Monitoring, Control, and Adjustment of Non-Homogeneous Healthcare and Patient Data

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This research project is to develop new statistical process control (SPC) and bounded feedback adjustment (BFA) methods for healthcare adverse event and patient physiologic data that exhibit non-homogeneity or autocorrelation. Examples include surgery complications where each patient has a different survival likelihood and diabetic glucose levels that are desirable to control to minimize deviations from a target value. The risk-adjusted research will include new Shewhart, EWMA, and Cusum methods based on a mixed-risk model for non-identical dichotomous events. Numeric code will be developed to compute exact run length properties and investigate the effect of possible approximations. The feedback control research will integrate SPC with deadband adjustment charts (as opposed to continual adjustment), an area with important healthcare applications that remains relatively unexplored. This will include determining statistical properties of the bounded adjustments and evaluating the performance of parametric and non-parametric approaches to integrating BFA and SPC. Cost models will be developed for these integrated methods and used to determine their optimal simultaneous design, as well as the consequence of sub-optimal designs and robustness to model misspecification. Developed methods will also be validated empirically working with three academic hospitals.Broader impacts of this research include improved healthcare process safety, better control of patients' health status, and significant reduction in associated costs. The developed methods will provide greater ability to detect important changes by accurately accounting for the natural statistical behavior inherent in many healthcare processes. Important medical adverse events include medication errors, surgical site infections, ventilator-associated pneumonia, and wrong-site surgery, together estimated to result in 770,000 to 2 million patient injuries, 45,000 to 98,000 deaths, and $8.8 billion annually nationwide. Important feedback control applications include oral anticoagulant self-dosing, hormone self-regulation, and ICU patient blood counts and oxygen saturation levels, where continuous control is not practical and competing costs of adjustments, deviations from desired levels, and delayed change detection need to be balanced. The project's integrated methods will optimize the control of these processes and reduce the time and costs in detecting systemic changes. This research also will be benefit similar problems in other industries and will develop graduate students with a healthcare focus.