Division of Medical Oncology and Hematology, Princess Margaret Cancer Centre, Toronto, Ontario, Canada.
Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada.
Cancer. 2017 Oct 1;123(19):3772-3780. doi: 10.1002/cncr.30804. Epub 2017 Jul 5.
Setting realistic targets for performance is a consistent challenge in quality improvement. In the current study, the authors used administrative data to define achievable targets for a panel of 15 previously developed quality indicators (QIs) focusing on systemic therapy in patients with early-stage breast cancer.
Deterministically linked administrative databases were used to identify patients with TNM stage I to stage III breast cancer who were diagnosed between 2006 and 2010 in Ontario, Canada. For each individual indicator, data-driven empirical benchmarks were calculated using the pared-mean benchmark approach. Variation in institution-level performance for each indicator was examined through the construction of funnel plots.
A total of 28,303 patients with early-stage breast cancer were identified, 43% of whom received adjuvant chemotherapy. For the 9 QIs for which receiving the service or outcome was desirable (ie, consultation with a medical oncologist), the benchmark varied from 40.9% to 100%. For the 6 indicators for which not receiving the service or outcome was desirable (ie, incidence of febrile neutropenia), the benchmark varied from 0% to 49.0%. There was substantial variation noted with regard to the number of institutions meeting the target and the amount of interinstitution variation between the QIs. Top performing institutions varied by indicator, with no individual institution meeting the benchmark for all indicators. For the majority of indicators, institution size was not found to be correlated with performance.
Data-derived benchmarking can be used to facilitate quality improvement by identifying areas of both good as well as suboptimal performance while defining an achievable target for which to strive. Cancer 2017;123:3772-3780. © 2017 American Cancer Society.
为绩效设定现实目标是质量改进的一个持续挑战。在本研究中，作者使用行政数据为一组 15 个先前开发的质量指标（QIs）定义可实现的目标，这些指标集中在早期乳腺癌患者的系统治疗上。
使用确定性链接的行政数据库来识别在加拿大安大略省诊断为 I 期至 III 期乳腺癌的 TNM 分期患者，诊断时间为 2006 年至 2010 年。对于每个个体指标，使用平均配对基准方法计算数据驱动的经验基准。通过构建漏斗图检查机构水平绩效的变化。
共确定了 28303 名早期乳腺癌患者，其中 43%接受了辅助化疗。对于 9 个希望获得服务或结果的 QIs（即与肿瘤内科医生的咨询），基准从 40.9%到 100%不等。对于 6 个不希望获得服务或结果的指标（即发热性中性粒细胞减少症的发生率），基准从 0%到 49.0%不等。在达到目标的机构数量和 QIs 之间的机构间变异量方面，注意到了大量的差异。绩效最高的机构因指标而异，没有一个机构达到所有指标的基准。对于大多数指标，机构规模与绩效之间没有发现相关性。
数据衍生的基准可以通过识别表现良好和表现不佳的领域，并定义一个可实现的目标来促进质量改进。癌症 2017；123：3772-3780。©2017 美国癌症协会。
