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Regression-Based Methods of Phase-I Monitoring Surgical Performance Using Risk-Adjusted Charts: An Overview

Regression-Based Methods of Phase-I Monitoring Surgical Performance Using Risk-Adjusted Charts: An Overview
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Author(s): Negin Asadayyoobi (Sharif University of Technology, Iran)
Copyright: 2017
Pages: 13
Source title: Handbook of Research on Data Science for Effective Healthcare Practice and Administration
Source Author(s)/Editor(s): Elham Akhond Zadeh Noughabi (University of Calgary, Canada), Bijan Raahemi (University of Ottawa, Canada), Amir Albadvi (Tarbiat Modares University, Iran)and Behrouz H. Far (University of Calgary, Canada)
DOI: 10.4018/978-1-5225-2515-8.ch010

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Abstract

Monitoring medical processes gained importance and researchers attempted to reduce death rates by quick detection mortality rate of surgical outcomes in recent years. The patient time until death (survival time) depends on risk factor of each patient, which reflects the patients' health condition prior to surgery. Ignoring differences in risk factors among specific patients, risk adjusted control charts could be considered as a corrective tool to minimize false alarms related to inhomogeneity in patients' health condition. A number of risk adjusted charting procedures have been developed on both phase I & II monitoring of aforementioned outcomes. This chapter will review both models and focus on phase-I risk-adjustment models in medical setting with a particular emphasis on monitoring for surgical context and describe each method's unique properties.

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