Use Of Decision Support Tools Research Articles

Using decision support tools for treatment decision making about antidepressants in outpatient psychiatric consultations

ObjectiveTo examine the use of decision support tools in decision making about antidepressants during conversations between patients with major depressive disorder (MDD) and their psychiatrists. MethodsTheme-oriented discourse analysis of two psychiatric consultation groups: control (n = 17) and intervention (n = 16). In the control group, only a doctor’s conversation guide was used; in the intervention group, the conversation guide and a patient decision aid (PDA) were used. ResultsPsychiatrists mainly dominated conversations in both consultation groups. They were less likely to elicit patient treatment-related perspectives in the intervention group as they focused more on delivering the information than obtaining patient perspectives. However, using PDA in the intervention group slightly encouraged patients to participate in decisional talk. ConclusionThe decision support tools did promote SDM performance. Using the conversation guide in both consultation groups encouraged the elicitation of patient perspectives, which helped the psychiatrists in tailoring their recommendations of options based on patient preferences and concerns. Using the PDA in the intervention group created space for treatment discussion and fostered active collaboration in treatment decision making. Practice ImplicationsOur findings have implications for SDM communication skills training and critical reflection on SDM practice.

Current and potential use of animal disease data by stakeholders in the global south and north

What cannot be measured will not be managed. The Global Burden of Animal Diseases (GBADs) will generate information on animal disease burdens by species, production system, type and gender of farmer and consumer, geographical region, and time period. To understand the demand for burden of animal disease (BAD) data and how end-users might benefit from this, we reviewed the literature on animal diseases prioritisation processes (ADPP) and conducted a survey of BAD information users. The survey covered their current use of data and prioritizations as well as their needs for different, more, and better information. We identified representative (geography, sector, species) BAD experts from the authors’ networks and publicly available documents and e-mailed 1485 experts. Of 791 experts successfully contacted, 271 responded (34% response rate), and 185 complete and valid responses were obtained. Most respondents came from the public sector followed by academia/research, and most were affiliated to institutions in low- and middle-income countries (LMICs). Of the six ADPPs commonly featured in literature, only three were recognised by more than 40% of experts. An additional 23 ADPPs were used. Awareness of ADDPs varied significantly by respondents. Respondents ranked animal disease priorities. We used exploded logit to combine first, second and third disease priorities to better understand prioritzation and their determinants. Expert priorities differed significantly from priorities identified by the ADDPs, and also from the priorities stated veterinary services as reported in a survey for a World Organisation of Animal Health (WOAH) technical item. Respondents identified 15 different uses of BAD data. The most common use was presenting evidence (publications, official reports, followed by disease management, policy development and proposal writing). Few used disease data for prioritzation or resource allocation, fewer routinely used economic data for decision making, and less than half were aware of the use of decision support tools (DSTs). Nearly all respondents considered current BAD metrics inadequate, most considered animal health information insufficiently available and not evidence-based, and most expressed concerns that decision-making processes related to animal health lacked transparency and fairness. Cluster analysis suggested three clusters of BAD users and will inform DSTs to help them better meet their specific objectives. We conclude that there is a lack of satisfaction with current BAD information, and with existing ADDPs, contributing to sub-optimal decision making. Improved BAD data would have multiple uses by different stakeholders leading to better evidenced decisions and policies; moreover, clients will need support (including DSTs) to optimally use BAD information.

The EPA Ecosystem Services Tool Selection Portal.

The dynamics of an environmental decision-making context can be complicated. The use of decision support tools can help better facilitate restoring and maintaining ecosystems that provide environmental benefits (ecosystem services) to people. Although an ecosystem services assessment tool is designed for specific purposes, having access to a comprehensive suite of tools offers the user additional insight and resources to help in decision making. A range of approaches exist to connect ecosystem services to a given decision context ranging from less to more complex: using the best professional judgment; applying examples from other efforts; testing individual tool applications; and using a systematic, decision-tree approach to navigate among relevant tools and frameworks. The U.S. Environmental Protection Agency developed a decision-tree approach for a user to navigate the question of how to choose among a suite of ecosystem services assessment tools for three decision contexts: (1) ecological risk assessments; (2) cleanup of contaminated sites; (3) and generic structured decision-making processes. This tool selection navigator was developed with/for the intended user, including developing crosswalks between tool functionality and the user's language for what they require in a tool. To navigate the tool, the user first chooses one of three decision contexts. Second, the user selects among the different phases of the decision process. Third, the user selects among a few ecosystem-services related tasks relevant to the decision context chosen to identify potential tools. The tool uses simple language to navigate the decision pathways and provides the user with a suite of potential ES resources and tools for their given decision context.

