Risk Assessment for Prolonged Sickness Absence Due to Musculoskeletal Conditions

Study Overview
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Brief Summary
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Musculoskeletal (MSK) conditions are a leading cause of years lived with disability worldwide and for the last decade they have also been the most common cause of sickness absence and disability pension in Norway. Although most sickness absence is short-termed, a small proportion of people with MSK conditions are on long-term sick leave, contributing to large cost due to disbursement of benefits, productivity loss and extensive use of health care. There is growing evidence that long-term sickness absence is harmful to mental and physical health, with a reduced probability of return to work (RtW) with prolonged sickness absence. Thus, focusing on early RtW in people on sick leave due to MSK conditions is important to reduce the burden on both the individual and the society. However, to provide interventions to reduce the duration of sickness absence to all people on sick leave would require enormous resources. By targeting those at risk of long-term sickness absence, resources may be used differently, e.g. more resource-saving. By using information on modifiable risk factors from simple risk assessment tools, health care providers and other stakeholders may facilitate RtW in a better way. The overall purposes of this project are 1) to identify the most accurate screening tool to identify people at a high risk of prolonged sickness absence due to a MSK condition, and 2) to investigate severity of MSK health, health-related quality-of-life, health care consumption, and costs across different risk profiles in people on sick leave due to MSK conditions. We will use registered data on sickness absence from 1 year before to 1 year after inclusion in the study.

Detailed Description
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Main aims are: To compare the predictive ability of the STarT MSK tool and the ÖMPSQ-SF, and other established risk factors for long-term sickness absence (e.g. symptoms of depression and emotional distress, low motivation for returning to work, low self-efficacy, work expectancies) for identifying prolonged sickness absence at 6- and 12-months follow-up due to MSK conditions To develop a prognostic model to predict risk of prolonged sickness absence at 12-month follow-up in people with MSK conditions To assess predictors for high costs (productivity loss and health care use) at 6- and 12-months follow-up in people on sick leave due to MSK conditions The study will also include additional methodological and descriptive aims. Prior to the data collection we translated and culturally adapted the Keele STarT MSK and MSK-HQ following the Beaton guidelines. The study is conducted within the Norwegian Welfare and Labor Administration (NAV) system in collaboration with OsloMet - Oslo Metropolitan University. Data on sickness absence from the NAV registry will be retrieved prospectively in the period from study inclusion to 12 months follow-up, and retrospectively 12 months prior to inclusion in the study. Previous studies show that 30-40% of people with MSK conditions have not RtW after 3 to 12 months. In order to conduct analyses including 15- 20 predictor variables, we aim at including 500-600 people on sick leave due to MSK conditions. As the main outcomes are collected through registries, we do not expect any dropouts.

Official Title
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Risk Assessment for Prolonged Sickness Absence Due to Musculoskeletal Conditions

Conditions
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Musculoskeletal Pain Disorder

Intervention / Treatment
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* Other: Risk assessment


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: People older than 18 years on sick leave due to musculoskeletal pain for at least 4 weeks Exclusion Criteria: People on sick leave for other pain conditions or diseases People not able to read or write Norwegian or English

Ages Eligible for Study
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Minimum Age: 18 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| People on sick leave<br>People on sick leave due to musculoskeletal conditions for at least 4 weeks. | Other: Risk assessment<br>* People on sick leave due to musculoskeletal conditions will be screened for potential risk factors for prolonged sickness absence. No intervention will be given.<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Sickness absence days | Total number of absence days during 12 months of follow-up adjusted for percentage of work and percentage of sickness absence. Register data from the national health and welfare services | 12 months | 
| Time to sustainable return to work | The time until full sustainable return to work, i.e. at least 4 weeks without relapse during 12 months of follow-up. Register data from the national health and welfare services | 12 months | 
| Probability of return to work | Probability of working (i.e. not receiving medical benefits) each month during 12 months of follow-up, measured as repeated events. Register data from the national health and welfare services | 12 months | 
| Proportion who have returned to work | Proportion of people with sustainable return to work (at least 4 weeks) at 12 months. Register data from the national health and welfare services | 12 months | 
| Health care costs | Use of health care will be collected from public registries including Norwegian Patient Registry (NPR), Municipal Patient and User Registry (KPR) and Control and Payment of Health Refunds (KUHR). | 12 months | 
| Sickness absence costs | Sickness absence costs will be calculated based on data from the NAV registry | 12 months | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Musculoskeletal Health Questionnaire (MSK-HQ) | 14 questions scored on a 0-4-point scale, summed up to a 0 to 56 points score, with higher score indicating better musculoskeletal health. | Baseline and 4 weeks | 
| EuroQol 5 Dimensions (EQ5D-5L) | The EQ5D-5L covers five domains: mobility, self-care, activities of daily living, pain/discomfort, and anxiety/depression, scored on a 5-point scale from 0 (worst imaginable health) to 5 (best imaginable health). Responses can be transformed into an index ranging from -0.59 to 1, where -0.59 represents worst possible state and 1 represents perfect health. The EQ5D Visual Analogue Scale (VAS) is also included, which is a question asking about the respondent's self-rated health on a vertical 0 to 100 visual analog scale, with 100 being best health. | Baseline and 4 weeks | 
| Institute of Medical Technology Assessment (iMTA) Productivity Cost Questionnaire (iPCQ) | Measure and value health-related productivity loss for both paid and unpaid work. The instrument is found to be suitable for measuring absenteeism from paid work and productivity loss related to unpaid labor. Nine questions related to paid work and three questions related to unpaid work. | Baseline and 4 weeks | 
| Sickness absence days | Total number of absence days during 6 months of follow-up adjusted for percentage of work and percentage of sickness absence. Register data from the national health and welfare services | 6 months | 
| Time to sustainable return to work | The time until full sustainable return to work, i.e. at least 4 weeks without relapse during 6 months of follow-up. Register data from the national health and welfare services | 6 months | 
| Proportion who have returned to work | Proportion of people with sustainable return to work (at least 4 weeks) at 6 months. Register data from the national health and welfare services | 6 months | 
| Probability of return to work | Probability of working (i.e. not receiving medical benefits) each month during 6 months of follow-up, measured as repeated events. Register data from the national health and welfare services | 6 months | 
| Health care costs | Use of health care will be collected from public registries including Norwegian Patient Registry (NPR), Municipal Patient and User Registry (KPR) and Control and Payment of Health Refunds (KUHR). | 6 months | 
| Sickness absence costs | Sickness absence costs will be calculated based on data from the NAV registry | 6 months | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Risk Assessment