Can Streamlined Multicriteria Decision Analysis Be Used to Implement Shared Decision Making for Colorectal Cancer Screening?

Dolan, James G.; Boohaker, Emily A.; Allison, Jeroan J.; Imperiale, Thomas F.

doi:10.1177/0272989x13513338

Cited by 19 publications

(15 citation statements)

References 42 publications

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“…MCDA methods were also used to help decision makers with criteria assessments for setting priorities ( n = 4), to support HTA decision‐making processes ( n = 14) and regulatory decisions during pandemic influenza (Maro, Fryback, Lieu, Lee, & Martin, ), as well as to assess care quality ( n = 6), select new medical equipment ( n = 6), compare methods for suitability ( n = 3), assess screening priorities (Dolan, Boohaker, Allison, & Imperiale, ), define new fee schedules (Hung, Huang, & Chang, ), assess potential harms (Nutt, King, & Phillips, ), improve outpatient services (Kuo, Wu, & Hsu, ), support early diagnosis (Nunes, Pinheiro, Pequeno, & Pinheiro, ), select healthcare waste‐treatment technologies (Lu, You, Liu, & Li, ), select an infrastructure's localization (Vahidnia, Alesheikh, & Alimohammadi, ), optimize a process (Bennis, Janah, & Benajiba, ), and evaluate the performance of medical devices (Lee, Chung, & Shyu, ).…”

Section: Resultsmentioning

confidence: 99%

“…Another study (Kitamura, ) focused on patients' perspectives in the value assessment of treatment options. The last paper (Dolan et al, ) applied an MCDA method to assess patients' screening priorities.…”

Section: Resultsmentioning

confidence: 99%

“…Another (Kitamura, ) chose participants who were currently suffering from ovarian or endometrial cancer. One paper (Dolan et al, ) provided details on demographic characteristics of age and gender. The fourth paper (Cho and Lee, ) explained that people were selected by quota sampling across South Korea.…”

Section: Resultsmentioning

confidence: 99%

“…One study (Kitamura, ) gave questionnaires to 31 patients. In two other papers (Dolan et al, ; Cho and Lee, ), surveys were administered to 283 and 484 patients. In only one study (Danner et al, ) were stakeholders invited to workshops.…”

Section: Resultsmentioning

confidence: 99%

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Healthcare decision‐making applications using multicriteria decision analysis: A scoping review

Glaize

Duenas²,

Martinelly

et al. 2019

Multi Criteria Decision Anal

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The objective of this study is to review applications of multicriteria decision analysis (MCDA) methods to provide structure for and practical insights on how MCDA methods are applied in different healthcare areas. Four databases (Embase, Medline, Web of Science, and PubMed) were searched from 1980 to February 7, 2018. A scoping review was performed to outline the most frequently applied MCDA methods, in which only case studies were considered, as the objective was to assess the applications of MCDA methods. Seventy case studies were selected. The review showed that the first real-life application was published in 1990. With regard to areas of application, three aspects were analysed: type of health services (public or private), type of intervention (preventive, diagnostic, or treatment), and healthcare area (policymaking; resource allocation; health technology assessment; pharmaceutics; and hospital, clinical, or patient level). Data revealed that MCDA was principally used in public health services (n = 59). Three types of interventions were identified: prevention (n = 36), diagnosis (n = 32), and treatment (n = 2). An MCDA process of application was then followed to provide practical insights. During the problem-structuring phase, results showed that processes for selecting stakeholders and criteria differed among healthcare areas. For model building, authors preferred value measurement methods and especially the analytical hierarchy process. Authors of the 70 case studies included and confirmed the usefulness of MCDA in different healthcare contexts.The stakeholders, criteria, and MCDA methods chosen differ from one study to another, answering different research objectives in different healthcare areas. This scoping review highlights the importance of each MCDA step (using Belton and Stewart's framework), from problem structuring (including the selection of stakeholders) to the model building phase (encompassing the selection of the appropriate MCDA method). We recommend structured and justified analysis so that decision makers and stakeholders can feel confident during the application process in order to make final decisions more meaningful. Further work is needed to help researchers and decision makers when choosing a suitable MCDA method.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

See 2 more Smart Citations

Healthcare decision‐making applications using multicriteria decision analysis: A scoping review

