Decision Trees and Their Development: Use of Data to Determine the Quality of Care

Decision Trees and Their Development: Use of Data to Determine the Quality of Care

Patricia Cerrito (University of Louisville, USA) and John Cerrito (Kroger Pharmacy, USA)
DOI: 10.4018/978-1-61520-905-7.ch013
OnDemand PDF Download:
$37.50

Abstract

Decision trees are developed to support physicians who must make treatment decisions. Risk estimates are used to find the optimal treatment pathway for a group of patients. Unfortunately, decision trees often are developed in the absence of empirical evidence concerning risk. In particular, long-term risk is almost always unknown. Instead, physician panels are convened, or physician groups are surveyed to give estimates of risk. However, these outcomes databases discussed in this text can be used to investigate risk, and the relationship of treatment to outcomes. This relationship can be translated into percentages of risk, and that risk used to develop decision trees. Risk versus benefit can be used to find optimal treatment. However, patient benefit is subjective. Pain, especially, is very subjective. Is a patient better off to have surgery to relieve pain, or to just take pain medication continuously? There are attempts to define patient benefit as a function of the patient’s utility. To save costs, should treatment be denied if it fails to increase a patient’s utility? Who should decide a patient’s utility? Often, the patient has little input into the definition of utility that is often used to deny treatment.
Chapter Preview
Top

Introduction

Decision trees are developed to support physicians who must make treatment decisions. Risk estimates are used to find the optimal treatment pathway for a group of patients. Unfortunately, decision trees often are developed in the absence of empirical evidence concerning risk. In particular, long-term risk is almost always unknown. Instead, physician panels are convened, or physician groups are surveyed to give estimates of risk.

However, these outcomes databases discussed in this text can be used to investigate risk, and the relationship of treatment to outcomes. This relationship can be translated into percentages of risk, and that risk used to develop decision trees. Risk versus benefit can be used to find optimal treatment. However, patient benefit is subjective. Pain, especially, is very subjective. Is a patient better off to have surgery to relieve pain, or to just take pain medication continuously? There are attempts to define patient benefit as a function of the patient’s utility. To save costs, should treatment be denied if it fails to increase a patient’s utility? Who should decide a patient’s utility? Often, the patient has little input into the definition of utility that is often used to deny treatment.

Complete Chapter List

Search this Book:
Reset