Predicting long-term sickness absence with employee questionnaires and administrative records: a prospective cohort study of hospital employees.

IF 4.7 2区 医学 Q1 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Solja T Nyberg, Marko Elovainio, Jaana Pentti, Philipp Frank, Jenni Ervasti, Mikko Härmä, Aki Koskinen, Laura Peutere, Annina Ropponen, Jussi Vahtera, Marianna Virtanen, Jaakko Airaksinen, G David Batty, Mika Kivimäki
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引用次数: 0

Abstract

Objective: This study aimed to compare the utility of risk estimation derived from questionnaires and administrative records in predicting long-term sickness absence among shift workers.

Methods: This prospective cohort study comprised 3197 shift-working hospital employees (mean age 44.5 years, 88.0% women) who responded to a brief 8-item questionnaire on work disability risk factors and were linked to 28 variables on their working hour and workplace characteristics obtained from administrative registries at study baseline. The primary outcome was the first sickness absence lasting ≥90 days during a 4-year follow-up.

Results: The C-index of 0.73 [95% confidence interval (CI) 0.70-0.77] for a questionnaire-only based prediction model, 0.71 (95% CI 0.67-0.75) for an administrative records-only model, and 0.79 (95% CI 0.76-0.82) for a model combining variables from both data sources indicated good discriminatory ability. For a 5%-estimated risk as a threshold for positive test results, the detection rates were 76%, 74%, and 75% and the false positive rates were 40%, 45% and 34% for the three models. For a 20%-risk threshold, the corresponding detection rates were 14%, 8%, and 27% and the false positive rates were 2%, 2%, and 4%. To detect one true positive case with these models, the number of false positive cases accompanied varied between 7 and 10 using the 5%-estimated risk, and between 2 and 3 using the 20%-estimated risk cut-off. The pattern of results was similar using 30-day sickness absence as the outcome.

Conclusions: The best predictive performance was reached with a model including both questionnaire responses and administrative records. Prediction was almost as accurate with models using only variables from one of these data sources. Further research is needed to examine the generalizability of these findings.

用员工问卷和管理记录预测长期病假:一项针对医院员工的前瞻性队列研究。
目的:本研究旨在比较从问卷和行政记录中得出的风险估计在预测轮班工人长期病假方面的效用。方法:这项前瞻性队列研究包括3197名轮班工作的医院员工(平均年龄44.5岁,88.0%为女性),他们对一份关于工作残疾风险因素的8项简短问卷做出了回应,并与研究基线时从行政登记处获得的28个关于工作时间和工作场所特征的变量相关联。主要结果是在4年的随访中第一次病假持续≥90天。结果:仅基于问卷的预测模型的C指数为0.73[95%置信区间(CI)0.70-0.77],仅基于行政记录的预测模型为0.71(95%CI 0.67-0.75),对于组合来自两个数据源的变量的模型,0.79(95%CI 0.76-0.82)表示良好的判别能力。对于作为阳性检测结果阈值的5%估计风险,三个模型的检测率分别为76%、74%和75%,假阳性率分别为40%、45%和34%。对于20%风险阈值,相应的检测率分别为14%、8%和27%,假阳性率分别为2%、2%和4%。为了用这些模型检测一个真阳性病例,使用5%的估计风险,伴随的假阳性病例数在7到10之间变化,使用20%的估计风险临界值,在2到3之间变化。使用30天病假作为结果,结果模式相似。结论:模型包括问卷调查和行政记录,达到了最佳的预测性能。模型只使用其中一个数据源的变量,预测几乎同样准确。需要进一步的研究来检验这些发现的可推广性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Scandinavian journal of work, environment & health
Scandinavian journal of work, environment & health 医学-公共卫生、环境卫生与职业卫生
CiteScore
8.20
自引率
9.50%
发文量
65
审稿时长
>12 weeks
期刊介绍: The aim of the Journal is to promote research in the fields of occupational and environmental health and safety and to increase knowledge through the publication of original research articles, systematic reviews, and other information of high interest. Areas of interest include occupational and environmental epidemiology, occupational and environmental medicine, psychosocial factors at work, physical work load, physical activity work-related mental and musculoskeletal problems, aging, work ability and return to work, working hours and health, occupational hygiene and toxicology, work safety and injury epidemiology as well as occupational health services. In addition to observational studies, quasi-experimental and intervention studies are welcome as well as methodological papers, occupational cohort profiles, and studies associated with economic evaluation. The Journal also publishes short communications, case reports, commentaries, discussion papers, clinical questions, consensus reports, meeting reports, other reports, book reviews, news, and announcements (jobs, courses, events etc).
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