Glaize

Duenas²,

Martinelly

et al. 2019

Multi Criteria Decision Anal

View full text Add to dashboard Cite

show abstract

“…In a complex decision process such as rectal cancer treatment, which depends on various criteria, the AHP method is an appropriate approach in providing decision support since it can straightly be adapted to the natural decision making processes of the decision maker [15]. In the present literature, it is possible to run across studies on priority determining use of the AHP for rectal cancer screening methods, but there is not any study, yet, on treatment methods using the AHP method [16][17][18][19][20].…”

Section: Introductionmentioning

confidence: 99%

corRECTreatment: A web-based decision support tool for rectal cancer treatment that uses the analytic hierarchy process and decision tree

Süner¹,

Karakülah²,

Dıcle³

et al. 2015

Appl Clin Inform

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SummaryBackground: The selection of appropriate rectal cancer treatment is a complex multi-criteria decision making process, in which clinical decision support systems might be used to assist and enrich physicians' decision making. Objective: The objective of the study was to develop a web-based clinical decision support tool for physicians in the selection of potentially beneficial treatment options for patients with rectal cancer. Methods: The updated decision model contained 8 and 10 criteria in the first and second steps respectively. The decision support model, developed in our previous study by combining the Analytic Hierarchy Process (AHP) method which determines the priority of criteria and decision tree that formed using these priorities, was updated and applied to 388 patients data collected retrospectively. Later, a web-based decision support tool named corRECTreatment was developed. The compatibility of the treatment recommendations by the expert opinion and the decision support tool was examined for its consistency. Two surgeons were requested to recommend a treatment and an overall survival value for the treatment among 20 different cases that we selected and turned into a scenario among the most common and rare treatment options in the patient data set. Results: In the AHP analyses of the criteria, it was found that the matrices, generated for both decision steps, were consistent (consistency ratio<0.1). Depending on the decisions of experts, the consistency value for the most frequent cases was found to be 80% for the first decision step and 100% for the second decision step. Similarly, for rare cases consistency was 50% for the first decision step and 80% for the second decision step. Conclusions:The decision model and corRECTreatment, developed by applying these on real patient data, are expected to provide potential users with decision support in rectal cancer treatment processes and facilitate them in making projections about treatment options. Research Article

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Implications of the stability analysis of preferences for personalised colorectal cancer screening

Sava

Stanciu

Dolan

et al. 2021

Multi Criteria Decision Anal

Self Cite

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Patients are increasingly interested in becoming involved in the medical decisionmaking process. As a result, healthcare providers and researchers are concerned with finding new ways to integrate patients' preferences, by understanding their commitment to and the stability of those preferences. Preventive medicine, such as colorectal cancer screening, presents an opportunity for personalising the decision-making trajectory based on patients' preferences. In this paper, we propose a framework for a joint decision-making process, capable of integrating patients' changing preferences, as described by a stability analysis of those preferences and design scenarios for implementing the process in clinical practice. In this study, a secondary data analysis, we present scenarios that demonstrate how the stability analysis of an Analytic Network Process (ANP) model supports personalising the process of agreeing on an appropriate colorectal cancer screening option. We illustrate the framework using two patients whose preferences have different stabilities and for whom the healthcare provider has different rankings for the recommended alternatives. The results show the differences in additional medical information the healthcare provider might need to provide as part of the joint decision-making process in order to reach an agreement between the patient and the provider. A stability analysis of the patient's preferences provides the healthcare provider with a mapping of the preferred options. It also shows how the patient's most preferred alternative might change as the patient obtains additional relevant medical information. Knowing how the patient's priorities might change supports a personalisation of the medical decision-making process. We conclude that the healthcare provider can utilise the stability analysis of a patient's preferences to identify possible dialogue paths that would enable reaching a consensus about an appropriate screening option.

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Can Streamlined Multicriteria Decision Analysis Be Used to Implement Shared Decision Making for Colorectal Cancer Screening?

Cited by 19 publications

References 42 publications

Healthcare decision‐making applications using multicriteria decision analysis: A scoping review

Healthcare decision‐making applications using multicriteria decision analysis: A scoping review

corRECTreatment: A web-based decision support tool for rectal cancer treatment that uses the analytic hierarchy process and decision tree

Implications of the stability analysis of preferences for personalised colorectal cancer screening

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