Improve Decision Quality Research Articles

The practicalities of a partial lottery to allocate research funding

Abstract This article explores the practical dimension of organizing a partial lottery as an alternative funding allocation mechanism in academic institutions. Following an assessment of the recent literature that presents criticism of traditional ranking-based system derived from academic peer assessment and the need for improved decision-making procedures in research funding, we highlight four key arguments for organizing a partial lottery: improved decision quality (more fair, transparent, and divers), an alternative to ranking-based selection, prevention of questionable research practices, and increased efficiency. Based on our observations from a lottery-based ‘seed money call’ at Tilburg University, we provide insights into the organization and implementation of a lottery procedure, including the criteria for proposal eligibility, the administrative process, and the weighting mechanism based on budget categories. We furthermore share six lessons we learned that might be useful for future implementation in other institutional contexts, emphasizing the need for transparency, external supervision, and pre-registration of the lottery procedure to ensure trust and minimize gaming. As such, we not only contribute to the ongoing conceptual discussion about improving funding allocation mechanisms in academia. Our article also offers an account of how partial lotteries could be put into practice.

Validation, adaptation and application of a multi‐criteria decision analysis‐based framework for chemotherapeutic agents in Egypt

AbstractHealth technology assessment is a systematic, transparent, robust, and unbiased assessment of healthcare technology that links evidence and decisions. Healthcare decisions usually require trading‐off, and using a structured approach, such as multi‐criteria decision analysis (MCDA), could improve decision quality. This study aimed to adapt an MCDA‐based framework for oncological drug evaluation in an Egyptian clinical setting to explore the perspectives of different stakeholders. The 10th edition of the Evidence and Value: Impact on decision making framework was translated, validated, adapted, and applied to explore key differences between the priorities of different stakeholders for coverage decisions in the oncology field in Egypt. A direct rating scale or hierarchical point allocation was used to elicit criteria weights. Normalized weights were calculated and compared using the preset cut‐off value of 0.008. Understandability, willingness to use the adopted weighting techniques, and cognitive burden were assessed and compared. Ninety participants completed the criteria‐weighting interview for the adapted tool. The elicited criteria weights differed between the two adopted weighting techniques when comparing stakeholders' priorities using the preset cut‐off (0.008). However, there was no significant difference in the weighting technique understandability, future use willingness, and cognitive burden parameters on categorization by either the weighting technique or stakeholder group. This study provides a specially tailored, straightforward procedure for Egyptian stakeholders to evaluate oncologic drugs in a standardized manner by combining various inputs. It also highlights the main variations across Egyptian stakeholder preferences.

Consulting Multiple Advisors: When It Hurts and When It Does Not Hurt the Advisor–Advisee Relationship?

ABSTRACTConsulting multiple advisors tends to improve decision quality; however, limited understanding exists regarding how advisors respond to the presence of co‐advisors. Previous research has cautioned about the potential interpersonal costs of seeking advice from multiple sources. It suggests that advisors may perceive their advice as less likely to be utilized, diminishing their willingness to continue assisting the seeker. In contrast, we propose that advisors are generally unconcerned if seekers consult others, as long as they are informed before offering advice. We argue that advisors do not closely monitor or dwell on the utilization of their advice and maintain a positive attitude toward the seeker unless they infer rejection of their advice. In three studies, we show that disclosing a co‐advisor upfront completely eliminates any negative interpersonal effects by rendering inferences about advice rejection implausible. Advisors respond as if they were the sole advisor irrespective of the presence of multiple co‐advisors and regardless of whether they are consulted first of second.

Human-AI collaboration to mitigate decision noise in financial underwriting: A study on FinTech innovation in a lending firm

