Designing for Health Equity- Turning Data Into Action

I led UX strategy for a healthcare innovation initiative exploring how SDOH data could improve health equity. The project resulted in an AI-assisted decision support experience that transformed fragmented member data into actionable insights, helping wellness coaches identify risks and make more informed intervention decisions.

The context

Healthcare organizations are increasingly focused on preventive healthcare—identifying potential health risks early and helping people access support before those risks lead to serious medical issues, hospitalizations, or higher healthcare costs.

A person’s health is influenced by more than clinical conditions alone. Factors such as access to transportation, stable housing, food security, income, education, and social support can significantly impact health outcomes. These non-medical factors are commonly referred to as Social Determinants of Health (SDOH).

For both members and the professionals supporting them, understanding these factors can be difficult because relevant information exists across different parts of the healthcare ecosystem. Rather than relying on hard-to-access external datasets, this project focused on data sources that could realistically exist within a healthcare platform, including:

  • Health Risk Assessment (HRA) forms completed by members.
  • Insurance claims and eligibility data.
  • Employment and demographic information.
  • Wellness coach interaction notes.
  • Clinical and behavioral health records.

While these sources contain valuable insights, they are often fragmented, making it difficult to build a complete picture of a member’s needs and risks.

👉 This is a public, NDA-safe overview of the work that shows how I led design decisions through ambiguity in a healthcare environment with strict time and data constraints..

organization

Emids

INDUSTRY:

Healthcare

TIMELINE:

March 2023 (2 weeks)

Team Members:

Swati Soni

Sr. Lead Product Designer

Mohd. Asif

Principle Designer

Abhinav Singh

Sr.Manager, Consulting

Who this solution supports?

The primary users of this experience were:

Wellness Coaches

who work directly with members to identify care barriers, provide guidance, and support healthier behaviors.

Members

who need access to resources, services, and support programs that can help address social and health-related challenges.

Key challenges

  • Relevant member information is spread across multiple systems and records.
  • Social and clinical factors are difficult to connect into a complete picture.
  • Wellness coaches spend significant time reviewing fragmented information.
  • Important signals can be overlooked when data is disconnected.
  • Members often lack visibility into the factors influencing their health outcomes.
  • Limited visibility slows proactive intervention and support.

Problem statement

The problem is not a lack of information.

The problem is turning fragmented information into informed action.

Wellness coaches and members need a way to:

  • Make informed decisions based on a more complete understanding of member needs.
  • Quickly identify potential health risks.
  • Understand the clinical and social factors contributing to those risks.
  • Prioritize areas that require attention.
  • Reduce time spent navigating disconnected information.

Example Scenario

Michael has visited the ER multiple times and missed preventive care appointments because transportation is unreliable and day-to-day expenses often take priority. While these signals exist across claims, assessments, and wellness coach interactions, they rarely come together in one place. As a result, Sarah, his Wellness Coach, spends valuable time piecing together fragmented information before she can fully understand his situation and identify the right support options.

Solution

To address this challenge, I designed a decision-support experience that helps wellness coaches and members move from information gathering to informed action more efficiently.

Design goals & workflow approach:

The experience was designed to help users:

  • Understand risk at a glance.
  • Identify the factors contributing to risk.
  • Focus attention on the most important issues.
  • Take action with greater confidence.
  • Support preventive and equitable care outcomes.

Since the goal was to support better decision-making, I first focused on understanding the workflow wellness coaches follow when helping members. Mapping this journey helped identify where information, insights, and actions needed to come together to create a more effective experience.

End-to-end workflow followed by a Wellness Coach when supporting at-risk members.

Solution Highlights

Improvised HRA forms

Expanded the member-facing HRA survey to capture key SDOH factors and use periodic assessments to keep Health Equity Scores current.

Introduced health equity score

The insights from HRA were combined with wellness coach interactions and available employment and insurance data to calculate Health Equity Score

Health equity overview: A unified view of SDOH risk factors

Clicking a member’s name opened a unified profile that consolidated clinical, behavioral, and SDOH information into a single view, enabling wellness coaches to quickly understand the member’s history, current circumstances, and potential barriers to care.

Transforming qualitative insights into quantifiable risk factors

Created modular assessments that allowed wellness coaches to capture information about housing, nutrition, and other SDOH factors during member conversations. The responses contributed to the member’s Health Equity Score.

Conversation insights at a glance

Integrated AI-powered speech analysis to identify key topics and moments of concern from member conversations. Important themes were surfaced as keyword highlights, helping wellness coaches quickly understand areas that may require attention.

Reducing documentation effort with AI

AI generated a draft summary of each conversation that wellness coaches could review and edit before saving. This reduced documentation effort while ensuring important concerns, context, and next steps were captured accurately.

Connecting members to local resources

Enabled wellness coaches to search for nearby resources such as food banks, shelters, and support services based on a member’s location. This made it easier to provide practical guidance and connect members with help during the conversation.

Human-centered AI design principle

This approach reflects a broader principle that has shaped my work: technology creates the most value when it enhances human decision-making rather than attempting to replace it.

What AI does well?
  • Processes large volumes of information.
  • Identifies patterns and trends.
  • Surfaces relevant insights.
  • Highlights potential risks.
  • Accelerates information review.
What Human does well?
  • Apply context and judgment.
  • Consider individual circumstances.
  • Build trust and relationships.
  • Make nuanced decisions.
  • Remain accountable for outcomes..

Key reflection

This project reinforced a simple idea: AI is most valuable when it helps people make better decisions, not when it makes decisions for them.

While AI helped identify patterns, summarize information, and surface insights, wellness coaches remained essential for understanding context, building trust, and guiding members toward meaningful action.