School of Mathematical Sciences, Faculty of Science, Queensland University of Technology, 2 George St, Brisbane, QLD, 4000, Australia.
Centre for Data Science, Queensland University of Technology, 2 George St, Brisbane, QLD, 4000, Australia.
Health Care Manag Sci. 2023 Sep;26(3):533-557. doi: 10.1007/s10729-023-09648-1. Epub 2023 Jun 28.
Prioritising elective surgery patients under the Australian three-category system is inherently subjective due to variability in clinician decision making and the potential for extraneous factors to influence category assignment. As a result, waiting time inequities can exist which may lead to adverse health outcomes and increased morbidity, especially for patients deemed to be low priority. This study investigated the use of a dynamic priority scoring (DPS) system to rank elective surgery patients more equitably, based on a combination of waiting time and clinical factors. Such a system enables patients to progress on the waiting list in a more objective and transparent manner, at a rate relative to their clinical need. Simulation results comparing the two systems indicate that the DPS system has potential to assist in managing waiting lists by standardising waiting times relative to urgency category, in addition to improving waiting time consistency for patients of similar clinical need. In clinical practice, this system is likely to reduce subjectivity, increase transparency, and improve overall efficiency of waiting list management by providing an objective metric to prioritise patients. Such a system is also likely to increase public trust and confidence in the systems used to manage waiting lists.
由于临床医生决策的变异性和额外因素影响类别分配的可能性，澳大利亚的三类系统优先考虑择期手术患者具有内在的主观性。因此，可能存在等待时间不公平的情况，这可能导致不良的健康结果和发病率增加，特别是对于被认为优先级较低的患者。本研究调查了使用动态优先级评分（DPS）系统根据等待时间和临床因素更公平地对择期手术患者进行排名。这样的系统使患者能够以更客观和透明的方式根据他们的临床需求相对速度在候补名单上取得进展。比较这两个系统的模拟结果表明，DPS 系统有可能通过使等待时间与紧急程度相对标准化来帮助管理候补名单，同时还可以提高具有相似临床需求的患者的等待时间一致性。在临床实践中，该系统通过提供优先考虑患者的客观指标，可能会减少主观性、提高透明度，并提高候补名单管理的整体效率。这样的系统还有可能增加公众对用于管理候补名单的系统的信任和信心。
