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Titre : | Comorbidity and Insurance as Predictors of Disability After Traumatic Brain Injury (2014) |
Auteurs : | Elmar Gardizi ; Robin A. Hanks ; Scott R. Millis |
Type de document : | Article |
Dans : | Archives of Physical Medicine and Rehabilitation (2014/12, 2014) |
Article en page(s) : | p. 2396-2401 |
Langues: | Anglais |
Descripteurs : |
HE Vinci Assurance ; Comorbidité ; Rééducation et réadaptation |
Mots-clés: | Comorbidity ; Insurance ; Brain Injuries ; Traumatic ; Lésions traumatiques de l'encéphale |
Résumé : |
Objective To examine the unique contribution of self-reported medical comorbidity and insurance type on disability after traumatic brain injury (TBI). Design Inception cohort design at 1-year follow up. Setting A university affiliated rehabilitation hospital. Participants Adults with mild-complicated to severe TBI (N=70). Intervention Not applicable. Main Outcome Measures Self-reported medical comorbidities were measured using the Modified Cumulative Illness Rating Scale, while insurance type was classified as commercial or government-funded; disability was measured using the Disability Rating Scale. Results Two models were run using multiple linear regression, and the best-fitting model was selected on the basis of Bayesian information criterion. The full model, which included self-reported medical comorbidity and insurance type, was significantly better fitting than the reduced model. Participants with a longer duration of posttraumatic amnesia, more self-reported medical comorbidities, and government insurance were more likely to have higher levels of disability. Meanwhile, individual organ systems were not predictive of disability. Conclusions The cumulative effect of self-reported medical comorbidities and type of insurance coverage predict disability above and beyond well-known prognostic variables. Early assessment of medical complications and improving services provided by government-funded insurance may enhance quality of life and reduce long-term health care costs. |
Disponible en ligne : | Oui |
En ligne : | https://login.ezproxy.vinci.be/login?url=https://www.sciencedirect.com/science/article/pii/S0003999314004353 |