I streamlined this process by learning the domain and collaborating with data scientists while adhering to medical regulations