Predicting return to work among sickness-certified patients in general practice: Properties of two assessment tools

Celsing, Anna-Sophia von; Svärdsudd, Kurt; Wallman, Thorne

doi:10.3109/03009734.2014.922143

Cited by 6 publications

(6 citation statements)

References 29 publications

(21 reference statements)

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“…An important factor might be the timing of rehabilitation. In a United Kingdom review, it was found that in the first 3-6 weeks of sick leave, the likelihood of recovery and rapid sick leave conclusion is high, with or without healthcare intervention [29], as was found in another report from the present study [13]. After 6 weeks of sickness absence in workers, the risks of long- term incapacity increased by 10-20%, and after 6 months, there was only a 50% chance of returning to a previous job.…”

Section: Discussionsupporting

confidence: 78%

“…Having access to the individual risk factor pattern of subjects on sick leave provides the possibility of early identification of patients who may not conclude their sick leave period as expected. In another previous report from this study, a further development of the risk factor concept was presented in the form of nomograms, where the risk of not concluding sick leave within the expected time might be obtained based on the three most important risk factors [13].…”

Section: Introductionmentioning

confidence: 99%

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Effects of a vocational rehabilitation programme on return to work among sick-listed primary health care patients: a population-based matched, case-control study

et al. 2020

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Background: To evaluate the efficacy of a multidisciplinary vocational programme in sick-listed, primary health care patients as compared to matched non-programme patients. Methods: The design was a 3-year prospective population-based, matched case-control study. It was set in a large primary healthcare centre in the city of Eskilstuna, Sweden. The subjects were 943 sickness-certified patients (482 women and 461 men). 170 high-risk patients and a matched control group (n = 340) with similar risk for not returning to work within expected time, based on propensity score was created. The intervention group passed a multidisciplinary medical assessment and a coordinated vocational programme, while the control group received usual care by their general practitioner. Main outcome was sick leave conclusion and the day when it occurred. Results: The follow-up time was subdivided into four periods. During the first two periods, days 1-14 and days 15-112 after baseline, the intervention group had a significantly lower sick leave conclusion rate than the control group (hazard ratios, (HR) 0.32, 95% CI 0.20-0.51, p < 0.0001 and 0.47, 95% CI 0.35-0.64). During the third period, days 113-365, the intervention group had an insignificantly lower conclusion rate (HR 0.70, 95% CI 0.46-1.08, p = 0.10), and during the fourth follow-up period, days 366-1096, the intervention group had an insignificantly higher conclusion rate than the control group (HR 1.16, 95% CI 0.69-1.96, p = 0.58). Across the total follow-up period, the intervention group had a lower conclusion rate than the control group (HR 0.55, 95% CI 0.45-0.66, p < 0.0001). Conclusions: No positive significant effects of the rehabilitation programme on time to sick leave conclusion were found.

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Section: Discussionsupporting

confidence: 78%

Section: Introductionmentioning

confidence: 99%

Effects of a vocational rehabilitation programme on return to work among sick-listed primary health care patients: a population-based matched, case-control study

et al. 2020

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show abstract

“…An important factor might be the timing of rehabilitation. In a United Kingdom review, it was found that in the first 3-6 weeks of sick leave, the likelihood of recovery and rapid sick leave conclusion is high, with or without healthcare intervention [30], as was found in another report from the present study [13]. After 6 weeks of sickness absence in workers, the risks of long-term incapacity increased by 10-20%, and after 6 months, there was only a 50% chance of returning to a previous job.…”

Section: Discussionsupporting

confidence: 78%

Effects of a vocational rehabilitation programme on return to work among sick-listed primary health care patients A population-based matched, case-control study

