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Structure data entry using graphical input: recording symptoms for multiple sclerosis.

P J McCullagh1, J McGuigan, M Fegan

  • 1School of Computing and Mathematics, University of Ulster.

Studies in Health Technology and Informatics
|December 11, 2003
PubMed
Summary
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Structured Data Entry (SDE) offers efficient patient record input for Multiple Sclerosis (MS) symptoms. This graphical interface aids in objective monitoring and management of MS symptoms, including pain.

Area of Science:

  • Medical Informatics
  • Neurology
  • Human-Computer Interaction

Background:

  • Computer-based patient records require efficient data entry methods.
  • Multiple Sclerosis (MS) management necessitates accurate symptom tracking.
  • Current methods for recording MS symptoms can be ambiguous.

Purpose of the Study:

  • To develop and evaluate a Structured Data Entry (SDE) interface for Multiple Sclerosis (MS) symptom recording.
  • To enhance the efficiency and objectivity of patient data input for MS.
  • To explore the potential of graphical interfaces for symptom monitoring and self-management.

Main Methods:

  • Utilized Structured Data Entry (SDE) to create a prototype interface for MS symptoms.
  • Implemented graphical input for symptom selection (e.g., pain location on a body image).

Related Experiment Videos

  • Employed graphical visual analog scales for severity and attribute representation, transforming input to textual data stored in a hierarchical database.

    • Main Results:

    • The SDE interface facilitates efficient and flexible data entry for MS symptoms.
    • Graphical input provides a less ambiguous coding of symptoms compared to narrative text.
    • The system transforms graphical data into textual information for database storage.
    • The prototype demonstrates potential for objective disease progress monitoring and symptom management.

    Conclusions:

    • Structured Data Entry offers an efficient and objective method for recording Multiple Sclerosis symptoms.
    • Graphical interfaces enhance data entry convenience and reduce ambiguity in symptom coding.
    • This approach may improve the monitoring of disease progression and effectiveness of pain management in MS.
    • The intuitive design has the potential to support patient self-monitoring.