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Background: Studies examining the impact of injury on health-related quality of life (HRQL) over time are necessary to understand the short-and long-Term consequences of injury for population health. The aim of this systematic review was to provide an evidence update on studies that have measured HRQL over time in general injury populations using a generic (general) health state measure. Methods: Studies conducted between 2010 and 2018 that assessed HRQL at more than one time point among general injury populations were eligible for inclusion. Two reviewers independently extracted information from each study on design, HRQL measure used, method of HRQL measure administration, timing of assessment(s), predictive variables, ability to detect change, and findings. Quality appraisals of each study were also completed by two reviewers using items from the RTI Item Bank on Risk of Bias and Precision of Observational Studies and the Guidelines for the Conduction of Follow-up Studies Measuring Injury-Related Disability. Results: Twenty-nine studies (44 articles) that met the inclusion criteria were identified. HRQL was measured using 14 different generic measures; the SF-36, SF-12, and EQ-5D were used most frequently. A varying number of follow-up assessments were undertaken, ranging from one to five. Follow-up often occurred 12 months post-injury. Fewer studies (n = 11) examined outcomes two or more years post-injury, and only one to 10 years post-injury. While most studies documented improvements in HRQL over time since the injury event, study populations had not returned to pre-injury status or reached general population norm HRQL values at post-injury follow-ups. Conclusions: Since 2010 there has been a substantial increase in the number of studies evaluating the HRQL of general injury populations. However, significant variability in study design continues to impede quantification of the impact of injury on population health over time. Variation between studies is partic

Purpose: This study investigated the psychometric yield of extension of the EQ-5D-5L with a cognitive domain (EQ-5D+C) in a mixed cohort of trauma patients with repeated data. Methods: A stratified sample of patients that presented at the emergency department filled out a follow-up survey 6 and 12 months after trauma. The surveys included the EQ-5D-5L+C, EQ-VAS, and the impact of events scale-revised (IES-R), a validated post-traumatic stress disorder (PTSD) self-assessment scale. Generally, results of the EQ-5D and EQ-5D+C were compared. Psychometrics included the following: distributional features (ceiling/floor effects), discriminatory performance, convergent validity with the EQ-VAS as reference, and responsiveness to change. Psychometric properties were compared between predefined subgroups based on conditions with cognitive impact (Traumatic Brain Injury (TBI)/PTSD). Results: In total, 1799 trauma patients responded 6 and 12 months after trauma, including 107 respondents with PTSD, and 273 with TBI. Six months post-trauma, ceiling of the EQ-5D (26.3%) was reduced with 2.2% with the additional cognitive domain. Using EQ-VAS as reference, convergent validity increased slightly with the addition of the cognitive domain: correlation increasing from 0.651 to 0.664. Cognitive level was found to slightly improve over time in TBI (delta: 0.04) and PTSD patients (delta: 0.05), while (almost) no change was found in patients without TBI and PTSD. Conclusion: Adding a cognitive domain to the EQ-5D-5L slightly improved measurement properties and better captured change in health status for trauma patients with TBI and PTSD. Inclusion of the cognitive domain in the EQ-5D-5L when measuring in populations with cognitive problems should be considered.

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.

BACKGROUND: Well-advised priority setting in prevention and treatment of injuries relies on detailed insight into costs of injury. This study aimed to provide a detailed overview of medical and productivity costs due to injury up to two years post-injury and compare these costs across subgroups for injury severity and age. METHODS: A prospective longitudinal cohort study followed all adult (≥18 years) injury patients admitted to a hospital in Noord-Brabant, the Netherlands. Patients filled out questionnaires 1 week, 1, 3, 6, 12 and 24 months after trauma, including items on health care consumption from the medical consumption questionnaire (iMCQ) and productivity loss from the productivity cost questionnaire (PCQ). Furthermore, injury severity was defined by Injury Severity Score (ISS). Data on diagnostics was retrieved from hospital registries. We calculated medical costs, consisting of in-hospital costs and post-hospital medical costs, and productivity costs due to injury up to two years post-injury. RESULTS: Approximately 50% (N = 4883) of registered patients provided informed consent, and 3785 filled out at least one questionnaire. In total, the average costs per patient were €12,190. In-hospital costs, post-hospital medical costs and productivity costs contributed €4810, €5110 and €5830, respectively. Total costs per patient increased with injury severity, from €7030 in ISS1-3 to €23,750 in ISS16+ and were lowest for age category 18-24y (€7980), highest for age category 85 years and over (€15,580), and fluctuated over age groups in between. CONCLUSION: Both medical costs and productivity costs generally increased with injury severity. Furthermore, productivity costs were found to be a large component of total costs of injury in ISS1-8 and are therefore a potentially interesting area with regard to reducing costs.

Purpose: To evaluate the correspondence of directly reported and recalled health-related quality of life (HRQL) in a heterogeneous sample of trauma patients. Methods: Adult trauma patients who attended the Emergency Department and were admitted between 03/2016 and 11/2016 were invited to participate. Postal surveys were sent 1 week (T1), 3 months (T2), and 12 months (T3) post-trauma. The EQ-5D-3L and Visual Analogue Scale (EQ-VAS) were used to assess directly reported and recalled HRQL. Results: The EQ-5D was completed by 446 patients at T1, T2, and T3. Directly reported mean T1 EQ-5D summary score was 0.482, whereas recalled T1 EQ-5D summary score was 0.453 (p < 0.05) at T2 and 0.363 (p < 0.001) at T3. Directly reported mean T2 EQ-5D summary score was 0.737 and mean recalled T2 EQ-5D summary score was 0.713 (p < 0.05) at T3. Directly reported mean T1 EQ-VAS was 56.3, whereas mean recalled T1 EQ-VAS at T2 and T3 was 55.4 (p = 0.304) and 53.3 (p < 0.05), respectively. Directly reported mean T2 EQ-VAS was 72.5 and recalled T2 EQ-VAS at T3 was 68.0 (p < 0.001). The correspondence between all directly reported and recalled HRQL (both EQ-5D summary and EQ-VAS) was fair (ICC = 0.518–0.598). Lowest correspondence was seen in patients with major trauma (injury severity score ≥ 16) and in patients with middle-level education. Conclusions: Recalled HRQL measured by the EQ-5D-3L and EQ-VAS was systematically lower compared to the directly reported HRQL. Patient characteristics, injury severity, subjectivity of the dimension, and time interval appear to influence correspondence between directly reported and recalled HRQL.