Financial institutions have recognized the value of collaborating human expertise and AI to create high-performance augmented decision-support systems. Stakeholders at lending firms have increasingly acknowledged that plugging data into AI algorithms and eliminating the role of human underwriters by automation, with the expectation of immediate returns on investment from business process automation, is a flawed strategy. This research emphasizes the necessity of auditing the consistency of decisions (or professional judgment) made by human underwriters and monitoring the ability of data to capture the lending policies of a firm to lay a strong foundation for a legitimate system before investing millions in AI projects. The judgments made by experts in the past re-emerge in the future as outcomes or labels in the data used to train and evaluate algorithms. This paper presents Evidential Reasoning-eXplainer, a methodology to estimate probability mass as an extent of support for a given decision on a loan application by jointly assessing multiple independent and conflicting pieces of evidence. It quantifies variability in past decisions by comparing the subjective judgments of underwriters during manual financial underwriting with outcomes estimated from data. The consistency analysis improves decision quality by bridging the gap between past inconsistent decisions and desired ultimate-true decisions. A case study on a specialist lending firm demonstrates the strategic work plan adapted to configure underwriters and developers to capture the correct data and audit the quality of decisions.

Bridging the gap: Experimental evidence on information provision and health insurance choices.

Previous research has shown that individuals do not always make rational decisions when selecting their health insurance, for example, due to the existence of information frictions or mental gaps. We study the effect of specific types of information provision for decision support on health plan choices and test their potential to improve decision quality by implementing a randomized laboratory experiment. We provide personalized and generic aids, differentiate between numerical and visual decision support, and provide one or two optional formats of personalized information. We find that generic aids have no effect on health plan choices while personalized information leads to better choices as measured by several indicators of decision quality. The largest effects were observed for those who "opted in" to visualize personalized information, with immediate and lasting improvements in health insurance decisions. By reducing information frictions, our results suggest that accessible and easy-to-use tools can positively impact health insurance navigation, improve decision-making, and reduce switching costs.

Differential effects of prior outcomes and pauses on the speed and quality of risky choices

AbstractFailures to obtain rewards influence what people choose to do next and how quickly they execute a chosen action, which are two components of motivated behavior. For instance, in risky decisions, losses can induce faster responses and sometimes increase risk‐taking, which may lead to detrimental consequences in some situations (such as gambling). Pauses might reduce these motivational influences of prior outcomes. To examine this question, participants alternated between a guess game, in which they won or lost money, and a choice game, in which they chose between a high probability of winning a small amount of money and a low probability of winning a large amount of money. The pause between a guess and a choice game was made either short (0 or 300 ms) or long (3000 ms). In four experiments, prior outcomes consistently influenced decision speed, such that people chose faster after a loss than after a win. However, prior outcomes did not consistently influence people's choices. In contrast, pauses increased decision quality, such that participants chose the option with a higher expected value more often, without substantially reducing decision speed. Pauses may improve decision quality by influencing predecisional attention allocation to relevant information, as its effect was absent when the overall task attention was high (Experiment 3). These findings have implications for both safer gambling and risky decision research. Future work can examine the underlying computational and cognitive processes and the generalizability of these findings to other contexts and populations.

A Qualitative Exploration of Stakeholders' Preferences for Early-Stage Rectal Cancer Treatment.

As treatment options for patients with rectal cancer evolve, patients with early-stage rectal cancer may have a treatment choice between surgery and a trial of nonoperative management. Patients must consider the treatments' clinical tradeoffs alongside their personal goals and preferences. Shared decision-making (SDM) between patients and clinicians can improve decision quality when patients are faced with preference-sensitive care options. We interviewed 28 stakeholders (13 clinicians and 15 patients) to understand their perspectives on early-stage rectal cancer treatment decision-making. Clinicians included surgeons, medical oncologists, and radiation oncologists who treat rectal cancer. Adult patients included those diagnosed with early-stage rectal cancer in the past 5 years, recruited from an institutional database. A semi-structured interview guide was developed based on a well-established decision support framework and reviewed by the research team and stakeholders. Interviews were conducted between January 2022 and January 2023. Transcripts were coded by 2 raters and analyzed using thematic analysis. Both clinicians and patients recognized the importance of SDM to support high-quality decisions about the treatment of early-stage rectal cancer. Barriers to SDM included variable clinician motivation due to lack of training or perception of patients' desires or abilities to engage, as well as time-constrained encounters. A decision aid could help facilitate SDM for early-stage rectal cancer by providing standardized, evidence-based information about treatment options that align with clinicians' and patients' decision needs.

'A good decision is the one that feels right for me': Codesign with patients to inform theoretical underpinning of a decision aid website.

