Introduction: Chemotherapy is complex. We hypothesized that a design thinking approach could redesign preparatory processes and reduce wait times. Methods: A multidisciplinary process mapping exercise was undertaken to understand the current processes, followed by proposing and testing solutions. Proposals were selected based on desirability and feasibility. These focused on starting the morning treatments on time and scheduling pre-made regimens in these slots. The primary outcome measure was the time from the appointment to starting treatment. Treatments in the post-intervention study group were compared against a historical control group. Results: The median time to start morning treatment decreased by 46%, from 83 min (with an interquartile range 50–127) in the control group to 45 min (with an interquartile range of 24–81 min) in the study group (p< 0.001). This translated into an overall improvement for the day, with the median time to start treatment decreasing from 77 min (with an interquartile range of 40–120 min) to 47 min (with an interquartile range of 20–79 min) (p< 0.001). Pre-makes increased by 258%, from 908 (28.5%) to 2340 (71.7%) regimens (p< 0.001). The number of patients starting treatment within an hour of their appointment increased from 1688 (32.8%) to 3355 (62.3%,p< 0.001). Conclusion: We have shown that a data-driven, design thinking approach can improve waiting times. This can be adapted to improve other processes in an empathetic, sustainable manner.
引言：化疗流程复杂。我们假设采用设计思维方法可重构化疗准备流程并缩短等待时间。方法：首先通过多学科流程梳理明确现行流程，随后提出并测试解决方案。方案筛选基于需求度与可行性原则，重点关注晨间治疗的准时启动及预配置方案在该时段的排程优化。主要结局指标为预约至开始治疗的时间间隔。干预后研究组的治疗数据与历史对照组进行比较。结果：晨间治疗启动中位时间从对照组的83分钟（四分位距50-127分钟）降至研究组的45分钟（四分位距24-81分钟），降幅达46%（p<0.001）。全天治疗启动中位时间相应从77分钟（四分位距40-120分钟）缩短至47分钟（四分位距20-79分钟）（p<0.001）。预配置方案数量从908例（28.5%）增至2340例（71.7%），提升258%（p<0.001）。预约后1小时内开始治疗的患者数从1688例（32.8%）增加至3355例（62.3%，p<0.001）。结论：本研究证实数据驱动的设计思维方法能有效改善化疗等待时间。该方法可通过共情、可持续的方式推广至其他医疗流程优化中。
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