Developing a General Population Screening Programme for Paediatric Type 1 Diabetes: Evidence from a Qualitative Study of the Perspectives and Attitudes of Parents

Introduction. With reliable tests and preventative treatments now available the United Kingdom has introduced a prototype population-based paediatric (ages 3–13) screening programme for type 1 diabetes (T1D). To aid its ethical and sustainable implementation this work explores parental views around the concept of this programme to determine how their involvement might be encouraged and supported. Research Design and Methods. Qualitative interviews were undertaken with 38 parents and the data were analysed using a purposely developed “Burden of Screening” framework, which presented the data within three domains describing the various elements of screening participation; pre-screening tasks designated to participants; factors influencing engagement with screening; and consequences of screening participation. Results. Regarding pre-screening tasks designated to participants, the importance of clear communication about the condition were apparent with parents expressing uncertainty of the benefits of screening against the potential anxiety engendered. In factors influencing their engagement with screening participants described their preference for less invasive testing techniques, the reassurance of structured support from healthcare professionals inherent within the programme, and the potential benefit of peer support. Regarding the consequences of screening participation parents described how a positive result might lead to overly protective behaviours, and anxiety from watching and waiting for the onset of symptomatic T1D. Conclusions. The benefits of T1D screening need to be clearly communicated to facilitate uptake. To this end the use of decision-support tools and better targeted educational materials should be explored. Post-testing, parents expressed preferences for peer support and access to psychological counselling.

Environmental Sustainability and AI in Radiology: A Double-Edged Sword.

According to the World Health Organization, climate change is the single biggest health threat facing humanity. The global health care system, including medical imaging, must manage the health effects of climate change while at the same time addressing the large amount of greenhouse gas (GHG) emissions generated in the delivery of care. Data centers and computational efforts are increasingly large contributors to GHG emissions in radiology. This is due to the explosive increase in big data and artificial intelligence (AI) applications that have resulted in large energy requirements for developing and deploying AI models. However, AI also has the potential to improve environmental sustainability in medical imaging. For example, use of AI can shorten MRI scan times with accelerated acquisition times, improve the scheduling efficiency of scanners, and optimize the use of decision-support tools to reduce low-value imaging. The purpose of this Radiology in Focus article is to discuss this duality at the intersection of environmental sustainability and AI in radiology. Further discussed are strategies and opportunities to decrease AI-related emissions and to leverage AI to improve sustainability in radiology, with a focus on health equity. Co-benefits of these strategies are explored, including lower cost and improved patient outcomes. Finally, knowledge gaps and areas for future research are highlighted.

Environmental Impact Decision Support Tools for Horticulture Farming: Evaluation of GHG Calculators

Horticulture is essential in the European agricultural sector and fundamental for many EU member states. Decision Support Systems and Tools can play an essential role in a shift to result-based agriculture and evidence-based decision making, improving productivity and environmental performance of farming practices. Investigations have been conducted on horticulture crop and farming impact on the environment and Green House Gas emissions. Despite the availability of a broad spectrum of tools, the use of Decision Support Tools in agriculture in Europe could be much higher. This research aims to analyze and recommend environmental impact Decision Support Tools for small and medium-sized companies to approach, measure, and evaluate horticulture farming. The research methodology includes a systematic review, bibliometric analysis, Multicriteria Decision analysis, and a case study analysis. During the research, multiple tools, including calculators used for an impact assessment of the agricultural sector, were selected. After applying eligibility criteria, an in-depth analysis of eight of the most suitable calculators was performed. The results of the Multicriteria Decision analysis show that the Solagro Carbon Calculator, The Farm Carbon Calculator, and the Cool Farm Tool are recommended in the first place as Green House Gas calculators for farmers.

