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Related Experiment Videos

[Database application for information on post-surgical evolution after functional neurosurgery].

J Teijeiro-Amador1, E Guerra-Figueredo, J M Morales

  • 1Departamento de Neurocirugía. Centro Internacional de Restauración Neurológica (CIREN), La Habana, Cuba. jaun@neuro.sld.cu

Revista De Neurologia
|October 10, 2002
PubMed
Summary
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This study developed an automated database system to efficiently track patient data for movement disorders like Parkinson's disease. The tool streamlines clinical evolution studies and enhances data reliability.

Area of Science:

  • Neurosurgery
  • Medical Informatics
  • Movement Disorders

Background:

  • Quantitative scales are used internationally to assess functional status in movement disorders.
  • Patient data over time is crucial for studying disease evolution and performing statistical analyses.
  • Current methods for managing this data can be time-consuming and prone to error.

Purpose of the Study:

  • To develop an efficient, reliable, and automated tool for managing clinical data of patients with movement disorders.
  • To facilitate the study of disease progression and statistical analysis of patient outcomes.
  • To improve the handling of pre- and post-surgical information for neurosurgery patients.

Main Methods:

  • Selection of key variables from international protocols for movement disorders.

Related Experiment Videos

  • Development of a Windows-based database application using Delphi 3.0 and SQL.
  • Implementation of features for data collection, automated processing, and export.

    • Main Results:

    • A validated database system for automatic handling of clinical evolution data in functional neurosurgery patients was created.
    • The system enables efficient collection, fast searching, data processing, and standardized data export.
    • The database system has been successfully utilized for over three years in a clinical setting.

    Conclusions:

    • The developed system significantly reduces the time and effort required for monitoring post-surgical patient evolution.
    • The automation and structured data handling increase the reliability of research findings.
    • This tool enhances the efficiency and accuracy of clinical research in movement disorders.