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DigitalOwl's Competitive Edge: The Specialized Medical Knowledge Base

Published On
February 27, 2025
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A standout feature that distinguishes DigitalOwl from its competitors, particularly general-purpose AI solutions, is its specialized Medical Knowledge Base. This unique asset empowers DigitalOwl’s AI to understand, contextualize, and establish intricate relationships within medical data as a human would. 

In this blog, we’ll explore the specifics of our Medical Knowledge Base—detailing what it is, its functions, and the substantial benefits it delivers to our customers.

What is DigitalOwl’s Medical Knowledge Base?

DigitalOwl’s Medical Knowledge Base is an extensive and continuously expanding resource that includes numerous data points critical for AI-powered medical record summaries. This comprehensive database encompasses all necessary medical terminology and integrates hierarchical data across conditions, procedures, and medications, allowing the AI to infer connections and enhance its ability to extract and highlight key information. Additionally, the Medical Knowledge Base includes a system of codes that link unstructured data to standardized medical codes such as ICD, SNOMED, and UMLS.

The Medical Knowledge Base team also focuses on mapping diagnoses to their relevant diagnostic and therapeutic procedures, associated medications, and risk factors. This approach enables the model to function as a reliable "medical expert" when uncertainty arises, ensuring that even the most complex cases are handled with precision. All of this is curated by DigitalOwl’s in-house team of medical experts, data scientists, and industry professionals to ensure both accuracy and depth in every summary.

How It Works

DigitalOwl’s Medical Knowledge Base is the cornerstone of our AI’s capability to interpret and analyze complex medical information with high accuracy. It extends beyond mere keyword scanning, enabling the AI to comprehend the subtle nuances in medical language and the intricate relationships between various medical conditions, treatments, and outcomes. This sophisticated understanding facilitates more precise and insightful AI medical record reviews, crucial for our clients in the insurance and legal industries.

The Medical Knowledge Base enables the normalization of medical information and standardization of unstructured medical data, making sense of it in real-time. It helps organize and clarify data where specific diagnoses, abbreviations, and diagnosis codes might be listed in a record and convey slightly different information. This organization is crucial for distinguishing and prioritizing the most important information.

Moreover, the Medical Knowledge Base goes further than just terminology standardization; it establishes intricate relationships within the medical data. For instance, it maps various aspects of medical diagnoses including symptoms, risk factors, complications, indicated medications, therapeutic and diagnostic procedures. This mapping provides a structured way for our model to understand and determine the connections between different medical terms.

Additionally, the Medical Knowledge Base acts as a dataset for highlighting conditions, procedures, and medications. This feature is instrumental in identifying and elaborating on key impairments and the medical terms that appear in our impairment rundowns, enhancing the depth and utility of the insights we provide. Through these capabilities, DigitalOwl’s Medical Knowledge Base ensures that our AI can rely on a robust foundation of medical data to support critical decision-making processes in AI in insurance claims, underwriting, and legal.

What This Means for Clients

The advanced capabilities of our AI, powered by the comprehensive Medical Knowledge Base, translate into a deeper understanding of medical data and its implications in real-world applications such as life underwriting and claims review. This expertise enables the AI to provide relevant and actionable information tailored to specific needs.

For clients, this means several key benefits:

  • Enhanced Decision-Making: The AI's nuanced understanding of medical terms allows it to identify critical insights that might be overlooked by less specialized AI solutions. This leads to more informed decisions in underwriting and claims processing, significantly reducing the risk of costly errors or oversights.
  • Increased Efficiency: By enhancing the extraction and interpretation of complex medical data, the AI significantly speeds up the review process. In addition to reducing the time spent on manual reviews, the AI highlights key medical items and their relationships—such as associated conditions, procedures, and medications—allowing clients to focus on what truly matters. This ability boosts efficiency and enables clients to handle a higher volume of cases without compromising quality.
  • Improved Consistency and Accuracy: With the support of the Medical Knowledge Base, DigitalOwl’s AI maintains a high level of consistency and accuracy in its work. Each case is treated with the same meticulous attention to detail, ensuring that all clients receive reliable and uniform medical record summaries and chronologies.
  • Customized Insights: The AI's ability to understand and interpret medical terminology and relationships allows it to tailor its analyses to the specific context of each client’s needs. Whether it's assessing the severity of a medical condition for underwriting or identifying key factors in a claims review, the AI provides insights that are directly applicable and highly relevant.
  • Reduced Costs: By streamlining the medical record review process and enhancing decision-making accuracy, the AI helps reduce the overall operational costs associated with medical reviews in underwriting and claims management. 

The integration of DigitalOwl’s specialized AI in underwriting, claims and legal processes revolutionizes our clients' core operations, driving enhanced outcomes across the board. By leveraging smarter, faster, and more reliable data processing and analysis, our technology ensures that decision-making is both accurate and efficient.

See our technology in action! Click here to explore our case studies and discover the time savings and efficiency gains our clients achieve.

Daniela Shapiro
Head of Medical Database Department
,
DigitalOwl
About the author

Daniela serves as the Head of the Medical Database Department at DigitalOwl, where she leverages her medical expertise to oversee the management and strategic development of the company's extensive medical databases. Concurrently, she is pursuing her MD, further deepening her knowledge and skills in the medical field.