Secondary use of clinical data

Area of Science:

• Health Informatics
• Clinical Research
• Data Science

Background:

• Clinicians generate vast amounts of data crucial for patient care continuity and referrals.
• Electronic quality (eQuality) monitoring uses this data for practice improvement and care activity generation.
• Traditionally, patient records were manually abstracted for clinical research.

Purpose of the Study:

• To highlight the potential of computable electronic health record (EHR) data for retrospective research.
• To introduce the concept of electronic studies (eStudies) for rapid research and inquiry.
• To identify barriers hindering the widespread adoption of eStudies.

Main Methods:

• Leveraging computable EHR data for retrospective research.
• Utilizing eQuality monitoring for generating alerts and care activities.
• Identifying challenges in data interoperability and computable measure definitions.

Main Results:

• Computable EHR data significantly accelerates retrospective research capabilities.
• eStudies offer a lower activation energy for posing new research questions.
• Identified barriers include data interoperability, computable definitions, and professional training.

Conclusions:

• Transitioning to computable EHR data enhances research speed and efficiency.
• Addressing identified barriers is crucial for unlocking the full potential of eStudies.
• Developing common methods for distributing computable best practice rules is essential for evidence dissemination.