Patient decision aids (PtDA) complement shared decision-making with healthcare professionals and improve decision quality. However, PtDA often lack theoretical underpinning. We are codesigning a PtDA to help people with increased genetic cancer risks manage choices. The aim of an innovative workshop described here was to engage with the people who will use the PtDA regarding the theoretical underpinning and logic model outlining our hypothesis of how the PtDA would lead to more informed decision-making. Short presentations about psychological and behavioural theories by an expert were interspersed with facilitated, small-group discussions led by patients. Patients were asked what is important to them when they make health decisions, what theoretical constructs are most meaningful and how this should be applied to codesign of a PtDA. An artist created a visual summary. Notes from patient discussions and the artwork were analysed using reflexive thematic analysis. The overarching theme was: It's personal. Contextual factors important for decision-making were varied and changed over time. There was no one 'best fit' theory to target support needs in a PtDA, suggesting an inductive, flexible framework approach to programme theory would be most effective. The PtDA logic model was revised based on patient feedback. Meaningful codesign of PtDA including discussions about the theoretical mechanisms through which they support decision-making has the potential to lead to improved patient care through understanding the intricately personal nature of health decisions, and tailoring content and format for holistic care. Patients with lived experience were involved in codesign and coproduction of this workshop and analysis as partners and coauthors. Patient discussions were the primary data source. Facilitators provided a semi-structured guide, but they did not influence the patient discussions or provide clinical advice. The premise of this workshop was to prioritise the importance of patient lived experience: to listen, learn, then reflect together to understand and propose ideas to improve patient care through codesign of a PtDA.

Evaluation of a Novel Question Prompt List in Pediatric Surgical Oncology

IntroductionParents of children with cancer describe interactions with clinicians as emotionally distressing. Patient engagement in treatment discussions decreases decisional conflict and improves decision quality which may limit such distress. We have shown that parents prefer to engage surgeons by asking questions, but parents may not know what to ask. Question Prompt Lists (QPLs), structured lists of questions designed to help patients ask important questions, have not been studied in pediatric surgery. We developed a QPL designed to empower parents to ask meaningful questions during pediatric surgical oncology discussions. We conducted a mixed methods analysis to assess the acceptability, appropriateness, and feasibility of using the QPL. MethodsKey stakeholders at an academic children's hospital participated in focus groups to discuss the QPL. Focus groups were recorded and transcribed. Participants were surveyed regarding QPL acceptability, appropriateness, and feasibility. Thematic content analysis of transcripts was performed. ResultsFour parents, five nurses, five nurse practitioners, five oncologists, and four surgeons participated. Seven key themes were identified: (1) QPL as a tool of empowerment; (2) stick to the surgical details; (3) QPLs can impact discussion quality; (4) time consuming, but not overly disruptive; (5) parental emotion may impact QPL use; (6) provide QPLs prior to surgical consultation in both print and digital formats; and (7) expansion of QPLs to other disciplines. Over 70% of participants agreed that the QPL was acceptable, appropriate, and feasible. ConclusionsOur novel QPL is acceptable, appropriate, and feasible to use with parents of pediatric surgical oncology patients.