Making technological innovations accessible to agricultural water management: Design of a low-cost wireless sensor network for drip irrigation monitoring in Tunisia

Unsustainable use of water resources and climate change will exacerbate the existing tensions surrounding resources, especially in the Mediterranean context. Despite investments in costly modern equipment, the performance of irrigated agriculture remains below expectations, notably because of the lack of available water data and the limited use of decision support tools. Although a variety of soil moisture sensors are available on the market, they are not widely used by the agricultural community because of their high cost and complexity. Access to information at an unprecedented level, via easily accessible low-cost and low-tech sensors, may be a major lever for improved identification of achievable gains in performance, and to guide actors toward efficient water management. To explore this hypothesis, an open source wireless soil moisture sensor, low-energy and economically and technically accessible, was developed. The tool was designed according to water users’ requirements and applied to a Tunisian irrigation scheme subject to major water use efficiency issues. The functioning of the wireless sensor network was tested on pilot plots over a growing season and compared with commercial sensors. A single parameter calibration can be performed in either the laboratory or the field. This low-cost sensor can be used for real-time irrigation monitoring and as a decision-making tool for water management.

Planning and licensing for marine aquaculture.

Marine aquaculture has the potential to increase its contribution to the global food system and provide valuable ecosystem services, but appropriate planning, licensing and regulation systems must be in place to enable sustainable development. At present, approaches vary considerably throughout the world, and several national and regional investigations have highlighted the need for reforms if marine aquaculture is to fulfil its potential. This article aims to map and evaluate the challenges of planning and licensing for growth of sustainable marine aquaculture. Despite the range of species, production systems and circumstances, this study found a number of common themes in the literature; complicated and fragmented approaches to planning and licensing, property rights and the licence to operate, competition for space and marine spatial planning, emerging species and diversifying marine aquaculture production (seaweed production, Integrated Multi-Trophic Aquaculture [IMTA], nutrient and carbon offsetting with aquaculture, offshore aquaculture and co-location and multiuse platforms), and the need to address knowledge gaps and use of decision-support tools. Planning and licensing can be highly complicated, so the UK is used as a case study to show more detailed examples that highlight the range of challenges and uncertainty that industry, regulators and policymakers face across interacting jurisdictions. There are many complexities, but this study shows that many countries have undergone, or are undergoing, similar challenges, suggesting that lessons can be learned by sharing knowledge and experiences, even across different species and production systems, rather than having a more insular focus.

Farm-level sustainability assessment in Mediterranean environments: Enhancing decision-making to improve business sustainability

In typical Mediterranean settings farming systems are key components and have an impact on the community structure and the environment in which they take place hence it is important to develop tools for Sustainability Assessment (SA). To enable positive change it is necessary to effectively allocate resources. Thus, it is important to understand how farmers’ decision-making impacts their farm’s sustainability performance and their awareness and use of Decision Support Tools (DST) for sustainable management. Twenty representative farms were selected from the National Farm Accountancy Data Network (FADN) for the regional unit of Argolida (Peloponnese, Greece). To investigate sustainability on these farms an indicator-based method, RISE 3.0, was employed to evaluate the current situation and semi-structured phone interviews were used to identify and analyse patterns and attitudes within the data regarding decision-making, sustainability performance and DST with the help of thematic analysis. The results demonstrate that the decision-making process was poorly informed and not always evidence-based while the concept of sustainability was not well understood by most of the farmers. The sustainability assessment illustrated the specific strengths and weaknesses of farm businesses in the area whereas the correlation of the RISE assessment with perceptions of farmers on decision-making and sustainability performance identified the challenges of moving towards more sustainable systems in typical Mediterranean environments.

Le cadre d'usage des outils d'aide à la décision

Cet article analyse la prise en charge par les coopératives de la critique environnementale au moyen d’outils numériques et la façon dont leur cadre d’usage se construit avec les technico-commerciaux (TC) et les agriculteurs. À partir du cas d’une coopérative, il montre comment son engagement dans une forme réduite d’agroécologie se traduit par le développement d’outils d’aide à la décision pour aider l’activité de prescription des TC. Cependant, les agriculteurs s’approprient ces OAD et cadrent également l’activité des TC. L’article décrit l’inertie des pratiques et du rapport entre ces deux acteurs dans la construction d’un cadre d’usage commun des OAD et de plusieurs variantes, et interroge le rôle d’intermédiation des TC dans sa stabilisation et ses déclinaisons.

