GOALI: Statistical Quality Control Methods for Health Systems Problems

该奖项的研究目标是为医疗保健不良事件开发新的统计质量控制，例如药物和实验室错误，医院获得性感染以及其他可预防的问题和错误。三种新的方法将是基于逆二项抽样和不同分布的混合物的控制罕见事件，将逻辑回归和其他方法纳入一般的风险质量控制框架，并将这些控制方法同时结合联合收割机。将开发数值程序，并用于调查这些方法的统计性能和操作特性，并将开发一种优化搜索算法，以确定方法的最佳经济和经济设计。开发的方法还将使用两家学术医院的大型数据库药物事件、针刺伤和耐甲氧西林金黄色葡萄球菌进行经验验证。如果成功，这项研究的好处将导致改进监测方法，减少可预防的不良医疗事件的发生，估计将导致200万患者受伤，45，000至98，000人死亡，全国每年花费88亿美元。所开发的方法将提供更大的统计功效来检测罕见不良事件发生率的变化，并将准确解释聚集同质患者。确定每种方法的操作特性和最佳设计将有助于减少检测问题的时间和相关成本。结果将用于比较拟议的和传统的医院监测方法，确定条件下，每种方法比别人表现更好，并制定设计和选择指南。该研究也将有益于高产量制造业和其他行业的类似质量控制问题。

The research objectives of this Grant Opportunities for Academic Liaison with Industry (GOALI) award are to develop new statistical quality control for healthcare adverse events, such as medication and laboratory errors, hospital-acquired infections, and other preventable problems and mistakes. Three new methods will be control rare events based on inverse binomial sampling and mixtures of non-identical distributions, to incorporate logistic regression and other approaches into a general risk quality control framework, and to combine these control methods simultaneously. Numeric programs will be developed and used to investigate the statistical performance and operating characteristics of these methods, and an optimization search algorithm will be developed implemented to determine the optimal economic and statistical-economic designs of methods. Developed methods also will be validated empirically using large database drug events, needle stick injuries, and methicillin-resistant Staphylococcus aurous at two academic hospitals.If successful, the benefits of this research will lead to improved surveillance methods and reduce the occurrence of preventable adverse healthcare events, estimated to result to 2 million patient injuries, 45,000 to 98,000 deaths, and $8.8 billion in costs annual nationwide. The developed methods will provide greater statistical power to detect changes in the occurrence rates of infrequent adverse events and will accurately account for aggregation homogeneous patients. Determining the operating characteristics and optimal design of each method will help reduce the time to detect problems and the associated costs. Results will be used to compare proposed and traditional hospital surveillance methods, identify conditions under which each method performs better than others, and develop design and selection guidelines. The proposed research also will benefit similar quality control problems in high yield manufacturing and other industries.