Total Provider View

Overview

Total Provider View is an enterprise healthcare product currently being developed as part of Elevance Health's broader Provider Interoperability strategy. The platform brings together provider information across claims, authorizations, appeals, contracting, payment integrity, provider operations, and other business domains into a unified experience designed to improve provider transparency and executive decision-making.

Unlike traditional reporting platforms, Total Provider View is being designed as an AI-enabled product that proactively identifies meaningful operational signals, explains significant changes in provider performance, and helps users investigate issues before they become larger business problems. The long-term vision includes AI-powered anomaly detection, conversational exploration, guided investigations, and executive decision support.

My Role

I support product development by helping translate business needs into meaningful product capabilities across reporting, AI insights, and executive experiences.

Working closely with engineering teams, market leads, product partners, and business stakeholders, I help define executive metrics, validate AI-generated insights, identify gaps in business logic, improve metric definitions, and ensure new capabilities reflect how users actually make decisions.

I also contribute to the platform's conversational AI by developing business documentation, metric definitions, reporting context, and user knowledge that help ground chatbot responses in trusted healthcare information rather than technical data alone.

The Opportunity

Healthcare organizations generate enormous amounts of operational data, but executives rarely need more dashboards. They need trusted answers.

Total Provider View seeks to transform provider transparency by combining operational analytics, AI-generated insights, conversational exploration, and executive workflows into a single product experience.

As Total Provider View continues to evolve, one of the ongoing product challenges has been determining which AI-generated insights provide meaningful value to users. While AI can identify statistical anomalies, product teams must still determine which signals matter, how they should be explained, and what actions they should encourage.

Building trustworthy AI requires strong business knowledge, trusted metric definitions, product thinking, and governance—not simply machine learning models.

Connecting Strategy to Execution

One of my primary contributions has been helping connect technical implementation with meaningful business outcomes.

An example of that work is the Executive Dashboard, where I designed executive metrics based on stakeholder feedback and business workflows. Rather than organizing information around source systems, I worked backwards from the decisions leaders needed to make—identifying meaningful KPIs, defining executive navigation, and helping shape AI insight concepts that support executive decision-making.

Beyond executive dashboard design, I regularly evaluate AI-generated insights, identify inconsistencies in business logic, advocate for stronger metric governance, and help ensure AI recommendations align with real provider operations rather than simply highlighting statistical anomalies.

As the platform continues to evolve, I also contribute to redesigning the Joint Operating Committee (JOC) presentation experience, expanding conversational AI capabilities, and helping build the business knowledge foundation required for AI-generated insights to become trusted decision-support tools rather than isolated technical features.

Current Progress

Total Provider View remains an active product under continuous development.

Current work includes refining executive dashboards, validating AI-generated insights, strengthening business metric governance, expanding chatbot knowledge, redesigning the Joint Operating Committee (JOC) experience, and helping improve delivery practices as the platform continues expanding across new provider domains.

Because the platform is still evolving, my work remains focused on ensuring AI capabilities are grounded in trusted business knowledge, meaningful user workflows, and practical decision support.

Artificial intelligence creates value only when trusted business knowledge, meaningful user workflows, and well-defined metrics come together. Successful AI products begin by understanding people and the decisions they need to make—not simply the technology behind the models.