OBJECTIVE: In economic evaluation of health care programmes normally health-related quality of life is part of measurement of a programme's effectiveness and productivity part of its costs. In this paper the relationship between quality of life and productivity is highlighted and empirically assessed in persons suffering from low back pain. METHODS: A secondary analysis was performed on data from a sample of 483 patients treated for low back pain. Periodically, both quality of life (EQ-5D) and productivity indicators for both paid and unpaid work were measured. Mean EQ-5D scores were compared for groups of patients classified by level of productivity. The relationship between quality of life and productivity was also assessed using Spearman rank correlation coefficients. RESULTS: Mean EQ-5D scores for patients without productivity losses were a half to a full standard deviation higher than for patients with the lowest levels of productivity. The correlation between quality of life and productivity was moderate. CONCLUSION: Lower levels of quality of life were associated with efficiency loss and absenteeism. However, due to the moderate strength of the relation the use of information on quality of life to model productivity costs in case of absence of productivity data was not recommended.
OBJECTIVE: In economic evaluation of health care programmes normally health-related quality of life is part of measurement of a programme's effectiveness and productivity part of its costs. In this paper the relationship between quality of life and productivity is highlighted and empirically assessed in persons suffering from low back pain. METHODS: A secondary analysis was performed on data from a sample of 483 patients treated for low back pain. Periodically, both quality of life (EQ-5D) and productivity indicators for both paid and unpaid work were measured. Mean EQ-5D scores were compared for groups of patients classified by level of productivity. The relationship between quality of life and productivity was also assessed using Spearman rank correlation coefficients. RESULTS: Mean EQ-5D scores for patients without productivity losses were a half to a full standard deviation higher than for patients with the lowest levels of productivity. The correlation between quality of life and productivity was moderate. CONCLUSION: Lower levels of quality of life were associated with efficiency loss and absenteeism. However, due to the moderate strength of the relation the use of information on quality of life to model productivity costs in case of absence of productivity data was not recommended.
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