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Design and Implementation of Big Data-Based Documents to Optimize Medical Coding.

Joseph Noussa-Yao1, Didier Heudes1, Patrice Degoulet1

  • 1INSERM, UMR_S 1138, CRC, Team 22, Paris, France.

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|June 6, 2018
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Summary
This summary is machine-generated.

This study introduces a big data-coding warehouse using a Not Only SQL (NoSQL) model to manage complex medical coding data. The new framework enhances data management for clinical information systems, improving coding quality.

Keywords:
Big dataDecision makingDiagnostic codingclinical decision supportmedical diagnostic computingoptimization

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Area of Science:

  • Health Informatics
  • Database Management
  • Medical Coding

Background:

  • Clinical information systems (CISs) face challenges managing large, heterogeneous data from diverse medical specialties.
  • Efficient management of medical service quality coding is increasingly difficult with growing data volumes.
  • Existing data management frameworks may lack the flexibility required for complex coding tasks.

Purpose of the Study:

  • To design and implement a big data-coding warehouse for improved medical service quality coding.
  • To define rules for converting conceptual coding models into a document-oriented logical model.
  • To evaluate the performance and precision of the implemented big data-coding warehouse.

Main Methods:

  • Utilized a document-based Not Only SQL (NoSQL) model for data management.
  • Developed a framework to convert conceptual coding models into a document-oriented logical model.
  • Implemented and analyzed a big data-coding warehouse using the MongoDB database.
  • Evaluated the system using mono- and multi-criteria data research and calculated model precision.

Main Results:

  • The designed big data-coding warehouse provides an accessible, extensive, and robust framework for coding data management.
  • The document-oriented logical model successfully converted conceptual coding models.
  • Evaluation demonstrated the model's effectiveness in handling complex coding data and achieving measurable precision.

Conclusions:

  • The NoSQL-based big data-coding warehouse offers a flexible and robust solution for managing medical coding data within CISs.
  • This approach enhances the efficiency and accuracy of quality coding for medical services.
  • The implemented model shows promise for improving data management in healthcare settings dealing with large datasets.