Tako Antuela A, Kotiadis Kathy, Vasilakis Christos, Miras Alexander, le Roux Carel W
School of Business and Economics, Loughborough University, , Loughborough, UK.
BMJ Qual Saf. 2014 May;23(5):373-81. doi: 10.1136/bmjqs-2013-002107. Epub 2013 Sep 19.
Obesity care services are often faced with the need to adapt their resources to rising levels of demand. The main focus of this study was to help prioritise planned investments in new capacity allowing the service to improve patient experience and meet future anticipated demand.
We developed computer models of patient flows in an obesity service in an Academic Health Science Centre that provides lifestyle, pharmacotherapy and surgery treatment options for the UK's National Health Service. Using these models we experiment with different scenarios to investigate the likely impact of alternative resource configurations on patient waiting times.
Simulation results show that the timing and combination of adding extra resources (eg, surgeons and physicians) to the service are important. For example, increasing the capacity of the pharmacotherapy clinics equivalent to adding one physician reduced the relevant waiting list size and waiting times, but it then led to increased waiting times for surgical patients. Better service levels were achieved when the service operates with the resource capacity of two physicians and three surgeons. The results obtained from this study had an impact on the planning and organisation of the obesity service.
Resource configuration combined with demand management (reduction in referral rates) along the care service can help improve patient waiting time targets for obesity services, such as the 18 week target of UK's National Health Service. The use of simulation models can help stakeholders understand the interconnectedness of the multiple microsystems (eg, clinics) comprising a complex clinical service for the same patient population, therefore, making stakeholders aware of the likely impact of resourcing decisions on the different microsystems.
肥胖症护理服务常常需要使其资源适应不断增长的需求水平。本研究的主要重点是帮助确定对新服务能力的计划投资的优先级，以使服务能够改善患者体验并满足未来预期需求。
我们开发了一个学术健康科学中心肥胖症服务的患者流计算机模型，该中心为英国国家医疗服务体系提供生活方式、药物治疗和手术治疗选择。利用这些模型，我们对不同场景进行试验，以研究替代资源配置对患者等待时间的可能影响。
模拟结果表明，向该服务增加额外资源（如外科医生和内科医生）的时间和组合很重要。例如，将药物治疗诊所的能力提高相当于增加一名内科医生，这减少了相关等候名单的规模和等待时间，但随后导致手术患者的等待时间增加。当该服务以两名内科医生和三名外科医生的资源能力运作时，实现了更好的服务水平。本研究获得的结果对肥胖症服务的规划和组织产生了影响。
资源配置与护理服务过程中的需求管理（降低转诊率）相结合，有助于提高肥胖症服务的患者等待时间目标，如英国国家医疗服务体系的18周目标。使用模拟模型可以帮助利益相关者理解构成针对同一患者群体的复杂临床服务的多个微观系统（如诊所）之间的相互联系，因此，使利益相关者意识到资源配置决策对不同微观系统可能产生的影响。
