GOALI: Statistical Quality Control Methods for Health Systems Problems

Northeastern University, Boston MA

Investigators

Abstract

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.