Threshold Decision-making in Clinical Medicine

With Practical Application to Hematology and Oncology
2023
ISBN: 978-3-031-37992-5
Verlag: Springer International Publishing

Buch, Englisch, Band 189, 138 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 448 g

Reihe: Cancer Treatment and Research

This book aims to provide threshold models to help physicians to make optimal diagnostic, therapeutic and predictive decisions. Readers will not only find theoretical information but also practical examples illustrating how these decisions should be made.

Poor decision-making is considered a leading cause of death in contemporary medicine. Decisions, however, have to be made - at a given threshold of risk and unfortunately physicians are not trained on how to make decisions. This book provides help to all those who want to improve their decision-making for a better patient outcome. With its examples from hematology and oncology the book will not only benefit haematologists and oncologists but physicians from all disciplines, hence the threshold model is applicable to all fields in medicine. This book will be useful to experienced physicians as well as trainees alike.

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

Hozo, Iztok

Djulbegovic, Benjamin

Fachgebiete

• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Klinische und Innere Medizin Onkologie, Krebsforschung
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Klinische und Innere Medizin Hämatologie, Transfusionsmedizin

Inhaltsverzeichnis

Evidence and decision-making.- Evidence-based summary measures.- Making decisions when diagnosis is certain: Under expected utility theory.- Under regret theory.- Under dual processing theory.- Hybrid model.- Making decisions when diagnosis is uncertain: Under expected utility theory.- Under regret theory.- Under dual processing theory.- Hybrid model.- Using predictive modelling to tailor therapy.- Under expected utility theory.- Under regret theory.- Heuristic decision-making: fast-and-frugal tree.- Conclusions: future of decision-making in oncology and hematology.- Artificial intelligence vs standard decision theories.

Über Autor(innen)

Benjamin Djulbegovic is a Professor at City of Hope. His main academic and research interest lies in attempts to measure and optimize clinical research and practice of medicine by understanding both, the nature of medical evidence and decision-making. His work aims to integrate methods and techniques across evidence-based medicine (EBM), predictive analytics, health outcome research, and decision-sciences with the goal of improvement of health care. Dr. Djulbegovic has systematically applied science of EBM and decision analysis to the entire fields of hematology and oncology that resulted in two books; the book on “Reasoning and decision-making in hematology” was listed one of the best books by J Natl Cancer Inst and the book “Decision Making in Oncology. Evidence-based management” was assessed as “one of the first and best attempts to apply an evidence-based approach to the practice of medical oncology”. As of September 2020, he has published over 350 papers inpeer-reviewed journals, 195 abstracts and numerous book chapters. He also received numerous awards for his work, which has also been published in major scientific and medical journals including Nature, Lancet, JAMA, New England Journal of Medicine, etc. He has also widely taught on these subjects. He was also selected in the Newsweek’s list of Top Cancer Doctors and since 2011 continuously selected in 1% of top US doctors by the US News & World Report in the field of hematology. His current h-index is 69; in 2018 he is included in the list of highly cited researchers which “recognizes world-class researchers selected for their exceptional research performance, demonstrated by production of multiple highly cited papers that rank in the top 1% by citations for field and year in Web of Science.”
Iztok Hozo is a Professor at Indiana University Northwest. After completing his doctoral thesis in applied mathematics at University of Michigan, his main research interests became applications of mathematical modelling and decision theory in Medical applications. Mainly collaborating with Dr. Djulbegovic, he published 75 articles in peer-reviewed scientific journals.

In addition to receiving several Indiana University awards for excellence in research, Dr. Hozo won prestigious teaching awards in recognition of his expertise in the classroom and curriculum development.
He is a mathematician capable of translating real scientific and medical problems into mathematical language. His mathematical acumen has enabled him to tackle the vast array of diverse medical problems. Over the years he has made contribution to statistical analysis of clinical data and improvement in techniques of meta-analysis, tackled the issues of diagnostic tests using information theory approach, recast the issue of clinical trials from game theory point of view, developed new methods for decision-making, including a novel method based on mathematical modelling of regret, and helped develop the first mathematical model of decision-making that is based on dual processing theory and developed a new theory called acceptable regret, which could explain many phenomena in the diagnostic and treatment decisions in medicine.
According to Google Scholar, his current h-index is 25. One of his published articles has over 4200 citations (written jointly with Dr. Djulbegovic and Mrs. Pudar-Hozo).