Identification of CAD/PAD Patients Without Prior Major CV Event in Healthcare Systems

Summary

We are actively searching for innovative healthcare startups to address a significant gap in the identification of Coronary Artery Disease (CAD) and Peripheral Artery Disease (PAD) patients without prior major cardiovascular (CV) events within healthcare systems. Our goal is to develop a solution that enables healthcare professionals to promptly identify these patients, allowing for timely interventions to manage their LDL-C levels and overall CV risk.

Background

The early identification of patients at risk of CAD and PAD who have not yet experienced a major CV event remains a critical challenge in healthcare. Despite the availability of various diagnostic tools and guidelines, the practical integration of these assessments into daily clinical practice is often hindered by time constraints and manual processes. Additionally, there is a need for a more interdisciplinary approach involving cardiologists, diabetologists, general practitioners (GPs), and internal medicine specialists to effectively manage these patients.

According to the European Society of Cardiology (ESC) guidelines, patients with CAD/PAD are considered to be at very high cardiovascular risk and should target an LDL-C level of 55 mg/dL or lower. Achieving this target is crucial in reducing the risk of future cardiovascular events. Therefore, timely identification and management of these patients are paramount.

Challenge Description

We are seeking technological innovations that can enhance the identification of CAD/PAD patients without prior major CV events. The proposed solutions should leverage advanced technologies such as decision support systems, patient record system alarms, and AI-driven tools to analyze patient data and alert healthcare professionals. The aim is to integrate these solutions seamlessly into existing healthcare systems to ensure efficient and timely identification and management of at-risk patients.

Possible directions (just examples!):

1. Develop an AI-Driven Decision Support System: Implement a system that utilizes AI to analyze patient data from electronic health records (EHR) and identify individuals at risk of CAD/PAD who have not experienced a major CV event. The system should provide actionable insights and alerts to healthcare professionals.

2. Integrate Patient Record System Alarms: Create a solution that integrates with existing patient record systems to automatically trigger alarms or notifications when potential CAD/PAD patients are identified based on specific criteria.

3. Enable Interdisciplinary Collaboration: Design a platform that facilitates communication and collaboration among cardiologists, diabetologists, GPs, and internal medicine specialists to ensure comprehensive patient management and follow-up.

What We Are Not Looking For

We do not seek educational activities, webinars, or informational materials for healthcare professionals. Our focus is on developing technological solutions that can directly impact patient identification and management processes.

Flexibility and Innovation

While we have outlined specific possible directions, we encourage potential partners to propose innovative solutions that align with the spirit and direction of this challenge. We are open to creative approaches that address the identification and management of CAD/PAD patients and help achieve the LDL-C target of 55 mg/dL as per ESC guidelines.

Ideal Partner

Our ideal partner should share our vision for transforming cardiovascular health management and bring complementary expertise or resources to the table. We are looking for startups that can provide innovative, scalable, and practical solutions to enhance the identification of CAD/PAD patients and improve healthcare outcomes.

We invite interested startups to propose their solutions and collaborate with us in addressing this critical healthcare challenge.