Selected Work / Analysis
Denial Pattern Analyzer
A fictional diagnostic dashboard built to identify denial clusters, quantify revenue at risk, and clarify where operational intervention would matter most.
This case study is based on a fictional multi-specialty group practice and a synthesized claims dataset. The organization and numbers are fictional, but the denial categories, workflow logic, and intervention thinking are grounded in real-world revenue cycle experience.
01
The setup
This scenario centers on a fictional multi-specialty practice with a messy payer mix, uneven denial performance, and limited clarity into where claims are failing and why. The goal was not just to visualize denials, but to create a compact diagnostic view that surfaces the most meaningful patterns across payer, failure stage, and denial category.
Rather than treating all denials as one undifferentiated problem, the dashboard is designed to separate preventable workflow issues from broader revenue noise and highlight where operational focus would have the greatest impact.
02
What the dashboard is meant to do
The dashboard below simulates how I would evaluate denial activity in practice: isolating meaningful clusters, identifying which issues are concentrated by payer or stage, and translating raw claims activity into clearer operational priorities.
The point is not simply to report what is being denied. The point is to clarify where revenue is getting stuck, which issues appear most preventable, and where intervention would likely generate the fastest operational return.
Interactive demo
Live dashboard
If the embedded demo does not load cleanly on your device, use the full-screen link below.
03
What this demonstrates
This piece is meant to show more than dashboard fluency. It is an example of how I think through operational diagnosis: what I look for first, how I distinguish signal from noise, and how I tie claims data back to real workflow decisions.
The intended takeaway is not just that I can build or interpret a report, but that I can use revenue data to identify where systems are failing, where accountability should sit, and what should be addressed first.
Bottom line
The insight is the product.
In a real operating environment, the value of a dashboard is not the charts themselves. It is whether the dashboard helps a team see the right problem clearly enough to act.