School of Computing, Informatics and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA.
Department of Industrial and Systems Engineering, University of Wisconsin-Madison, 1513 University Ave, Madison, WI, 53706, USA.
J Med Syst. 2017 Dec 1;42(1):16. doi: 10.1007/s10916-017-0873-6.
The process of lung cancer care from initial lesion detection to treatment is complex, involving multiple steps, each introducing the potential for substantial delays. Identifying the steps with the greatest delays enables a focused effort to improve the timeliness of care-delivery, without sacrificing quality. We retrospectively reviewed clinical events from initial detection, through histologic diagnosis, radiologic and invasive staging, and medical clearance, to surgery for all patients who had an attempted resection of a suspected lung cancer in a community healthcare system. We used a computer process modeling approach to evaluate delays in care delivery, in order to identify potential 'bottlenecks' in waiting time, the reduction of which could produce greater care efficiency. We also conducted 'what-if' analyses to predict the relative impact of simulated changes in the care delivery process to determine the most efficient pathways to surgery. The waiting time between radiologic lesion detection and diagnostic biopsy, and the waiting time from radiologic staging to surgery were the two most critical bottlenecks impeding efficient care delivery (more than 3 times larger compared to reducing other waiting times). Additionally, instituting surgical consultation prior to cardiac consultation for medical clearance and decreasing the waiting time between CT scans and diagnostic biopsies, were potentially the most impactful measures to reduce care delays before surgery. Rigorous computer simulation modeling, using clinical data, can provide useful information to identify areas for improving the efficiency of care delivery by process engineering, for patients who receive surgery for lung cancer.
从初始病变检测到治疗，肺癌护理的过程非常复杂，涉及多个步骤，每个步骤都有可能导致大量的延迟。确定延迟最大的步骤可以使我们集中精力提高护理及时性，而不影响质量。我们回顾性地分析了在社区医疗系统中，所有疑似肺癌患者接受尝试性切除术的临床事件，包括从初始检测、组织学诊断、影像学和侵袭性分期、医学清除到手术的各个阶段。我们使用计算机过程建模方法来评估护理延迟，以确定等待时间中的潜在“瓶颈”，减少这些瓶颈可以提高护理效率。我们还进行了“如果......会怎样”的分析，以预测护理流程模拟变化的相对影响，从而确定最有效的手术途径。影像学病变检测和诊断性活检之间的等待时间，以及影像学分期和手术之间的等待时间是阻碍高效护理的两个最关键的瓶颈（比减少其他等待时间的影响大 3 倍以上）。此外，在进行心脏咨询之前进行手术咨询，以进行医学清除，并减少 CT 扫描和诊断性活检之间的等待时间，这些措施可能是减少手术前护理延迟最有影响力的措施。使用临床数据进行严格的计算机模拟建模，可以为通过流程工程提高接受肺癌手术的患者的护理效率提供有用的信息。