Celsing

Kristiansson²,

Svärdsudd³

et al. 2019

Preprint

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Background: To evaluate the efficacy of a multidisciplinary vocational programme in sick-listed, primary health care patients as compared to matched non-programme patients. Methods: The design was a 3-year prospective population-based, matched case-control study. It was set in a large primary healthcare centre in the city of Eskilstuna, Sweden. The subjects were 943 sickness-certified patients (482 women and 461 men). Intervention: 170 high-risk patients and a matched control group (n = 340) with similar risk for not returning to work within expected time, based on propensity score was created. The intervention group passed a multidisciplinary medical assessment and a coordinated vocational programme, while the control group received usual care by their general practitioner. Main outcome measures: Sick leave conclusion and the day when it occurred. Results: The follow-up time was subdivided into four periods. During the first two periods, days 1–14 and days 15–112 after baseline, the intervention group had a significantly lower sick leave conclusion rate than the control group (hazard ratios, (HR) 0.32, 95% CI 0.20–0.51, p < 0.0001 and 0.47, 95% CI 0.35–0.64). During the third period, days 113–365, the intervention group had an insignificantly lower conclusion rate (HR 0.70, 95% CI 0.46–1.08, p = 0.10), and during the fourth follow-up period, days 366–1096, the intervention group had an insignificantly higher conclusion rate than the control group (HR 1.16, 95% CI 0.69–1.96, p = 0.58). Across the total follow-up period, the intervention group had a lower conclusion rate than the control group (HR 0.55, 95% CI 0.45–0.66, p < 0.0001). Conclusions: No positive significant effects of the rehabilitation programme on time to sick leave conclusion were found.

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“…A comprehensive literature search strategy adapted from a 2017 review [2] was performed using Medline and yet, no studies were identified which categorized prognostic variables and used an analytical approach resembling the order of information obtained in a clinical setting. For this reason, direct comparison with previous studies was not possible, but some studies reported measures that can be compared with the current study [33, 34]. In a Norwegian study [33], the sickness absentees’ own prediction of sick leave duration ≥26 weeks yielded a slightly better PPV (0.78) than any of the models in the current study.…”

Section: Discussionmentioning

confidence: 78%

“…Rehabilitation professionals in another study [34] predicted the chance of RTW based on sick leave duration, reason for sick leave, unemployment, age > 45 years, female sex and ‘gut feeling’. Their prediction was concordant with actual RTW in 73% and thus lower than the specificity estimates of all four models in the current study.…”

Section: Discussionmentioning

confidence: 99%

Prediction of 2-year work participation in sickness absentees with neck or shoulder pain: the contribution of demographic, patient-reported, clinical and imaging information

Moll

Schmidt

Stapelfeldt

et al. 2019

BMC Musculoskelet Disord

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BackgroundIn cases of neck and shoulder pain, the responsibility for assessing work prognosis is held by clinicians with access to different domains of information. One of these domains is magnetic resonance imaging (MRI), and although MRI is increasingly used, it is unknown which domains of information contribute the most to the prediction of work prognosis. This retrospective cohort study explored the contribution of demographic, patient-reported, clinical, and MRI information to the prediction of work participation in sickness absentees with neck or shoulder pain.MethodsFrom a secondary care setting, 168 sickness absentees with neck or shoulder pain were included. Based on registry data, a successful work outcome was defined as ≥50% work participation score (WPS) from Weeks 1 to 104 after enrolment. Prognostic variables were categorized into four domains (demographic, patient-reported, clinical, and MRI) resembling the order of information obtained in a clinical setting. Crude logistic regression analyses were used to identify prognostic variables for each domain (p < 0.2). This was followed by multivariable analyses including the identified variables in a domain-wise order. For each added domain, the probability of successful WPS was dichotomized leaving two possible classifications: ≥ 50% chance of successful WPS or not. In cross-tabulations of chance and the actual WPS outcome, positive and negative predictive values (PPV and NPV), sensitivity, specificity and area under the curve (AUC) were calculated.ResultsThe combination of demographic and patient-reported variables yielded an NPV of 0.72 and a PPV of 0.67, while specificity was 0.82, sensitivity 0.54 and AUC 0.77. None of these values improved notably by adding clinical and MRI variables as predictors of successful WPS.ConclusionsThese results suggest that - among sickness absentees with neck or shoulder pain – clinical and MRI variables provide no additional information for the prediction of work participation compared with only demographic and patient-reported information.

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Predicting return to work among sickness-certified patients in general practice: Properties of two assessment tools

Cited by 6 publications

References 29 publications

Effects of a vocational rehabilitation programme on return to work among sick-listed primary health care patients: a population-based matched, case-control study

Effects of a vocational rehabilitation programme on return to work among sick-listed primary health care patients: a population-based matched, case-control study

Effects of a vocational rehabilitation programme on return to work among sick-listed primary health care patients A population-based matched, case-control study

Prediction of 2-year work participation in sickness absentees with neck or shoulder pain: the contribution of demographic, patient-reported, clinical and imaging information

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