scholarly journals Individual Value Clarification Methods Based on Conjoint Analysis: A Systematic Review of Common Practice in Task Design, Statistical Analysis, and Presentation of Results

2018 ◽  
Vol 38 (6) ◽  
pp. 746-755 ◽  
Author(s):  
Marieke G.M. Weernink ◽  
Janine A. van Til ◽  
Holly O. Witteman ◽  
Liana Fraenkel ◽  
Maarten J. IJzerman
Keyword(s):  
Decision Making ◽  
Shared Decision Making ◽  
Conjoint Analysis ◽  
Decision Aids ◽  
Clinical Decision ◽  
Task Design ◽  
Shared Decision ◽  
Attribute Importance ◽  
Barriers To Implementation ◽  
Choice Tasks

Background. There is an increased practice of using value clarification exercises in decision aids that aim to improve shared decision making. Our objective was to systematically review to which extent conjoint analysis (CA) is used to elicit individual preferences for clinical decision support. We aimed to identify the common practices in the selection of attributes and levels, the design of choice tasks, and the instrument used to clarify values. Methods. We searched Scopus, PubMed, PsycINFO, and Web of Science to identify studies that developed a CA exercise to elicit individual patients’ preferences related to medical decisions. We extracted data on the above-mentioned items. Results. Eight studies were identified. Studies included a fixed set of 4–8 attributes, which were predetermined by interviews, focus groups, or literature review. All studies used adaptive conjoint analysis (ACA) for their choice task design. Furthermore, all studies provided patients with their preference results in real time, although the type of outcome that was presented to patients differed (attribute importance or treatment scores). Among studies, patients were positive about the ACA exercise, whereas time and effort needed from clinicians to facilitate the ACA exercise were identified as the main barriers to implementation. Discussion. There is only limited published use of CA exercises in shared decision making. Most studies resembled each other in design choices made, but patients received different feedback among studies. Further research should focus on the feedback patients want to receive and how the CA results fit within the patient–physician dialogue.

scholarly journals Understanding shared decision-making experience among vulnerable population: Focus group with food bank clients

2020 ◽  
pp. 1-8
Author(s):  
Young Ji Lee ◽  
Tiffany Brazile ◽  
Francesca Galbiati ◽  
Megan Hamm ◽  
Cindy Bryce ◽  
...  
Keyword(s):  
Decision Making ◽  
Focus Groups ◽  
Shared Decision Making ◽  
Vulnerable Populations ◽  
Clinical Decision Making ◽  
Decision Aids ◽  
Clinical Decision ◽  
Therapeutic Options ◽  
Shared Decision ◽  
Food Bank

Abstract Introduction: Shared decision-making (SDM) is a critical component of delivering patient-centered care. Members of vulnerable populations may play a passive role in clinical decision-making; therefore, understanding their prior decision-making experiences is a key step to engaging them in SDM. Objective: To understand the previous healthcare experiences and current expectations of vulnerable populations on clinical decision-making regarding therapeutic options. Methods: Clients of a local food bank were recruited to participate in focus groups. Participants were asked to share prior health decision experiences, explain difficulties they faced when making a therapeutic decision, describe features of previous satisfactory decision-making processes, share factors under consideration when choosing between treatment options, and suggest tools that would help them to communicate with healthcare providers. We used the inductive content analysis to interpret data gathered from the focus groups. Results: Twenty-six food bank clients participated in four focus groups. All participants lived in areas of socioeconomic disadvantage. Four themes emerged: prior negative clinical decision-making experience with providers, patients preparing to engage in SDM, challenges encountered during the decision-making process, and patients’ expectations of decision aids. Participants also reported they were unable to discuss therapeutic options at the time of decision-making. They also expressed financial concerns and the need for sufficiently detailed information to evaluate risks. Conclusion: Our findings suggest the necessity of developing decision aids that would improve the engagement of vulnerable populations in the SDM process, including consideration of affordability, use of patient-friendly language, and incorporation of drug–drug and drug–food interactions information.

scholarly journals Current Status and Future Prospects for Shared Decision Making before and after Total Knee Replacement Surgery—A Scoping Review

