Despite the vast quantities of published artificial intelligence (AI) algorithms that target trauma and orthopaedic applications, very few progress to inform clinical practice. One key reason for this is the lack of a clear pathway from development to deployment. In order to assist with this process, we have developed the Clinical Practice Integration of Artificial Intelligence (CPI-AI) framework – a five-stage approach to the clinical practice adoption of AI in the setting of trauma and orthopaedics, based on the IDEAL principles ( Cite this article:
Due to widespread cancellations in elective orthopaedic procedures, the number of patients on waiting list for surgery is rising. We aim to determine and quantify if disparities exist between inpatient and day-case orthopaedic waiting list numbers; we also aim to determine if there is a ‘hidden burden’ that already exists due to reductions in elective secondary care referrals. Retrospective data were collected between 1 April 2020 and 31 December 2020 and compared with the same nine-month period the previous year. Data collected included surgeries performed (day-case vs inpatient), number of patients currently on the orthopaedic waiting list (day-case vs inpatient), and number of new patient referrals from primary care and therapy services.Aims
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