Intelligent Deepwater Solutions Hub Maximizes Value Across Asset Life Cycle

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 211453, “Intelligent Deepwater Advanced Solutions Hub for Value Maximization Throughout Asset Life Cycle,” by Sam Ryu, Carmela Chaney, and Wei Xu, ExxonMobil, et al. The paper has not been peer reviewed. _ Challenges posed by life-cycle management of an offshore asset, multidisciplinary systems engineering, and competing project objectives provide an opportunity for a new approach to maximize value. The objective of the complete paper is to introduce the operator’s intelligent Deepwater Advanced Solutions Hub (iDASH) approach, wherein various engineering tools are integrated strategically to improve decision quality. Introduction The complexities inherent in producing offshore oil and gas mean that creation of an optimal solution for all phases of the project life cycle is a serious challenge. Market research has suggested that the oil and gas industry could benefit from increased systems engineering with an approach that looks beyond first application, integrates requirements, and supports the identification of changes for new applications. The industry has been slow to adopt digitalization, with one of the lowest levels of digital maturity compared with other sectors. For the purposes of this paper, offshore oil and gas development can be broken into four phases after a field is evaluated to be commercially viable: concept selection, definition and execution, operations, and decommissioning. Each phase has unique objectives and challenges. During concept selection, generation of creative multiple alternatives for deepwater full-field development is a challenge because each offshore project is unique and requires time-consuming discussion cycles involving high uncertainty, multidisciplinary input, and constraints identified from a wide range of technical specialties. Once detailed design and execution begin, the objective becomes value preservation. Collaboration between the operator’s project management and contractors becomes a resource-intensive process. After startup, the objective moves toward value realization. Handover from project teams to operations can be time-consuming, leaving key pieces of data missing. Unexpected downtime, integrity issues, or process conditions can erode value and delay project payback. Operations also present an opportunity to process and implement feedback and lessons learned. The authors divide engineering tools into four pillars within the discussed iDASH approach: iConcept (concept-selection tools), iDesign (definition and execution tools), iOperate (operation tools), and iDecom (decommissioning tools), offering different value to each stage of value maximization, reducing capital expenditure (CAPEX) and maximizing net present value (NPV), achieving balance with other important objectives. These four pillars are expanded upon and illustrated with use cases in the complete paper. Finally, strong data integration is the foundation of this platform, enhancing interdisciplinary work, ideation cycle time, and decision traceability. Making Quality Decisions With Multiple Alternatives iConcept is a digital suite focusing on addressing challenges at the concept-selection stage. The centralized suite includes a variety of different tools developed both internally and externally based on data analytics, artificial intelligence (AI), and decision science that aim to improve decision quality. One of the key tools being leveraged is called the Field Layout Concept Optimizer. Through its use, a team can evaluate multiple alternative deepwater field developments rapidly to enable quick turnaround for quality decision-making. Multiple disciplines are integrated to reduce human bias.

MP48-18 PATIENT SATISFACTION WITH THE PHYSICIAN RELATIONSHIP IMPACTS THE EFFECTIVENESS OF DECISION AIDS IN MEN WITH PROSTATE CANCER

You have accessJournal of UrologyCME1 Apr 2023MP48-18 PATIENT SATISFACTION WITH THE PHYSICIAN RELATIONSHIP IMPACTS THE EFFECTIVENESS OF DECISION AIDS IN MEN WITH PROSTATE CANCER Patrick Wilson, Jonathon Bergman, Jefersson Villatoro, Lorna Kwan, Kristen Williams, David Penson, and Christopher Saigal Patrick WilsonPatrick Wilson More articles by this author , Jonathon BergmanJonathon Bergman More articles by this author , Jefersson VillatoroJefersson Villatoro More articles by this author , Lorna KwanLorna Kwan More articles by this author , Kristen WilliamsKristen Williams More articles by this author , David PensonDavid Penson More articles by this author , and Christopher SaigalChristopher Saigal More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003294.18AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: We scaled a Decision Aid (DA) for men with prostate cancer in different healthcare settings to learn best practices for implementation across a variety of patient populations. This DA was previously shown to improve decision quality at an academic medical center (AMC). We aimed to understand whether patients who showed persistent decisional conflict exhibited distinct characteristics. METHODS: The DA (“WiserCare”) was issued to men with newly diagnosed prostate cancer at a public hospital and two AMCs prior to a clinic visit. The DA displays personalized clinical outcomes and measures preferences for these outcomes with conjoint analysis. We used the Decisional Conflict Scale (DCS) score to categorize patients as having no difficulty (<25), some difficulty (25-37.5), or severe difficulty (>37.5) with making a decision after using the DA, based on prior data. We measured DCS score, Net Promoter Score (likelihood to recommend the physician), and treatment choice after the visit. We evaluated differences in DCS scores using Chi-squared analysis. A Spanish language version DA was available. RESULTS: 1,961 men were invited to use the DA across three sites, and 1,098 did so. 356 completed the post-visit survey. Overall, DCS scores were excellent (total median 6.3 across sites). However, patients reporting “severe difficulty” had significantly worse Net Promoter Scores for their doctor compared to patients with “no difficulty.” Patients with “severe difficulty” were also more likely to be unsure of their treatment choice. Patient age, language, and disease risk did not have a significant association with difficulty with decision making. CONCLUSIONS: Prostate cancer SDM programs can be scaled successfully in public hospitals serving men of varying languages and SES, with overall preservation of DA effectiveness. Patients with persistent “severe difficulty” making decisions were less satisfied with their physician interactions. They were also more likely to remain undecided regarding treatment choice. Additional qualitative work with this population is needed to understand how the physician-patient relationship impacts SDM and whether DAs can be modified to further support specific patient needs. Source of Funding: Patient Centered Outcomes Research Institute (PCORI) © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e662 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Patrick Wilson More articles by this author Jonathon Bergman More articles by this author Jefersson Villatoro More articles by this author Lorna Kwan More articles by this author Kristen Williams More articles by this author David Penson More articles by this author Christopher Saigal More articles by this author Expand All Advertisement PDF downloadLoading ...

