Background: An independent medical examination is a unique healthcare assessment conducted by an expert health professional with the aim of providing impartial advice to key stakeholders in workers' compensation schemes regarding a worker's injury or illness. A range of dedicated guidelines provide for best practice at local and national levels, but concerns exist regarding the quality of these encounters for all involved.
Methods: A narrative review was conducted to explore quality principles underpinning practices and reporting of independent medical examinations. Quality was defined by dimensions outlined by the World Health Organization (effectiveness, safety, people-centredness, timeliness, equity, integration of care, efficiency). Academic (databases: Medline, CINAHL, Embase) and grey literature (advanced Google search) published in English was searched with no date limits. Results were synthesised according to the components of independent medical examinations (independent medical examiner approval and selection, independent medical examinations, reporting) and then mapped to quality dimensions.
Results: The quality dimensions of effectiveness, safety, person-centredness, timeliness, equity, and efficiency were partly addressed in existing independent medical examination practices, most commonly within the examination itself. However, there were prominent gaps in person-centredness and integration of care across all stages of the examination and reporting process. Opportunities for strengthening quality practices included: inviting community members with lived experience of workplace injury to serve on boards responsible for appointing independent medical examiners; explicitly encouraging questions and perspectives from injured works during examinations; holistic reporting that accurately captures injured workers' experiences; consultations with usual treating teams prior to report finalisation and submission; and providing verbal summaries and/or reports directly to injured workers.
Conclusion: Although some quality principles were evident in existing independent medical examination practices described in the literature, unlike the acute and community healthcare sectors, the notion of quality was not universally applied in this context. To promote evidence-based practice, foster positive cultural shifts, and enhance experiences of injured workers and independent medical examiners, formally embedding a comprehensive quality experience in independent medical examination programs is recommended.
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http://dx.doi.org/10.1016/j.injury.2024.111965 | DOI Listing |
Eur J Med Res
December 2024
Department of Neurosurgery, Neuromedicine Center, Beijing Shijitan Hospital, Capital Medical University, No. 10, Tieyi Road, Yangfangdian, Haidian District, Beijing, 100038, People's Republic of China.
Background: Full-endoscopic microvascular decompression (fE-MVD) is an emerging treatment option for trigeminal neuralgia (TN). However, the risk factors associated with postoperative recurrence of TN after fE-MVD procedure remain controversial. The aim of the present study was to summarize the surgical technique of fE-MVD for the treatment of TN and to develop a predictive model for recurrence at 1 year postoperatively based on independent risk factors.
View Article and Find Full Text PDFLangenbecks Arch Surg
December 2024
Department of Surgery, TUM Universitätsklinikum Klinikum Rechts der Isar Technische Universität München, Ismaninger Str. 22, 81675, Munich, Germany.
Objective: Splenectomy is regularly performed in total and distal pancreatectomy due to technical reasons, lymph node dissection and radicality of the operation. However, the spleen serves as an important organ for competent immune function, and its removal is associated with an increased incidence of cancer and a worse outcome in some cancer entities (Haematologica 99:392-398, 2014; Dis Colon Rectum 51:213-217, 2008; Dis Esophagus 21:334-339, 2008). The impact of splenectomy in pancreatic cancer is not fully resolved (J Am Coll Surg 188:516-521, 1999; J Surg Oncol 119:784-793, 2019).
View Article and Find Full Text PDFSkeletal Radiol
December 2024
Department of Orthopedic Surgery, Akita Hospital, 2-6-12 Takara, Chiryu City, Aichi, 472-0056, Japan.
Objective: To determine which parameters, including femur morphology, proximal femur bone mineral density, or patient characteristics, are associated with bisphosphonate-related atypical femur fractures (AFFs) and to investigate the relationships between AFF location and these parameters.
Materials And Methods: Sixteen females with a history of bisphosphonate use who presented with AFFs and 38 females without AFFs, even those with long-term bisphosphonate use of > 5 years, were compared. Patient characteristics; physique, gait ability, and history of pain and medication, were recorded.
Cancer Cell Int
December 2024
Department of Applied Chemistry, Graduate Institute of Biomedicine and Biomedical Technology, National Chi Nan University, Puli, Taiwan.
Introduction: Chronic alcohol consumption and tobacco usage are major risk factors for esophageal squamous cell carcinoma (ESCC). Excessive tobacco and alcohol consumption lead to oxidative stress and the generation of reactive carbonyl species (RCS) which induce DNA damage and cell apoptosis. This phenomenon contributes to cell damage and carcinogenesis in various organs including ESCC.
View Article and Find Full Text PDFClin Lymphoma Myeloma Leuk
November 2024
Department of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, TX.
Background: The sensitivity of reverse-transcription polymerase chain reaction (RT-PCR) is limited for diagnosis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Chest computed tomography (CT) is reported to have high sensitivity; however, given the limited availability of chest CT during a pandemic, the assessment of more readily available imaging, such as chest radiographs, augmented by artificial intelligence may substitute for the detection of the features of coronavirus disease 2019 (COVID-19) pneumonia.
Methods: We trained a deep convolutional neural network to detect SARS-CoV-2 pneumonia using publicly available chest radiography imaging data including 8,851 normal, 6,045 pneumonia, and 200 COVID-19 pneumonia radiographs.
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