Electronic Medical Records for Mental Disorders: What Data Elements Should These Systems Contain?

Area of Science:

• Health Informatics
• Mental Health Research
• Data Management

Background:

• Electronic Medical Record (EMR) systems are crucial for effective health data collection.
• Standardizing data elements in EMRs is essential for comprehensive mental health care.
• Current EMR systems may lack specific data fields crucial for mental disorder management.

Purpose of the Study:

• To determine the essential data elements required for EMRs specifically for mental disorders.
• To establish a validated list of data fields for optimizing mental health record-keeping.

Main Methods:

• Conducted a literature review to identify preliminary data elements.
• Randomly selected 50 mental disorder patient medical records.
• Surveyed 33 mental health specialists using a questionnaire for validation.

Main Results:

• Identified seven main classes of data elements: patient demographics, physician/patient administrative data, history, clinical data, treatment, and financial data.
• Defined 10 subclasses within these categories.
• Validated and introduced a list of 140 essential data elements for mental disorder EMRs.

Conclusions:

• A comprehensive set of 140 essential data elements has been identified for mental disorder EMRs.
• These elements are categorized into seven classes and 10 subclasses for structured data collection.
• The findings provide a foundation for developing improved EMR systems in mental health.