Prevalence, recovery patterns and predictors of quality of life and costs after non-fatal injury: the Brabant Injury Outcome Surveillance (BIOS) study

Jongh, Mariska A. C. de; Kruithof, Nena; Gosens, Taco; Ree, Cornelis L. P. van de; Munter, Leonie de; Brouwers, Lars; Polinder, Suzanne; Lansink, Koen W.W.; BIOS-group,

doi:10.1136/injuryprev-2016-042032

Cited by 40 publications

(44 citation statements)

References 86 publications

(66 reference statements)

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“…This study was performed with data from the Brabant Injury Outcome Surveillance (BIOS) study [17]. The BIOS study is a prospective observational follow-up cohort study that was approved by the Medical Ethics Committee Brabant (NL50258.028.…”

Section: Methodsmentioning

confidence: 99%

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

et al. 2020

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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 R 2 (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.

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Section: Methodsmentioning

confidence: 99%

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

et al. 2020

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“…This study was part of the Brabant Injury Outcome Surveillance (BIOS) study, which was registered at http://clinicaltrials.gov (NCT02508675); the protocol has been published previously. Patients were included if they were admitted to an ICU or ward in the Noord‐Brabant region of the Netherlands within 48 h after injury and survived to hospital discharge between August 2015 and November 2016.…”

Section: Methodsmentioning

confidence: 99%

Predicting health status in the first year after trauma

Munter

Polinder

Ree

et al. 2019

British Journal of Surgery

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Background: Although mortality rates following major trauma are continuing to decline, a growing number of patients are experiencing long-term disability. The aim of this study was to identify factors associated with health status in the first year following trauma and develop prediction models based on a defined trauma population. Methods: The Brabant Injury Outcome Surveillance (BIOS) study was a multicentre prospective observational cohort study. Adult patients with traumatic injury were included from August 2015 to November 2016 if admitted to one of the hospitals of the Noord-Brabant region in the Netherlands. Outcome measures were EuroQol Five Dimensions 5D-3L (EQ-5D™ utility and visual analogue scale (VAS))and Health Utilities Index (HUI) 2 and 3 scores 1 week and 1, 3, 6 and 12 months after injury. Prediction models were developed using linear mixed models, with patient characteristics, preinjury health status, injury severity and frailty as possible predictors. Predictors that were significant (P < 0⋅050) for one of the outcome measures were included in all models. Performance was assessed using explained variance (R 2 ).Results: In total, 4883 patients participated in the BIOS study (50⋅0 per cent of the total), of whom 3366 completed the preinjury questionnaires. Preinjury health status and frailty were the strongest predictors of health status during follow-up. Age, sex, educational level, severe head or face injury, severe torso injury, injury severity, Functional Capacity Index score, co-morbidity and duration of hospital stay were also relevant in the multivariable models predicting health status. R 2 ranged from 35 per cent for EQ-VAS to 48 per cent for HUI 3.

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“…The study used the Brabant Injury Outcome Surveillance (BIOS) database, a multicentre observational follow-up cohort study, which is described elsewhere [12]. Data were collected in the period August 2015-November 2016.…”

Section: Datasetmentioning

confidence: 99%

Burden of illness of hip fractures in elderly Dutch patients

et al. 2020

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Patients with hip fractures experience reduced health-related quality of life and have a reduced life expectancy. Patients' utilization of healthcare leads to costs to society. The results of the study can be used in future economic evaluations of treatments for hip fractures.Purpose Hip fractures are associated with high mortality, reduced quality of life, and increased healthcare utilization, leading to an economic burden to society. The purpose of this study is to determine the burden of illness of hip fractures in elderly Dutch patients for specific time periods after surgery. Methods Patients with a hip fracture above the age of 65 were included in the study. In the 1-year period after surgery, patients were asked to complete a set of questionnaires pre-injury (retrospectively), and 1 week, 1 month, 3 months, 6 months and 12 months after surgery. The set of questionnaires included the Euroqol 5D (EQ-5D-3L), the iMTA Medical Consumption Questionnaire (iMCQ) and iMTA Productivity Cost Questionnaire (iPCQ). Health-related quality of life was calculated using Dutch tariffs. Costs were calculated using the methodology described in the Dutch costing manual. Results Approximately 20% of patients with a hip fracture died within 1 year. Health-related quality of life was significantly reduced compared to pre-injury values, and patients did not recover to their pre-injury values within 1 year. Total costs in the first year after injury were €27,573, of which 10% were due to costs of the procedure (€2706). Total follow-up costs (€24,876) were predominantly consisting of healthcare costs. Monthly costs decreased over time.Conclusions Hip fractures lead to a burden to patients, resulting from mortality and health-related quality of life reductions, and to society, due to (healthcare) costs. The results of this study can be used in future economic evaluations.

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Prevalence, recovery patterns and predictors of quality of life and costs after non-fatal injury: the Brabant Injury Outcome Surveillance (BIOS) study

Abstract: NCT02508675.

Cited by 40 publications

References 86 publications

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

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

Predicting health status in the first year after trauma

Burden of illness of hip fractures in elderly Dutch patients

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