Department of Health, Medicine and Caring Sciences, Division of Society and Health, Center for Medical Technology Assessment, Linköping University, Linköping, Sweden.
Department of Health, Medicine and Caring Sciences, Division of Society and Health, Unit of Public Health, Linköping University, Linköping, Sweden.
Work. 2021;68(4):1091-1100. doi: 10.3233/WOR-213439.
Health problems due to musculoskeletal disorders (MSD) and common mental disorders (CMD) result in costs due to lost productivity.
This study aimed to increase knowledge of employers' productivity loss due to employees' presenteeism and sickness absence.
A web questionnaire was sent to employers of workers who were sick-listed for more than 30 days due to MSD or CMD, response rate: 50%, n = 198. Presenteeism and the impact on productivity before and after sick leave, and the performance of work tasks by replacement workers during sick leave, were measured using supervisors' ratings.
The average loss of productivity per sick-leave case amounted to almost 10 weeks, 53%of productivity loss was attributable to presenteeism and 47%to lower productivity by replacement workers. Employees with a CMD diagnosis had significantly higher presenteeism-related productivity loss than those with MSD.
Employers experienced substantial productivity loss associated with employees' presenteeism and sick leave. Whether the supervisory rating of presenteeism is preferable to employee self-rating needs to be studied further. The long duration of presenteeism is counter-productive to resource-efficient organisations and indicates the need for improved supervisory skills to identify workers with poor health, both before and after sick leave.
肌肉骨骼疾病(MSD)和常见精神障碍(CMD)导致的健康问题会造成生产力损失方面的成本。
本研究旨在提高雇主对员工因生产力下降而导致的生产力损失的认识。
向因 MSD 或 CMD 请病假超过 30 天的员工的雇主发送了一份网络问卷,回应率为 50%,n=198。使用主管评估来衡量员工在病假前后的生产力下降和工作任务表现。
每个病假案例的平均生产力损失近 10 周,53%的生产力损失归因于出勤,47%归因于替代工人的生产力下降。患有 CMD 诊断的员工的与出勤相关的生产力损失明显高于患有 MSD 的员工。
雇主经历了与员工出勤和病假相关的重大生产力损失。主管对出勤的评估是否优于员工自评,需要进一步研究。出勤时间过长不利于资源效率高的组织,并表明需要提高主管技能,以便在病假前后识别健康状况不佳的员工。