2021 ◽  
Vol 18 (2) ◽  
pp. 668
Author(s):  
Geert van der Sluis ◽  
Jelmer Jager ◽  
Ilona Punt ◽  
Alexandra Goldbohm ◽  
Marjan J. Meinders ◽  
...  
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Total Knee Replacement ◽  
Shared Decision Making ◽  
Knee Replacement ◽  
Study Design ◽  
Scoping Review ◽  
Decision Aids ◽  
Shared Decision ◽  
Total Knee

Background. To gain insight into the current state-of-the-art of shared decision making (SDM) during decisions related to pre and postoperative care process regarding primary total knee replacement (TKR). Methods. A scoping review was performed to synthesize existing scientific research regarding (1) decisional needs and preferences of patients preparing for, undergoing and recovering from TKR surgery, (2) the relation between TKR decision-support interventions and SDM elements (i.e., team talk, option talk, and decision talk), (3) the extent to which TKR decision-support interventions address patients’ decisional needs and preferences. Results. 2526 articles were identified, of which 17 articles met the inclusion criteria. Of the 17 articles, ten had a qualitative study design and seven had a quantitative study design. All included articles focused on the decision whether to undergo TKR surgery or not. Ten articles (all qualitative) examined patients’ decisional needs and preferences. From these, we identified four domains that affected the patients’ decision to undergo TKR: (1) personal factors, (2) external factors, (3) information sources and (4) preferences towards outcome prediction. Seven studies (5) randomized controlled trials and 2 cohort studies) used quantitative analyses to probe the effect of decision aids on SDM and/or clinical outcomes. In general, existing decision aids did not appear to be tailored to patient needs and preferences, nor were the principles of SDM well-articulated in the design of decision aids. Conclusions. SDM in TKR care is understudied; existing research appears to be narrow in scope with limited relevance to established SDM principles and the decisional needs of patients undertaking TKR surgery.

Certified Patient Decision Aids: Solving Persistent Problems with Informed Consent Law

2017 ◽  
Vol 45 (1) ◽  
pp. 12-40 ◽  
Author(s):  
Thaddeus Mason Pope
Keyword(s):  
Decision Making ◽  
Informed Consent ◽  
Medical Treatment ◽  
Shared Decision Making ◽  
Decision Aids ◽  
Shared Decision ◽  
Legal Doctrine ◽  
Patient Decision Aids ◽  
Patient Decision ◽  
Decision Making Processes

The legal doctrine of informed consent has overwhelmingly failed to assure that the medical treatment patients get is the treatment patients want. This Article describes and defends an ongoing shift toward shared decision making processes incorporating the use of certified patient decision aids.

scholarly journals Crafting Care That Fits: Workload and Capacity Assessments Complementing Decision Aids in Implementing Shared Decision Making (Preprint)

2019 ◽  
Author(s):  
Thomas H Wieringa ◽  
Manuel F Sanchez-Herrera ◽  
Nataly R Espinoza ◽  
Viet-Thi Tran ◽  
Kasey Boehmer
Keyword(s):  
Decision Making ◽  
Shared Decision Making ◽  
Chronic Conditions ◽  
Decision Aids ◽  
Multiple Chronic Conditions ◽  
Shared Decision ◽  
Patient Centered ◽  
Patient Goals ◽  
Minimally Disruptive Medicine ◽  
Workload Capacity

UNSTRUCTURED About 42% of adults have one or more chronic conditions and 23% have multiple chronic conditions. The coordination and integration of services for the management of patients living with multimorbidity is important for care to be efficient, safe, and less burdensome. Minimally disruptive medicine may optimize this coordination and integration. It is a patient-centered approach to care that focuses on achieving patient goals for life and health by seeking care strategies that fit a patient’s context and are minimally disruptive and maximally supportive. The cumulative complexity model practically orients minimally disruptive medicine–based care. In this model, the patient workload-capacity imbalance is the central mechanism driving patient complexity. These elements should be accounted for when making decisions for patients with chronic conditions. Therefore, in addition to decision aids, which may guide shared decision making, we propose to discuss and clarify a potential workload-capacity imbalance.

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