An experiment on the impact of predictive analytics on kidney offers acceptance decisions

Because of the breadth of factors that might affect kidney transplant decisions to accept an organ or wait for another, presumably “better” offer, a high degree of heterogeneity in decision making exists among transplant surgeons and hospitals. These decisions do not typically include objective predictions regarding the future availability of equivalent or better-quality organs or the likelihood of patient death while waiting for another organ. To investigate the impact of displaying such predictions on organ donation decision making, we conducted a statistically designed experiment involving 53 kidney transplant professionals, in which kidney offers were presented via an online application and systematically altered to observe the effects on decision making. We found that providing predictive analytics for time-to-better offers and patient mortality improved decision consensus and decision-maker confidence in their decisions. Providing a visual display of the patient’s mortality slope under accept/reject conditions shortened the time-to-decide but did not have an impact on the decision itself. Presenting the risk of death in a loss frame as opposed to a gain frame improved decision consensus and decision confidence. Patient-specific predictions surrounding future organ offers and mortality may improve decision quality, confidence, and expediency while improving organ utilization and patient outcomes.

“IS IT TIME TO STOP DRIVING?”: A RANDOMIZED TRIAL OF AN ONLINE DECISION AID FOR OLDER DRIVERS

Abstract The decision to stop or continue driving can be challenging for older adults. In a prospective two-arm randomized trial, we sought to test whether an online driving decision aid (DDA) would improve decision quality. We recruited 301 English-speaking licensed drivers, age ≥70 years, without significant cognitive impairment but with ≥1 diagnosis associated with increased likelihood of driving cessation, from clinics associated with study sites in three states. They were randomized to view 1) the online Healthwise® DDA for older adults addressing “Is it time to stop driving?”; or 2) a control condition of web-based information. Our primary outcome was decision conflict as estimated by the Decisional Conflict Scale (DCS; lower scores indicate higher quality). Secondary outcomes were knowledge and decision self-efficacy about driving decisions. We examined differences in post-randomization outcomes by study arm using generalized linear mixed-effects models with adjustment for site and pre-randomization scores. Intervention participants had a lower mean DCS score (12.3 DDA vs 15.2 control; p=0.017) and a higher mean knowledge score (88.9 DDA vs 79.9 control; p=0.038); we found no difference between groups in self-efficacy scores. The DDA had high acceptability; 86.9% of those who viewed it said they would recommend it to others in similar situations.The online Healthwise® DDA decreased decision conflict and increased knowledge in this sample of English-speaking, older adults without significant cognitive impairment. Use of such resources in clinical or community settings may support older adults as they transition from driving to other forms of mobility.

The impacts of modelling-based SSI teaching module on preservice teachers’ decision making – a case of Dongfeng Highway route selection

ABSTRACT The demand for the Dongfeng Highway connecting Dongshi and Fengyuan, Taiwan, originates from a 7.3 ML earthquake disaster affecting residents’ medical treatment and material transportation. The Dongfeng Highway route selection was identified as the socioscientific issues (SSI) and the Decision Factors Table and SageModeler (two representational modelling tools) were used to design a teaching module with two Generation-Evaluation-Modification modelling cycles. This study aims to explore the impacts of the Modelling-based SSI (M-SSI) teaching module on 23 preservice teachers’ (PSTs) plans, factor dimensions, and quality of decision making. The results indicated that the PSTs focused on the original purpose of constructing the Dongfeng Highway; therefore, the Fengshi plan, which has advantages in safety, economy, and ecology, was chosen by most participants. Initially, PSTs focused only on ‘relevance to the topic’ factor and few relationships among other factors. However, they improved their decision quality by focusing on ‘comparability and measurement’ and ‘sufficient evidence or justification’ factors and more vertical relationships among factors after completing the module. Although the PSTs’ horizontal relationships among factors still need to be strengthened, they demonstrated significant increases in factor, relationship, and overall scores with large effect sizes, indicating that the M-SSI teaching module can improve decision quality.

