Model-Based Monitoring of Patient Response to Staged Thyroidectomy

The goal of this study is to develop a model-based control chart for monitoring patient behavior in a staged thyroidectomy considering risk factors and clinical prescription. prospectively collected data are gathered from the thyroid surgery unit of a hospital located in Tehran, Iran for 80 staged thyroidectomy patients discharged from 2009 to 2013. A risk-adjusted state-space model is developed based on the staged thyroidectomy. Variables to be included in the model are determined as a part of the model building process. Performance criteria, clinical prescription and patient risk factors are three variable components for the model. The appropriate risk factors are directly involved in the model and no scoring system is used for the model construction. Model identification is performed in two steps; model order selection and parameter estimation. In the first step, Hankel singular value decomposition (HSVD) is used for detecting the model order and in the second step, unknown parameters are estimated by the prediction error minimization (PEM) method. For monitoring patient responses, a group individual (GI) control chart is introduced and applied to a real-world problem. Results indicate that the suggested control chart can monitor the staged thyroidectomy patient’s behavior with an acceptable accuracy. Also, computer-aided diagnosis (CAD) systems can be developed based on the proposed identification and monitoring method.