Measuring productivity loss due to health: a multi-method approach

Area of Science:

• Occupational Health
• Health Economics
• Human Performance

Background:

• Current health-related productivity loss (HRPL) assessments are valuable but may not fully capture the nuances of all job roles.
• Managerial and knowledge-based positions often require specialized approaches to accurately measure productivity impacts.
• A clear decision-making process is needed to select the most appropriate HRPL methodology.

Purpose of the Study:

• To propose an alternate approach for measuring HRPL in specific job sectors.
• To develop a decision framework for selecting optimal HRPL assessment methodologies.
• To enhance the precision of HRPL cost estimates and return on investment (ROI) calculations.

Main Methods:

• Established human performance theories were applied to adapt existing HRPL measurement techniques.
• A novel model was developed to guide the selection between current and hybrid HRPL assessment strategies.
• A decision framework was created to match HRPL methods with distinct job classifications.

Main Results:

• A proposed model facilitates decisions on using current HRPL measures or adopting a multi-method strategy.
• The study includes a framework to determine the most suitable HRPL methods for various job types.
• The integration of diverse approaches offers potential for more precise HRPL cost estimations.

Conclusions:

• Incorporating additional methodologies can significantly improve the precision of HRPL measurements.
• Enhanced HRPL calculations contribute to more accurate estimations of return on investment (ROI).
• The proposed decision framework supports the selection of appropriate HRPL assessment tools for diverse work environments.