Too much information? The use of extraneous information to support decision‐making in emergency settings

AbstractDecision‐makers in emergency settings need to employ the breadth of evidence available so as to inform critical judgments, yet the acute time pressure suggests that in some cases only partial information could be employed. Investigating this tension, the current study focuses on the usefulness of extraneous information that arrives from outside the organization and supplements the information that is available through local information systems. Namely, we explore the extent to which the use of Health Information Exchanges (HIEs)—a network that integrates patients’ clinical information across medical organizations and points of care—facilitates diagnosis decisions in hospitals’ emergency departments (EDs). Adopting the lens of cognitive decision‐making theory, we advance hypotheses regarding the moderating effects of the tasks’ cognitive requirements (diagnosis complexity) and clinicians’ time availability (ED crowdedness) on the relation between the use of extraneous information (in the form of HIE data) and decision quality (ED revisit rate). Our empirical investigation employs complete field data collected from a network of hospitals, capturing over half‐a‐million patient ED encounters. The results reveal that, in general, ED clinicians’ use of the HIE improves decision quality, as reflected in reduced patient revisits to the ED. However, when diagnosis complexity is low, this effect is reversed, such that HIE use is associated with increased ED revisit rates. Our discussion highlights the conditions under which extraneous information contributes to better decision‐making and calls for a mindful use of interorganizational information exchanges in emergency settings.

Decision Support System for Determining the Best Nurse at Grandmed Hospital Using the Simple Additive Weighting Method

A decision support system is a combination of individual intelligence sources with component capabilities to improve decision quality. Decision support system is also a computer-based information system for decision-making management that handles semi-structured problems. The purpose of this study was to create an application for nurse employees at Grandmed Hospital. Based on the results of the research that has been discussed, the Decision Support System for Determining the Best Nurse at Grandmed Hospital using the Simple Additive Wieghting (SAW) method with the benefit of being able to make it easier to process nurse data and make it easier to determine the best nurse for a nurse promotion at Grandmed Hospital.

Big data and decision quality: the role of management accountants’ data analytics skills

PurposeExisting research on the relationship between big data and organizational decision quality is still few and far between, and what does exist often assumes direct effects of big data on decision quality. More recent research indicates that such direct effects may be too simplistic, and in particular, an organization’s overall human skills are often not considered sufficiently. Inspired by the knowledge-based view, we therefore propose that interactions between three aspects of big data usage and management accountants’ data analytics skills may be key to reaching high-quality decisions. The purpose of this study is to test these predictions based on a survey of US firms.Design/methodology/approachThe authors draw on survey data from 140 US firms. This survey has been conducted via MTurk in 2020.FindingsThe results of the study show that the quality of big data sources is associated with higher perceived levels of decision quality. However, according to the results, the breadth of big data sources and a data-driven culture only improve decision quality if management accountants’ data analytics skills are highly developed. These results point to the important, but so far unexamined role of an organization’s management accountants and their skills for translating big data into high-quality decisions.Practical implicationsThe present study highlights the importance of an organization’s human skills in creating value out of big data. In particular, the findings imply that management accountants may need to increasingly draw on data analytics skills to make the most out of big data for their employers.Originality/valueThis study is among the first, to the best of the authors’ knowledge, to provide empirical proof of the relevance of an organization’s management accountants and their data analytics skills for reaching desirable firm-level outcomes. In addition, this study thus adds to the further advancement of the knowledge-based view by providing evidence that in contemporary big-data environments, interactions between tacit and explicit knowledge seem crucial for driving desirable firm-level outcomes.

