Decision Making with Prostate Cancer: A Multiple-Objective Model with Uncertainty

Simon, Jay R.

doi:10.1287/inte.1080.0406

Cited by 11 publications

(6 citation statements)

References 40 publications

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“…There are examples of OR techniques helping with patients' cancer treatment decisions (Simon, 2009;Suner, Çelikoglu, Dicle, & Sökmen, 2012;Utley, Paschalides, & Treasure, 2006). These studies are about various different cancer types and treatment options.…”

Section: Treatment Decisionsmentioning

confidence: 99%

“…They find that the judgements of individuals are consistent, and represent the results in decision tree format. Finally, Simon's (2009) decision tool asks patients to quantify the expected influence of each treatment side effect on their quality of life. These are combined with the survival impacts of treatments and side effects to produce a "life score" for each treatment.…”

Section: Treatment Decisionsmentioning

confidence: 99%

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Operational research techniques applied throughout cancer care services: a review

2018

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Cancer is a disease affecting increasing numbers of people. In the UK, the proportion of people affected by cancer is projected to increase from 1 in 3 in 1992, to nearly 1 in 2 by 2020. Health services to tackle cancer can be grouped broadly into prevention, diagnosis, staging, and treatment. We review examples of Operational Research (OR) papers addressing decisions encountered in each of these areas. In conclusion, we find many examples of OR research on screening strategies, as well as on treatment planning and scheduling. On the other hand, our search strategy uncovered comparatively few examples of OR models applied to reducing cancer risks, optimising diagnostic procedures, and staging. Improvements to cancer care services have been made as a result of successful OR modelling. There is potential for closer working with clinicians to enable the impact of other OR studies to be of greater benefit to cancer sufferers. ARTICLE HISTORY

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Section: Treatment Decisionsmentioning

confidence: 99%

Section: Treatment Decisionsmentioning

confidence: 99%

Operational research techniques applied throughout cancer care services: a review

2018

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“…Such decisions under risk can be extended to have multiple objectives rather than just a single objective (which is usually to maximize a monetary measure). For examples of multiobjective utility models for medical decisions, see Simon [25] and Eriksen and Keller [8].…”

Section: Tutorials In Operations Research C 2009 Informsmentioning

confidence: 99%

Multiple-Objective Decision Analysis Involving Multiple Stakeholders

Keller¹,

Merage²,

Simon³

et al. 2009

Decision Technologies and Applications

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Many operations researchers know about the use of decision analysis to help decide among alternative investments (such as pharmacological research and development investments) using decision trees with chance nodes to compute expected monetary value or return on investment of different alternatives. Such an analysis often aims to maximize a single evaluation measure for a single decision maker. We demonstrate less widely known decision analysis techniques using spreadsheet models that will help analysts understand and model the multiple objective perspectives of the stakeholders to a decision. Using this approach can aid in identifying mutually agreeable alternative actions, designing new and better alternatives, and foreseeing opposition to decisions. It can also help analysts understand the evolution of past decisions from multiple perspectives.In some cases, one objectives hierarchy can be suitable for a set of stakeholders, and differences in opinions across stakeholders can be characterized by differences in weights on the multiple objectives. Examples include the analysis for the merger of the Operations Research Society of America and The Institute of Management Sciences to become INFORMS, Arizona water resources planning, and planning for protection against radioactive iodine releases in nuclear incidents. In other cases, an objectives hierarchy will be constructed for each stakeholder because their objectives are so different that construction of separate hierarchies better represents their divergent perspectives. Examples include a tuna fish supplier source selection decision (from the perspectives of StarKist, environmentalists, and the San Diego tuna fishing fleet), the potential siting of a new Home Depot in San Juan Capistrano (from the perspectives of Home Depot, the city, residents, and competing or complementary small businesses), and a prostate cancer treatment decision (from the perspectives of former Intel CEO Andy Grove, his family, his company, and his doctors).

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“…In another decision analysis model using multi-attribute utility theory, Simon [88] considers the decision needed to be made by a patient who has been diagnosed with prostate cancer and must choose among treatments (surgery, external beam radiation, brachytherapy, and dual radiation) or do nothing. The model uses up-to-date data collected from the medical literature to compute probabilities regarding the likelihood of death and other side effects for each of the treatments or for doing nothing.…”

Section: Decision Analysis and Dynamic Influence Diagramsmentioning

confidence: 99%

Operations research

Pierskalla¹

2009

Information Knowledge Systems Management

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Prologue:In Evita, Andrew Lloyd Webber and Tim Rice wrote: Politics, the Art of the Possible. To those of us in the operations research community, we postulate: Operations Research, the Science of Better -(i.e. better processes, better systems and better decisions). Using our own and other scientific, engineering, mathematical, and social sciences methodologies, operations researchers help decision makers make better decisions; decisions leading to improvements: greater quality, lower costs, greater revenues, better access, better scheduling, lower risks, more satisfaction -with the goal of always striving for the best or optimal decisions.1389-1995/09/$17.00  2009 -IOS Press and the authors. All rights reserved 242 W.P. Pierskalla / Operations research sectors, health-care sectors, and virtually every other sector in which strategic or operational decisions must be made to improve planning, performance and outcomes.Most operations research applications involve analyzing complex situations. The approach taken begins by looking at the complex situation from a systems perspective. Inside the system, processes are diagrammed and analyzed and a model is constructed based on the flows of people, products, services, technologies and information. Using this structure, the approach models the objectives desired to be achieved, the fixed and variable constraints on the system, all available options for decisions, evaluation of all possible outcomes, estimation of risks and bringing to bear the latest tools and techniques leading to improved or optimal decisions on system operation and outcomes. In most applications, it is frequently the case that multiple objectives such as to improve quality, lower costs, improve access and improve satisfaction are simultaneously achieved. In some cases, multiple objectives trade-off against one another and the decision maker has to weigh these objectives and choose among them. In this latter situation, operations research also provides decision analytic methodologies for optimally weighing and choosing among competing objectives.Because this book is about "Engineering the Health Care System", this chapter will be devoted to operations research applications in health care delivery with mentions of theory and methodologies as appropriate. We have space to cover only some of the applications from the thousands available but hope to do so with enough breadth of topic and depth of description to give a flavor for the capabilities of operations research in developing better or best solutions for many complex health care issues. If one wishes to have a brief introduction to the theory and methodologies mentioned in this chapter see Gass and Harris [35] and the website Wikipedia, http://en.wikipedia.org/wiki/Main Page.Operations research has been used in the development of theories and methodologies and in applications in many areas of health services delivery. Some of these areas are strategic in decision making and others are operational. Some examples are:1. Health care and health care syst...

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Decision Making with Prostate Cancer: A Multiple-Objective Model with Uncertainty

Cited by 11 publications

References 40 publications

Operational research techniques applied throughout cancer care services: a review

Operational research techniques applied throughout cancer care services: a review

Multiple-Objective Decision Analysis Involving Multiple Stakeholders

Operations research

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