Extract and Transform Unstructured Documents into Analytics-Ready Healthcare Data

80MB

Amount of information added to patient medical records annually.1

80%

Amount of data that exists in unstructured and image-based formats.2

$300B

Value of unlocking healthcare data in reduced costs alone.3

Making Mission-critical Patient Data Easily Accessible

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Curation Services

Turn-key ability for data ingestion, optimization and storage services for data buyers and/or providers who lack the ability or in-house expertise to curate, structure and prepare data.

Curation Platform

SaaS platform provides image-based document navigation, key term identification and progressive NLP for organizations with in-house curators needing advanced tools.

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EMR Insights Browser

For use by organizations seeking to streamline manual clinical record review, tools that enable image-based document navigation or augment their prior authorization process with autocorrection of records.

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Quadris Natural Language Processing (NLP) Technology

Quadris leverages advanced NLP models to continually improve the quality and accuracy of targeted data. Other data extraction methods ingest every statistic and line-item available, regardless of relevance and accuracy, requiring vast time and resources for manual sifting. In contrast, Quadris enables rapid access to essential data in support of specific and predefined business and patient-related needs.

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Unlock Value Within Healthcare Data

Quadris

Quadris Data Solutions provide meaningful and actionable data to optimize time and resources while improving patient outcomes through intelligence.

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  • Unveil hard-to-access patient data that can provide a more complete view and timely, better-informed care
  • Receive accessible, structured and optimized data for evaluation and analysis by medical staff, physicians or networks
  • Leverage cloud-based platform scalability to absorb, process, and utilize any volume of data, regardless of size

References:
1 Huesch, D., and Mosher, T. J. (2017). “Using It or Losing It? The Case for Data Scientists Inside Health Care.” NEJM Catalyst
2 Kong, Hyoun-Joong. “Managing Unstructured Big Data in Healthcare System.” Healthcare informatics research vol. 25,1 (2019): 1-2. doi:10.4258/hir.2019.25.1.1
3 Manyika, James, et. al. (2022). “Big data: The next frontier for innovation, competition, and productivity.” McKinsey Global Institute