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Prognostic factors for medical and productivity costs, and return to work after trauma.

ABSTRACT: AIM:The aim of this study was to determine prognostic factors for medical and productivity costs, and return to work (RTW) during the first two years after trauma in a clinical trauma population. METHODS:This prospective multicentre observational study followed all adult trauma patients (?18 years) admitted to a hospital in Noord-Brabant, the Netherlands from August 2015 through November 2016. Health care consumption, productivity loss and return to work were measured in questionnaires at 1 week, 1, 3, 6, 12 and 24 months after injury. Data was linked with hospital registries. Prognostic factors for medical costs and productivity costs were analysed with log-linked gamma generalized linear models. Prognostic factors for RTW were assessed with Cox proportional hazards model. The predictive ability of the models was assessed with McFadden R2 (explained variance) and c-statistics (discrimination). RESULTS:A total of 3785 trauma patients (39% of total study population) responded to at least one follow-up questionnaire. Mean medical costs per patient (€9,710) and mean productivity costs per patient (€9,000) varied widely. Prognostic factors for high medical costs were higher age, female gender, spine injury, lower extremity injury, severe head injury, high injury severity, comorbidities, and pre-injury health status. Productivity costs were highest in males, and in patients with spinal cord injury, high injury severity, longer length of stay at the hospital and patients admitted to the ICU. Prognostic factors for RTW were high educational level, male gender, low injury severity, shorter length of stay at the hospital and absence of comorbidity. CONCLUSIONS:Productivity costs and RTW should be considered when assessing the economic impact of injury in addition to medical costs. Prognostic factors may assist in identifying high cost groups with potentially modifiable factors for targeted preventive interventions, hence reducing costs and increasing RTW rates.

SUBMITTER: de Munter L

PROVIDER: S-EPMC7094860 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Prognostic factors for medical and productivity costs, and return to work after trauma.

de Munter Leonie L Geraerds A J L M AJLM de Jongh Mariska A C MAC van der Vlegel Marjolein M Steyerberg Ewout W EW Haagsma Juanita A JA Polinder Suzanne S

PloS one 20200325 3

<h4>Aim</h4>The aim of this study was to determine prognostic factors for medical and productivity costs, and return to work (RTW) during the first two years after trauma in a clinical trauma population.<h4>Methods</h4>This prospective multicentre observational study followed all adult trauma patients (≥18 years) admitted to a hospital in Noord-Brabant, the Netherlands from August 2015 through November 2016. Health care consumption, productivity loss and return to work were measured in questionn ...[more]

PMID: 32210472

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Project description:BackgroundThrough improvements in trauma care there has been a decline in injury mortality, as more people survive severe trauma. Patients who survive severe trauma are at risk of long-term disabilities which may place a high economic burden on society. The purpose of this study was to estimate the health care and productivity costs of severe trauma patients up to 24 months after sustaining the injury. Furthermore, we investigated the impact of injury severity level on health care utilization and costs and determined predictors for health care and productivity costs.MethodsThis prospective cohort study included adult trauma patients with severe injury (ISS≥16). Data on in-hospital health care use, 24-month post-hospital health care use and productivity loss were obtained from hospital registry data and collected with the iMTA Medical Consumption and Productivity Cost Questionnaire. The questionnaires were completed 1 week and 1, 3, 6, 12 and 24 months after injury. Log-linked gamma generalized linear models were used to investigate the drivers of health care and productivity costs.ResultsIn total, 174 severe injury patients were included in this study. The median age of participants was 55 years and the majority were male (66.1%). The mean hospital stay was 14.2 (SD = 13.5) days. Patients with paid employment returned to work 21 weeks after injury. In total, the mean costs per patient were €24,760 with in-hospital costs of €11,930, post-hospital costs of €7,770 and productivity costs of €8,800. Having an ISS ≥25 and lower health status were predictors of high health care costs and male sex was associated with higher productivity costs.ConclusionsBoth health care and productivity costs increased with injury severity, although large differences were observed between patients. It is important for decision-makers to consider not only in-hospital health care utilization but also the long-term consequences and associated costs related to rehabilitation and productivity loss.

