scholarly journals Factors Affecting Health Care Engagement of Patients With End-Stage Heart Failure: An Exploratory Survey Study

2019 ◽  
Vol 4 (2) ◽  
pp. 238146831986551
Author(s):  
Lisa Carey Lohmueller ◽  
Aakanksha Naik ◽  
Luke Breitfeller ◽  
Colleen K. McIlvennan ◽  
Manreet Kanwar ◽  
...  
Keyword(s):  
Heart Failure ◽  
Health Care ◽  
Decision Making ◽  
Decision Support ◽  
Information Seeking ◽  
Decision Support Tool ◽  
Treatment Decisions ◽  
Support Tool ◽  
End Stage Heart Failure ◽  
End Stage

Background. The decision to receive a permanent left ventricular assist device (LVAD) to treat end-stage heart failure (HF) involves understanding and weighing the risks and benefits of a highly invasive treatment. The goal of this study was to characterize end-stage HF patients across parameters that may affect their decision making and to inform the development of an LVAD decision support tool. Methods. A survey of 35 end-stage HF patients at an LVAD implant hospital was performed to characterize their information-seeking habits, interaction with physicians, technology use, numeracy, and concerns about their health. Survey responses were analyzed using descriptive statistics, grounded theory method, and Bayesian network learning. Results. Most patients indicated an interest in using some type of decision support tool (roadmap of health progression: 46%, n = 16; personal prognosis: 51%, n = 18; short videos of patients telling stories of their experiences with an LVAD: 57%, n = 20). Information patients desired in a hypothetical decision support tool fell into the following topics: prognoses for health outcomes, technical information seeking, expressing emotions, and treatment decisions. Desire for understanding their condition was closely related to whether they had difficult interpreting their electronic medical record in the past. Conclusions. Most patients reported interest in engaging in their health care decision making and seeing their prognosis and electronic health record information. Patients who were less interested in their own treatment decisions were characterized by having less success understanding their health information. Design of a decision support tool for potential LVAD patients should consider a spectrum of health literacy and include information beyond the technical specifications of LVAD support.

scholarly journals Video decision support tool promoting values conversations in advanced care planning in cancer: protocol of a randomised controlled trial

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Natasha Michael ◽  
Clare O’Callaghan ◽  
Ekavi Georgousopoulou ◽  
Adelaide Melia ◽  
Merlina Sulistio ◽  
...  
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Cancer Patients ◽  
Personal Values ◽  
Decision Support Tool ◽  
Trial Registration ◽  
Randomised Control Trial ◽  
Care Planning ◽  
Advanced Directives ◽  
Support Tool

Abstract Background Views on advance care planning (ACP) has shifted from a focus solely on treatment decisions at the end-of-life and medically orientated advanced directives to encouraging conversations on personal values and life goals, patient-caregiver communication and decision making, and family preparation. This study will evaluate the potential utility of a video decision support tool (VDST) that models values-based ACP discussions between cancer patients and their nominated caregivers to enable patients and families to achieve shared-decisions when completing ACP’s. Methods This open-label, parallel-arm, phase II randomised control trial will recruit cancer patient-caregiver dyads across a large health network. Previously used written vignettes will be converted to video vignettes using the recommended methodology. Participants will be ≥18 years and be able to complete questionnaires. Dyads will be randomised in a 1:1 ratio to a usual care (UC) or VDST group. The VDST group will watch a video of several patient-caregiver dyads communicating personal values across different cancer trajectory stages and will receive verbal and written ACP information. The UC group will receive verbal and written ACP information. Patient and caregiver data will be collected individually via an anonymous questionnaire developed for the study, pre and post the UC and VDST intervention. Our primary outcome will be ACP completion rates. Secondarily, we will compare patient-caregiver (i) attitudes towards ACP, (ii) congruence in communication, and (iii) preparation for decision-making. Conclusion We need to continue to explore innovative ways to engage cancer patients in ACP. This study will be the first VDST study to attempt to integrate values-based conversations into an ACP intervention. This pilot study’s findings will assist with further refinement of the VDST and planning for a future multisite study. Trial registration Australian New Zealand Clinical Trials Registry No: ACTRN12620001035910. Registered 12 October 2020. Retrospectively registered.

