# Creation of an Interactive Dashboard to Facilitate Early Detection of Cardiac Amyloidosis in African American Veterans

## TL;DR

This paper describes the creation of a dashboard to help identify African American veterans at high risk for cardiac amyloidosis, a heart condition that is often underdiagnosed.

## Contribution

The novel contribution is the development of an interactive dashboard to facilitate early detection of cardiac amyloidosis in African American veterans.

## Key findings

- The dashboard identified 949 out of 1,732 African American veterans with heart failure as high risk for cardiac amyloidosis.
- Challenges included dashboard development time, limited team experience, and data standardization across three VA hospitals.

## Abstract

Background
 Cardiac amyloidosis (CA) is an underdiagnosed cause of heart failure (HF) that disproportionately impacts men of African descent. Without a standardized method of screening and scattered patient health information, clinicians must integrate data that spans multiple disease systems and is stored across the electronic health record.

Objectives
 The aim of this project was to create a dashboard to facilitate identification of high-risk African American (AA) veterans who would benefit from CA screening tests. This paper described the development of the dashboard and identified barriers and opportunities in dashboard development.

Methods
 Three Veterans Affairs (VA) health systems participated in this project. Microsoft Structured Query Language (SQL) Report Builder was utilized to create an interactive dashboard that refreshes daily through stored procedures using SQL Server Integration Services and the SQL Server Job Agent. Inclusion criteria included AA patients less than 90 years old with a history of HF. The 2023 American College of Cardiology/American Heart Association consensus statement on diagnosis and treatment of transthyretin CA was the source of evidence in creating the inclusion criteria and parameters of interest.

Results
 The final dashboard contained 1,732 HF patients who met inclusion criteria, of which 949 (55%) were identified as high risk. We faced several challenges in this project, including time required for dashboard development, limited team experience in specifying dashboard requirements, identifying informatics counterparts at all sites, and standardizing data across three VA hospitals.

Conclusion
 In this clinical improvement project, we created a dashboard that identifies AA veterans with HF at risk for CA and that can help to mitigate the impact of CA on this population.