Project description:IntroductionExisting evidence of returning-to-work (RTW) after cancer comes predominately from Western settings, with none prospectively examined since the initial diagnostic phase. This study prospectively documents RTW-rate, time-to-RTW, work productivity loss, and activity impairment, within the first-year post-surgery among Chinese women with breast cancer (BCW) and identify potential causal co-variants.MethodsThis observational longitudinal study followed 371 Chinese BCW who were employed/self-employed at the time of diagnosis at 4-week post-surgery (baseline). RTW-status and time-to-RTW were assessed at baseline (T1), 4-month (T2), 6-month (T3), and 12-month (T4) post-baseline. WPAI work productivity loss and activity impairment were assessed at T4. Baseline covariates included demographics, medical-related factors, work satisfaction, perceived work demand, work condition, RTW self-efficacy, B-IPQ illness perception, COST financial well-being, EORTC QLQ-C30 and QLQ-BR23 physical and psychosocial functioning, and HADS psychological distress.ResultsA 68.2% RTW-rate (at 12-month post-surgery), prolonged delay in RTW (median = 183 days), and significant proportions of T4 work productivity loss (20%), and activity impairment (26%), were seen. BCW who were blue-collar workers with lower household income, poorer financial well-being, lower RTW self-efficacy, poorer job satisfaction, poorer illness perception, greater physical symptom distress, impaired physical functioning, and unfavorable work conditions were more likely to experience undesired work-related outcomes.DiscussionUsing a multifactorial approach, effective RTW interventions should focus on not only symptom management, but also to address psychosocial and work-environmental concerns. An organizational or policy level intervention involving a multidisciplinary team comprising nurses, psychologists, occupational health professionals, and relevant stakeholders in the workplace might be helpful in developing a tailored organizational policy promoting work-related outcomes in BCW.

Project description:BACKGROUND: Workers with persistent disabilities after orthopaedic trauma may need occupational rehabilitation. Despite various risk profiles for non-return-to-work (non-RTW), there is no available predictive model. Moreover, injured workers may have various origins (immigrant workers), which may either affect their return to work or their eligibility for research purposes. The aim of this study was to develop and validate a predictive model that estimates the likelihood of non-RTW after occupational rehabilitation using predictors which do not rely on the worker's background. METHODS: Prospective cohort study (3177 participants, native (51%) and immigrant workers (49%)) with two samples: a) Development sample with patients from 2004 to 2007 with Full and Reduced Models, b) External validation of the Reduced Model with patients from 2008 to March 2010. We collected patients' data and biopsychosocial complexity with an observer rated interview (INTERMED). Non-RTW was assessed two years after discharge from the rehabilitation. Discrimination was assessed by the area under the receiver operating curve (AUC) and calibration was evaluated with a calibration plot. The model was reduced with random forests. RESULTS: At 2 years, the non-RTW status was known for 2462 patients (77.5% of the total sample). The prevalence of non-RTW was 50%. The full model (36 items) and the reduced model (19 items) had acceptable discrimination performance (AUC 0.75, 95% CI 0.72 to 0.78 and 0.74, 95% CI 0.71 to 0.76, respectively) and good calibration. For the validation model, the discrimination performance was acceptable (AUC 0.73; 95% CI 0.70 to 0.77) and calibration was also adequate. CONCLUSIONS: Non-RTW may be predicted with a simple model constructed with variables independent of the patient's education and language fluency. This model is useful for all kinds of trauma in order to adjust for case mix and it is applicable to vulnerable populations like immigrant workers.

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Prognostic factors for medical and productivity costs, and return to work after trauma.

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Prognostic factors for medical and productivity costs, and return to work after trauma.

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