Learning Health Systems and Laboratory Medicine

Area of Science:

• Health Services Research
• Laboratory Medicine
• Health Informatics

Background:

• Healthcare systems face challenges in delivering optimal treatments due to rapid scientific advancements and structural changes.
• Learning Health Systems (LHS) offer a solution by continuously analyzing data to generate evidence and inform decisions.

Purpose of the Study:

• To investigate the integration and role of laboratory medicine within Learning Health Systems.
• To evaluate existing laboratory medicine-focused LHS based on scope, technology, evidence generation, data-action latency, and social factors.

Main Methods:

• Review and analysis of existing large-scale LHS and laboratory-specific systems.
• Evaluation of enabling technologies, evidence generation architectures, and data-action latency.
• Consideration of social aspects and stakeholder roles in LHS implementation.

Main Results:

• Laboratory medicine serves as a central information source in many large-scale LHS.
• Specialized systems, like external quality assessments, demonstrate long-standing success in laboratory data analysis and device surveillance.
• Emerging technologies, including wearables and enhanced connectivity, offer new avenues for LHS in laboratory medicine.

Conclusions:

• Laboratory medicine is integral to effective Learning Health Systems.
• Recognizing and integrating laboratory medicine within broader "systems of systems" is essential for generating superior evidence.
• Further research into stakeholder roles is needed to overcome barriers and ensure successful LHS development and maintenance.