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Dissertation Defense :: A New Tool to Measure the Relationship between Health-Related Quality of Life and Workforce Productivity

David Huang - Advisors: Dr. Brani Vidakovic, Dr. Paula Edwards, Committee: Dr. Dave Goldsman, Dr. Paul Griffin, Dr. Eva Lee

DATE: Friday, May 9, 2008
TIME: 2:00 PM
LOCATION: Poole Board Room (236), ISyE Main Building

Quality of life and productivity are two important measures in health outcomes that usually require the use of self-reported surveys for accurate assessment. Measuring health-related quality of life (HRQOL) has been established as an important field in the past century because of its implications for chronic disease impact, clinical effectiveness, resource utilization, medication expenditures, and reimbursement for payers. Many psychometrically validated instruments exist for both general and specific population use, and standards such as QALY and Short-Form-36 (SF-36) are commonly used to test and validate new instruments to measure various aspects of health.

Another health measure that has attracted a significant amount of attention in recent years is that of workforce productivity. Many productivity studies focus on measuring the amount of work loss incurred by employees, whether employees are absent from work, measured as absenteeism; or present at work, measured as presenteeism. Measuring overall workforce productivity typically involves creating and implementing self-reported employee surveys. In rare cases where performance may be measured using objective measures such as number of items produced or length of customer service calls taken, productivity as measured by both presenteeism and absenteeism can be measured using numerical indices that are relevant and easily understood. However, self-reported workforce surveys are the only practical method of measuring workforce productivity that can be used in a variety of settings and job functions.

A new survey that combines questions from existing HRQOL and workforce productivity surveys, Health-Related Quality of Life and Work Productivity Questionnaire (HQWP), was constructed and tested using a descriptive, cross-sectional study. As expected, HRQOL and productivity loss were found to be negatively correlated. In addition, staff were found to have significantly higher levels of 30-day continuous absenteeism and binary absenteeism than faculty, but faculty had higher levels of 30-day presenteeism and lower levels of 7-day productivity. For faculty and staff groups separately and together, MCS was found to be a significant predictor for 30-day binary absenteeism (binary logistic regression) and presenteeismrelated questions (linear regression); however, HRQOL predictors varied for 30-day presenteeism (ordinal regression), although role emotional scores were significant for all groups. Thus, we also concluded that mental health measures were a stronger predictor of productivity, both absenteeism and presenteeism, than physical health measures. Other statistical analyses performed include PCA factor analyses on each of the major output covariates.

This study reveals statistically significant differences in the absenteeism and presenteeism levels of faculty and staff. A better understanding of reasons for absenteeism and presenteeism could help inform targeted workplace policies and programs to reduce employer indirect costs related to productivity. By addressing these problems before health conditions arise, improving not only productivity but also saving companies and employees direct (medical, pharmacy, etc.) costs and improving both quantity and quality of life years.

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