Cystic Fibrosis Point of Personalized Detection (CFPOPD): An Interactive Web Application

Area of Science:

• Pulmonary Medicine
• Health Informatics
• Data Science

Background:

• Individuals with cystic fibrosis (CF) face progressive lung disease and respiratory failure despite increased life expectancy.
• Accurate, real-time risk assessment tools are crucial for managing CF lung disease and supporting clinical decisions.

Purpose of the Study:

• To develop an interactive, web-based application for predicting rapid lung function decline in CF patients.
• To integrate this predictive tool into electronic health record systems through clinician collaboration.

Main Methods:

• Utilized longitudinal data from 30,879 CF patients (2003-2015) from the US Cystic Fibrosis Foundation Patient Registry.
• Developed the application iteratively using R Shiny and qualitative feedback from 17 care providers.

Main Results:

• Identified key user feedback themes: ambiguity in defining rapid decline, clinical utility, significance, and suggested revisions.
• Revised the application based on user feedback, enhancing its prognostic capabilities for monitoring CF lung disease.
• The current version is available online, with future updates planned for additional features and a modular layout.

Conclusions:

• The developed framework facilitates the creation of visual analytics platforms for synthesizing electronic health data to improve clinical decision support for chronic diseases.
• A prospective study is needed to assess the tool's impact on patient-provider communication, shared decision-making, and clinical outcomes in CF care.