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Related Experiment Videos

Implementing a low-cost computer-based patient record: a controlled vocabulary reduces data base design complexity

D J Essin1, T L Lincoln

  • 1LAC+USC Medical Center, USA.

Proceedings. Symposium on Computer Applications in Medical Care
|January 1, 1995
PubMed
Summary

A simplified computer-based patient record (CPR) system was developed using a relational model and controlled vocabulary. This cost-effective, scalable solution is ideal for small practices, improving data management and accessibility.

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Area of Science:

  • Health Informatics
  • Medical Software Development
  • Database Management Systems

Background:

  • Computer-based patient record (CPR) systems are essential for modern healthcare, but high development and maintenance costs often limit their adoption in solo and small group practices.
  • Design complexity is a primary driver of these costs, impacting affordability and reliability.

Purpose of the Study:

  • To develop a cost-effective and reliable CPR system suitable for solo and small group practice settings.
  • To reduce development, deployment, and maintenance expenses by simplifying system design.

Main Methods:

  • Developed a simplified relational database model.
  • Integrated a controlled vocabulary for data standardization.
  • Implemented the CPR system using inexpensive components and standard Structured Query Language (SQL).

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Main Results:

  • The implemented CPR system effectively captures and stores diverse clinical data, including patient examinations, clinical notes, and test results.
  • Data can be accessed in a familiar document format and via SQL for further processing.
  • The system utilizes affordable components, making it economically viable for small practices.

Conclusions:

  • The simplified relational model and controlled vocabulary approach significantly reduce the complexity and cost of CPR system development.
  • The developed CPR system is scalable, reliable, and affordable, offering a practical solution for small healthcare practices.
  • This approach enhances data accessibility and management for improved clinical workflows.