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Patterns of computed tomography utilisation in injury management: latent classes approach using linked administrative data in Western Australia.
Ha, Ninh T; Harris, Mark; Bulsara, Max; Doust, Jenny; Kamarova, Sviatlana; McRobbie, Donald; O'Leary, Peter; Parizel, Paul M; Slavotinek, John; Wright, Cameron; Youens, David; Moorin, Rachael.
Afiliação
  • Ha NT; Health Economics and Data Analytics, Curtin School of Population Health, Faculty of Health Sciences, Curtin University, GPO Box U1987, Perth, WA, 6845, Australia. thi.ha@curtin.edu.au.
  • Harris M; School of Accounting, Economics and Finance, Faculty of Business and Law, Curtin University, Perth, Western Australia, Australia.
  • Bulsara M; Institute for Health Research, University of Notre Dame, Fremantle, WA, Australia.
  • Doust J; Centre for Health Services Research, School of Population and Global Health, The University of Western Australia, Crawley, Australia.
  • Kamarova S; Australian Women and Girls' Health Research Centre, School of Public Health, University of Queensland, Brisbane, Australia.
  • McRobbie D; Health Economics and Data Analytics, Curtin School of Population Health, Faculty of Health Sciences, Curtin University, GPO Box U1987, Perth, WA, 6845, Australia.
  • O'Leary P; School of Health Sciences, University of Sydney, Camperdown, New South Wales, Australia.
  • Parizel PM; Nepean Blue Mountains Local Health District, Kingswood, New South Wales, Australia.
  • Slavotinek J; School of Physical Sciences, University of Adelaide, Adelaide, Australia.
  • Wright C; Health Economics and Data Analytics, Curtin School of Population Health, Faculty of Health Sciences, Curtin University, GPO Box U1987, Perth, WA, 6845, Australia.
  • Youens D; Obstetrics and Gynaecology Medical School, Faculty of Health and Medical Sciences, The University of Western Australia, Perth, WA, Australia.
  • Moorin R; PathWest Laboratory Medicine, QE2 Medical Centre, Nedlands, WA, Australia.
Eur J Trauma Emerg Surg ; 49(6): 2413-2427, 2023 Dec.
Article em En | MEDLINE | ID: mdl-37318517
PURPOSE: Whilst computed tomography (CT) imaging has been a vital component of injury management, its increasing use has raised concern regarding ionising radiation exposure. This study aims to identify latent classes (underlying patterns) of CT use over a 3-year period following the incidence of injury and factors predicting the observed patterns. METHOD: A retrospective observational cohort study was conducted in 21,544 individuals aged 18 + years presenting to emergency departments (ED) of four tertiary public hospitals with new injury in Western Australia. Mixture modelling approach was used to identify latent classes of CT use over a 3-year period post injury. RESULTS: Amongst injured people with at least one CT scan, three latent classes of CT use were identified including a: temporarily high CT use (46.4%); consistently high CT use (2.6%); and low CT use class (51.1%). Being 65 + years or older, having 3 + comorbidities, history with 3 + hospitalisations and history of CT use before injury were associated with consistently high use of CT. Injury to the head, neck, thorax or abdomen, being admitted to hospital after the injury and arriving to ED by ambulance were predictors for the temporarily high use class. Living in areas of higher socio-economic disadvantage was a unique factor associated with the low CT use class. CONCLUSIONS: Instead of assuming a single pattern of CT use for all patients with injury, the advanced latent class modelling approach has provided more nuanced understanding of the underlying patterns of CT use that may be useful for developing targeted interventions.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Tomografia Computadorizada por Raios X / Traumatismos Craniocerebrais País/Região como assunto: Oceania Idioma: En Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Austrália

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Tomografia Computadorizada por Raios X / Traumatismos Craniocerebrais País/Região como assunto: Oceania Idioma: En Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Austrália