Healthcare and Personalized Pathways

In recent years, the digital revolution has triggered transformative changes across various sectors, and healthcare stands at the forefront of this paradigm shift. With the exponential growth of healthcare data fueled by advancements in technology, the traditional approaches to data management, analysis, and visualization are undergoing a profound evolution. Among the emerging methodologies, graph analytics and visualization have emerged as powerful tools with the potential to reshape the landscape of digital health.

GraphPolaris offers a novel approach to uncovering hidden patterns, relationships, and insights within complex datasets. By representing data as interconnected nodes and edges, graph analytics transcends the limitations of traditional tabular structures, enabling a more nuanced understanding of interdependencies within healthcare ecosystems.

Our strong visualization capabilities provide intuitive means to interactively explore and comprehend the rich context of interconnected data, empowering stakeholders to derive actionable insights with unprecedented clarity.

Our solutions therefore aim to ‘move the innovation needle’ towards personalized therapy pathways on both a population, as well as patient level:

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Patient Journey Analysis

Supported by the GraphPolaris platform, you can model the entire patient journey, including interactions with healthcare providers, treatments received, medications prescribed, and outcomes. Analyzing this data can help healthcare organizations optimize patient care pathways, identify inefficiencies, and improve patient outcomes.

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Precision Medicine

Providing personalized solutions is a typical multi-variate, spatial-temporal data analytics challenge. GraphPolaris helps you to integrate genomic data, pathology / imaging data and electronic health records to create comprehensive patient profiles. Analyzing these profiles - potentially substantiated by clinical trail data - can help healthcare providers explore potential for personalized patient pathways and tailor treatments to individual patients based on their genetic makeup, medical history, and lifestyle factors.

Disease Surveillance and Outbreak Management

Our platform can effectively model disease transmission networks, healthcare facility networks, and population demographics. Analyzing these networks can help public health authorities track disease outbreaks, monitor the spread of infectious diseases, and allocate resources effectively.

Healthcare Fraud Detection

GraphPolaris model relationships between patients, healthcare providers, insurance claims, and billing records. Analyzing these relationships can help detect patterns indicative of fraudulent activities such as overbilling, phantom billing, and kickbacks.