Experience with a urological waiting list initiative is presented, wherein a list of 231 non-urgent cases was cleared over a 5 month period by a single operator. Some patients had waited 10 years for surgery. Following a postal request, the waiting list was validated; 31.2% of patients wished to be removed. The remaining 68.8% desired surgery and consisted of 51 requiring minor surgical procedures and 108 who needed more major surgery mostly for the relief of bladder outflow obstruction. Minor cases received dates for surgery; however, only 68.2% of this group attended despite being given more than one date for admission. Major cases were reviewed in a pre-admission clinic. General and urological condition was assessed, improved where necessary and surgery booked or delayed accordingly. A small number of patients did not attend or only attended to be reassured that surgery was not needed. Following clinical review, 18.5% of this group did not require operation. The long urological waiting list is a unique situation where patients listed may no longer require surgery. Reviewing these patients not only reduces numbers but also markedly increases percentage attendance for surgery.
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http://dx.doi.org/10.1177/014107689408700308 | DOI Listing |
Sci Rep
January 2025
Department of Anesthesiology, Changhua Christian Hospital, Changhua, 50050, Taiwan.
In the modern healthcare system, the rational allocation of emergency department (ED) resources is crucial for enhancing emergency response efficiency, ensuring patient safety, and improving the quality of medical services. This paper focuses on the issue of ED resource allocation and designs a priority sorting system for ED patients. The system classifies patients into two queues: urgent and routine.
View Article and Find Full Text PDFClin Gastroenterol Hepatol
January 2025
Department of Computer Science and Numerical Analysis, University of Córdoba, Córdoba, Spain. Campus Universitario de Rabanales, Albert Einstein Building. Ctra. N-IV, Km. 396. 14071, Córdoba, Spain; Instituto Maimónides de Investigación Biomédica de Córdoba (IMIBIC), Córdoba, Spain. Av. Menéndez Pidal, s/n, Poniente Sur, 14004 Córdoba, Spain.
Background & Aims: We aimed to develop and validate an artificial intelligence score (GEMA-AI) to predict liver transplant (LT) waiting list outcomes using the same input variables contained in existing models.
Methods: Cohort study including adult LT candidates enlisted in the United Kingdom (2010-2020) for model training and internal validation, and in Australia (1998-2020) for external validation. GEMA-AI combined international normalized ratio, bilirubin, sodium, and the Royal Free Glomerular Filtration Rate in an explainable Artificial Neural Network.
Front Public Health
January 2025
Transplant Immunology Unit, Geneva University Hospitals, Geneva, Switzerland.
Introduction: The Swiss allocation system for kidney transplantation has evolved over time to balance medical urgency, immunological compatibility, and waiting time. Since the introduction of the transplantation law in 2007, which imposed organ allocation on a national level, the algorithm has been optimized. Initially based on waiting time, HLA compatibility, and crossmatch performed by cell complement-dependent cytotoxicity techniques, the system moved in 2012 to a score including HLA compatibility, waiting time, anti-HLA antibodies detected by the Luminex technology, and a virtual crossmatch.
View Article and Find Full Text PDFBMC Health Serv Res
January 2025
Centre for the Business and Economics of Health (CBEH), The University of Queensland, St Lucia, Brisbane, QLD, 4072, Australia.
Background: The purpose of this qualitative study was to focus on review and repeat review outpatients and the structural role they play in exacerbating waitlists for Specialist Outpatient (SOP) services in Queensland. Waitlists, which record the number of patients waiting for an initial consultation (new appointment), are an indicator of a health system under strain. Waiting too long to access SOP can have a detrimental effect on people's health outcomes.
View Article and Find Full Text PDFMDM Policy Pract
January 2025
Centre for Health Economics, University of York, Heslington, York, UK.
Unlabelled: Reducing hospital waiting lists for elective procedures is a policy concern in the National Health Service (NHS) in England. Following growth in waiting lists after COVID-19, the NHS published an elective recovery plan that includes an aim to prioritize patients from deprived areas. We use a previously developed model to estimate the health and health inequality impact under hypothetical targeted versus universal policies to reduce waiting time.
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