Hoefsmit Paulien C, Jansen Evert K, Does Ronald J M M, Zandbergen H Reinier
Department of Cardiothoracic Surgery, Amsterdam University Medical Centre, 1081HV Amsterdam, The Netherlands.
Department of Business Analytics, Amsterdam Business School, University of Amsterdam, 1081TV Amsterdam, The Netherlands.
Healthcare (Basel). 2023 May 14;11(10):1419. doi: 10.3390/healthcare11101419.
The translation of a large quantity of data into valuable insights for daily clinical practice is underexplored. A considerable amount of information is overwhelming, making it difficult to distill and assess quality and processes at the hospital level. This study contributes to this necessary translation by developing a Quality Process Index that summarizes clinical data to measure quality and processes.
The Quality Process Index was constructed to enable retrospective analyses of quality and process evolution from 2011 to 2021 for various surgery types in the Amsterdam Cardiosurgical Database (n = 5497). It is presented alongside mortality rates, which are the golden standard for quality measurement. The two outcome variables are compared as quality and process measurement options.
Results showed that the mean Quality Process Index appeared rather stable, even though analysis of variance found that the mean Quality Process Index differed significantly over the years ( < 0.001). The 30-day and 120-day mortality rates appeared to fluctuate more, but interestingly, we failed to reject the null hypothesis of equal means. The Quality Process Index and mortality rates were statistically negatively correlated, and the extent of correlation was more pronounced with the 120-day mortality rate, as computed using the Pearson correlation coefficient r (30-day rQPI,30 = -0.07, < 0.001 and 120-day mortality rates rQPI,120 = -0.12, < 0.001).
The Quality Process Index seeks to address the need to translate data for quality and process improvement in healthcare. While mortality remains the most impactful outcome measure, the Quality Process Index provides a more stable and comprehensive measurement of quality and process improvement or deterioration in healthcare. Therefore, the Quality Process Index as a quantification reinforces the understanding of the definition of quality and process improvement.
大量数据转化为日常临床实践中有价值的见解这一过程尚未得到充分探索。大量信息令人应接不暇,难以在医院层面提炼并评估质量和流程。本研究通过开发一个质量流程指数来推动这一必要的转化,该指数汇总临床数据以衡量质量和流程。
构建质量流程指数,以便对阿姆斯特丹心脏外科数据库(n = 5497)中2011年至2021年各种手术类型的质量和流程演变进行回顾性分析。它与死亡率一同呈现,死亡率是质量衡量的金标准。将这两个结果变量作为质量和流程测量选项进行比较。
结果显示,尽管方差分析发现多年来平均质量流程指数存在显著差异(< 0.001),但平均质量流程指数似乎相当稳定。30天和120天死亡率的波动似乎更大,但有趣的是,我们未能拒绝均值相等的原假设。质量流程指数与死亡率在统计学上呈负相关,使用皮尔逊相关系数r计算得出,与120天死亡率的相关程度更为明显(30天rQPI,30 = -0.07,< 0.001;120天死亡率rQPI,120 = -0.12,< 0.001)。
质量流程指数旨在满足将数据转化以改善医疗保健质量和流程的需求。虽然死亡率仍然是最具影响力的结果指标,但质量流程指数为医疗保健质量和流程的改善或恶化提供了更稳定、更全面的衡量。因此,质量流程指数作为一种量化方法,强化了对质量和流程改善定义的理解。