A Framework for Developing and Assessing Custom Case Definitions: A Demonstration Applied to Opioid Overdose in...

Area of Science:

• Public Health Informatics
• Epidemiology
• Data Science

Background:

• Manual review of public health data is slow and labor-intensive.
• Automated case identification requires formal logic-based case definitions.
• Evolving data practices necessitate adaptable surveillance methods.

Purpose of the Study:

• Establish a methodology for developing and evaluating public health case definitions.
• Provide a flexible framework for jurisdictions to tailor case definitions to their specific goals and data.
• Improve the efficiency and accuracy of disease surveillance.

Main Methods:

• Developed a case definition process incorporating free-text and categorical data.
• Illustrated the process using opioid overdose case identification from Maryland EMS data.
• Utilized the Electronic Surveillance System for Early Notification of Community-Based Epidemics (ESSENCE) for data capture.

Main Results:

• Described a case definition evaluation framework.
• Demonstrated the framework's application in developing an opioid overdose case definition for MDH ESSENCE.
• Showcased an iterative development process from conceptualization to data capture.

Conclusions:

• Presented a framework for developing and assessing case definitions.
• Applied the framework to identify opioid overdose incidents from EMS data.
• Offered guidelines for improving local surveillance capabilities using this framework.