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Establishing a sorting protocol for healthcare databases.

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Summary

This study developed a data cleaning and sorting algorithm for paper-based emergency department health records in Lebanon. The algorithm facilitates future epidemiological studies by organizing crucial health information.

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Area of Science:

  • Health Informatics
  • Epidemiology
  • Data Science

Background:

  • Many developing countries rely on paper-based health records, posing challenges for data storage and extraction.
  • Effective data cleaning and sorting guidelines are crucial for epidemiological studies but are scarce in literature.
  • This paper addresses the need for systematic data management in resource-limited settings.

Purpose of the Study:

  • To develop and describe an algorithm for cleaning and sorting health information from paper-based emergency department records.
  • To facilitate future data analysis and epidemiological research using existing paper records.
  • To highlight the challenges and propose solutions for managing health data in Lebanon.

Main Methods:

  • Extracted demographic and health data from emergency department records across three Beirut hospitals.
  • Utilized the International Classification of Disease 10th Edition (ICD-10) for health information categorization.
  • Developed a specific algorithm for sorting and coding the collected health data.

Main Results:

  • Collected and processed 16,537 health record entries.
  • Successfully categorized demographic information for epidemiological use.
  • Created and applied a sorting algorithm to categorize and code health data, enabling numerical and graphical representation.

Conclusions:

  • Paper-based health records in Lebanon present significant storage and extraction limitations.
  • The developed algorithm effectively sorts and categorizes health information from paper records.
  • This work provides a framework for enhanced data analysis and future epidemiological research in similar settings.