Creation of a Community-Driven Decision Support Tool for Caregivers of Children With Developmental Concerns

2021 ◽  
pp. 1-11
Author(s):  
Dawn M. Magnusson ◽  
Irena Shwayder ◽  
Natalie J. Murphy ◽  
Lindsay Ollerenshaw ◽  
Michele Ebendick ◽  
...  
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Shared Decision Making ◽  
Service Use ◽  
Decision Support Tool ◽  
Cultural Humility ◽  
Shared Decision ◽  
Plain Language ◽  
Support Tool ◽  
Key Aspects

Purpose Despite increasing standardization of developmental screening and referral processes, significant early intervention service disparities exist. The aims of this article are to: (a) describe methods used to develop a decision support tool for caregivers of children with developmental concerns, (b) summarize key aspects of the tool, and (c) share preliminary results regarding the tool's acceptability and usability among key stakeholders. Method Content and design of the decision support tool was guided by a systematic process outlined by the International Patient Decision Aid Standards (IPDAS) Collaborative. Three focus group interviews were conducted with caregivers ( n = 7), early childhood professionals ( n = 28), and a mix of caregivers and professionals ( N = 20) to assess caregiver decisional needs. In accordance with the IPDAS, a prototype of the decision support tool was iteratively cocreated by a subset of caregivers ( n = 7) and early child health professionals ( n = 5). Results The decision support tool leverages images and plain language text to guide caregivers and professionals along key steps of the early identification to service use pathway. Participants identified four themes central to shared decision making: trust, cultural humility and respect, strength-based conversations, and information-sharing. End-users found the tool to be acceptable and useful. Conclusions The decision support tool described offers an individualized approach for exploring beliefs about child development and developmental delay, considering service options within the context of the family's values, priorities, and preferences, and outlining next steps. Additional research regarding the tool's effectiveness in optimizing shared decision-making and reducing service use disparities is warranted.

Multivariable Automatisierungsentscheidungen*/Multivariate automation decisions – A tool for cost-benefit assessments as a basis for decision-making

2019 ◽  
Vol 109 (03) ◽  
pp. 134-139
Author(s):  
P. Burggräf ◽  
J. Wagner ◽  
M. Dannapfel ◽  
K. Müller ◽  
B. Koke
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Environmental Conditions ◽  
Cost Benefit ◽  
Decision Support Tool ◽  
Decision Making Process ◽  
Support Tool ◽  
Cost And Benefit ◽  
Benefit Evaluation ◽  
Level Of Automation

Der wachsende Bedarf an Wandlungsfähigkeit führt zu einer höheren Frequenz in der Umplanung von Montagesystemen und erfordert eine kontinuierliche Überprüfung und Anpassung des Automatisierungsgrades. Um auch die komplexen Umgebungsbedingungen abzubilden, sollen nicht-monetäre Faktoren in den Entscheidungsprozess eingebunden werden. Um die Entscheidung zu unterstützen, stellt dieser Beitrag ein Tool zur Identifizierung und Bewertung von Automatisierungsszenarien mittels einer Nutzwert-Aufwand-Analyse vor.   The increasing need for adaptability in assembly leads to a higher planning frequency of the system and requires continuous checks and adaptations of the appropriate level of automation. To account for the complex environmental conditions, non-monetary factors are included in the decision-making process. This paper presents a decision support tool to identify and evaluate automation scenarios by means of cost and benefit evaluation.

Predictive data analytics for contract renewals: a decision support tool for managerial decision-making

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Serhat Simsek ◽  
Abdullah Albizri ◽  
Marina Johnson ◽  
Tyler Custis ◽  
Stephan Weikert
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Organizational Performance ◽  
Predictive Analytics ◽  
Design Science ◽  
Decision Support Tool ◽  
Managerial Decision ◽  
Managerial Decision Making ◽  
Content Type ◽  
Support Tool

PurposePredictive analytics and artificial intelligence are perceived as significant drivers to improve organizational performance and managerial decision-making. Hiring employees and contract renewals are instances of managerial decision-making problems that can incur high financial costs and long-term impacts on organizational performance. The primary goal of this study is to identify the Major League Baseball (MLB) free agents who are likely to receive a contract.Design/methodology/approachThis study used the design science research paradigm and the cognitive analytics management (CAM) theory to develop the research framework. A dataset on MLB's free agents between 2013 and 2017 was collected. A decision support tool was built using artificial neural networks.FindingsThere are clear links between a player's statistical performance and the decision of the player to sign a new offered contract. “Age,” “Wins above Replacement” and “the team on which a player last played” are the most significant factors in determining if a player signs a new contract.Originality/valueThis paper applied analytical modeling to personnel decision-making using the design science paradigm and guided by CAM as the kernel theory. The study employed machine learning techniques, producing a model that predicts the probability of free agents signing a new contract. Also, a web-based tool was developed to help decision-makers in baseball front offices so they can determine which available free agents to offer contracts.

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