Managing attention: more mindful team decision-making

ABSTRACT Prior research has found that teams using computer-mediated communication (CMC) often make poor decisions because team members fail to pay attention to the information they receive from others. We developed a process designed to focus team members’ attention on one aspect of decision-making at a time. We divided the group decision-making process into three phases: 1) an initial period to contribute information, 2) a middle period of silence (i.e., no typing) to read others’ contributions, and 3) a final period to discuss the information. We designed a lab experiment to compare the information processing and decision-making of teams using this text-based CMC process to teams using text-based CMC with no intervention. Teams that used this CMC process contributed more information, recalled more information, committed fewer errors, and made better decisions. The effect sizes were large, about two times greater than the average effect sizes for the use of CMC. An examination of this new process suggests that it improved decision quality mostly by helping teams avoid errors.

'Replace uncertainty with information': shared decision-making and decision quality surrounding catheter ablation for atrial fibrillation.

As a first step in developing a decision aid to support shared decision-making (SDM) for patients with atrial fibrillation (AF) to evaluate treatment options for rhythm and symptom control, we aimed to measure decision quality and describe decision-making processes among patients and clinicians involved in decision-making around catheter ablation for AF. We conducted a cross-sectional, mixed-methods study guided by an SDM model outlining decision antecedents, processes, and outcomes. Patients and clinicians completed semi-structured interviews about decision-making around ablation, feelings of decision conflict and regret, and preferences for the content, delivery, and format of a hypothetical decision aid for ablation. Patients also completed surveys about AF symptoms and aspects of decision quality. Fifteen patients (mean age 71.1 ± 8.6 years; 27% female) and five clinicians were recruited. For most patients, decisional conflict and regret were low, but they also reported low levels of information and agency in the decision-making process. Most clinicians report routinely providing patients with information and encouraging engagement during consultations. Patients reported preferences for an interactive, web-based decision aid that clearly presents evidence regarding outcomes using data, visualizations, videos, and personalized risk assessments, and is available in multiple languages. Disconnects between clinician efforts to provide information and bolster agency and patient experiences of decision-making suggest decision aids may be needed to improve decision quality in practice. Reported experiences with current decision-making practices and preferences for decision aid content, format, and delivery can support the user-centred design and development of a decision aid.

Fostering shared decision-making about prostate cancer screening among African American men patients and their primary care providers: a randomized behavioral clinical trial

BackgroundProstate cancer is the third most prevalent cancer in the American population. Furthermore, the prognosis is worse in African American as there is increased morbidity and mortality associated with it.PurposeThe purpose of this study is to evaluate the effectiveness of a new online method to educate the patient population regarding prostate cancer risk, diagnosis, treatments, and their decisions about whether to be screened for the early detection of prostate cancer.MethodsTwo hundred Black male patients are recruited from different clinical sites and randomized to either the control arm (usual care) or the intervention arm (educational program). We will compare the effectiveness of the intervention to see if patients are discussing the need of getting a prostate-specific antigen (PSA) test, and the possible benefits and harms that may result of having or not having the test, with their primary care providers.DiscussionShared decision-making (SDM) is the current standard in most cancer-screening guidelines and also a standard of person-centered care. However, there is a lack of evidence-based approaches to improve decision quality in clinical settings and an increased ambiguity of applying SDM for PSA-based screening among Black men in primary care. Our proposal to evaluate a decisional-aid intervention and measure the actual application of SDM during clinical encounters has a high potential to advance the translation path of implementing shared decision-making in clinical settings and provide evidence of the applicability of the guideline in general.Innovation and overall impactGiven the 2018 USPSTF updated guidelines recommending shared decision-making about PSA-based screening, the increased risk of prostate cancer mortality in Black men, the challenges of evidence-based decision-making due to the underrepresentation of Blacks in major randomized clinical trials, and implicit racial bias among primary care providers, the time is ripe for interventions to improve shared decision-making about prostate cancer screening in Black men. In this study, we address communication and knowledge gaps between Black men and their primary care providers. The intervention, if proven effective, can be readily scaled across primary care practices across the U.S. and may be adapted to other types of cancer where guidelines have included shared decision-making as well. Early detection of prostate cancer may decrease mortality and morbidity in the long term.