A platform for generating clinical intelligence from routine health data in hospitals: PICTURE

Area of Science:

• Health Informatics
• Clinical Data Analytics
• Healthcare Management

Background:

• Electronic health records (EHR) generate vast amounts of routine patient data.
• Current aggregation methods lack standardization for clinical support and operational insights.
• Need for improved data utilization in healthcare settings.

Purpose of the Study:

• To describe a scalable clinical intelligence tool for aggregating and analyzing routine EHR data.
• To demonstrate a proof-of-concept implementation (PICTURE) for on-demand analytics.
• To explore the potential of generalized data analysis for clinical planning and hospital operations.

Main Methods:

• Development of a scalable clinical intelligence tool.
• Implementation of a proof-of-concept system named PICTURE.
• Utilizing generic data models and standardized analytical methods for EHR data reuse.
• Employing open-source languages and modern software development practices.

Main Results:

• Demonstrated a functional proof-of-concept (PICTURE) for clinical data aggregation and analysis.
• Showcased the tool's capability to address informatics consults and clinician queries.
• Validated the potential for improving clinical practice and healthcare operations through data insights.

Conclusions:

• Clinical intelligence tools can effectively aggregate and analyze routine EHR data.
• Standardized, generalized analytical methods enhance data reusability and composability.
• This approach offers significant potential to improve healthcare delivery and operational efficiency.