Knowledge coupling: implementing outcomes measurement through the disciplined and routine control of inputs

Area of Science:

• Health Informatics
• Systems Engineering in Healthcare
• Clinical Knowledge Management

Background:

• Outcomes measurement is crucial for healthcare quality assessment.
• Current healthcare systems often lack control over critical inputs, hindering accurate outcomes measurement.
• Individual practitioner knowledge is vital but difficult to standardize and apply consistently.

Purpose of the Study:

• To identify a systemic solution for improving outcomes measurement in healthcare.
• To propose a method for standardizing and controlling healthcare system inputs.
• To demonstrate how technology can enhance the reliability and accuracy of healthcare outcomes.

Main Methods:

• Proposing the integration of critical practitioner knowledge into computer-based knowledge coupling tools.
• Utilizing these tools to systematically track and control system inputs.
• Leveraging computational processing for unbiased and error-free information handling.

Main Results:

• Computer-based tools can effectively track and control healthcare system inputs.
• Information processing by these tools is free from error and bias.
• Outcomes measurement becomes an inherent result of controlled system operations.

Conclusions:

• Shifting healthcare conceptualization and implementation to computer-controlled systems is a paradigm shift.
• This approach ensures that outcomes measurement is a natural consequence of disciplined processes.
• The proposed system corrects fundamental flaws in current healthcare delivery and measurement.