Use of water decision-support tools for drought management

Climate is changing in ways that may significantly affect the provision of hydrologic ecosystem services in arid or semi-arid regions. To answer this challenge, there has been an effort to increase the adaptive capacity of organizations that manage water and the land-uses water supports. Governmental and non-governmental organizations (NGOs) managing large landscapes in the United States Northern Rockies region have access to a variety of water decision-support tools, such as indicators of precipitation and snowpack, which could increase their adaptive capacity to manage hydrologic ecosystem services under changing conditions. Yet little is known about the use of decision-support tools in this region and how tools could be improved. With the aim of informing future tool development and addressing information-use gaps, we conducted semi-structured interviews with representatives of federal and state agencies and NGOs to 1) identify which tools are being used, 2) describe tool-supported management actions across different types of organizations, and 3) determine “usability” criteria managers consider when adopting a climate tool. Through qualitative analysis, we found multiple types of tools being used, including processes and frameworks, data and models, and geospatial or web-based tools. We also identified several criteria that study participants used to assess whether or not to use a tool within their organization, including tool accuracy, robustness, extendibility, interpretability, capacity, and institutional fit. This study suggests that increased communication between tool developers and end-users, with a focus on tools’ relevance and ability to support management actions, could improve tools and increase the adaptive capacity of users. This research also points to the need for multiple lines of future research including how to improve the fit between organizational goals and water tools.

A Statewide EMS Viral Syndrome Pandemic Triage Protocol: 24 Hour Outcomes

Background: Early during the COVID-19 pandemic, Emergency Medical Services (EMS) systems encountered many challenges that prompted crisis-level strategies. Maryland’s statewide EMS system implemented the Viral Syndrome Pandemic Triage Protocol which contained a decision tool to help identify patients potentially safe for self-care at home. Objectives: This study assessed the effects of the Maryland Viral Syndrome Pandemic Triage Protocol and the safety of referring patients for self-care at home. Methods: This is a retrospective statewide analysis of EMS patients from March 19 thru September 4, 2020, who were not transported and had documentation of the Viral Syndrome Pandemic Triage Protocol’s decision support tool completed, as well as a random sample of 150 patients who were not transported and did not have documentation of the decision tool. Descriptive statistics were performed as well as a two-stage multivariable logistic regression model for the outcomes of ED presentation within 24 hours and subsequent hospitalization. Results: 301 EMS patients were documented as triaged to home using the protocol and outcomes data were available for 282 (94%). 41(14.5%) patients presented to an ED within 24 hours and 14 (5% of 282) required inpatient hospitalization. Nine (3.2%) patients were subsequently hospitalized with a diagnosis of COVID-19 illness. Of those patients for whom the decision tool was not documented, 35 (23%) had an ED visit within 24 hours and 15 (10%) were hospitalized (p = 0.075). Multivariate logistic regression model results (N = 432) suggest that those with documentation of triage protocol use had some advantage over those patients without documentation. The 95% CIs of the estimated effect of Triage/No Triage protocol documented were wide and crossed the 1.0 limit but overall, all effects Odds Ratios and Adjust Odds Ratios were consistently over 1.0 with the lowest value of 1.3 and the highest value of 2.1. Conclusion: Most patients (95%) who were triaged to self-care at home with home documented decision support tool use did not require hospitalization within 24 hours following EMS encounter and this appears to be safe. Future opportunity exists to incorporate such tools into comprehensive pandemic preparedness strategies along with appropriate follow up and quality improvement mechanisms.

Which Road to Recovery?: Factors Influencing Postacute Stroke Discharge Destinations: A Delphi Study.

The criteria for determining the level of postacute care for patients with stroke are variable and inconsistent. The purpose of this study was to identify key factors influencing the selection of postacute level of care for these patients. We used a collaborative 4-round Delphi process to achieve a refined list of factors influencing postacute level of care selection. Our Delphi panel of experts consisted of 32 panelists including physicians, physical therapists, occupational therapists, speech-language pathologists, nurses, stroke survivors, administrators, policy experts, and individuals associated with third-party insurance companies. In round 1, 207 factors were proposed, with subsequent discussion resulting in consolidation into 15 factors for consideration. In round 2, 15 factors were ranked with consensus on 10 factors; in round 3,10 factors were ranked with consensus on 9 factors. In round 4, the final round, 9 factors were rated with Likert scores ranging from 5 (most important) to 1(not important). The percentage of panelists who provided a rating of 4 or above were as follows: likelihood to benefit from an active rehabilitation program (97%), need for clinicians with specialized rehabilitation skills (94%), need for active and ongoing medical management and monitoring (84%), ability to tolerate an active rehabilitation program (74%), need for caregiver training to return to the community (48%), family/caregiver support (39%), likelihood to return to community/home (39%), ability to return to physical home environment (32%), and premorbid dementia (16%). This study provides an expert, consensus-based set of key factors to be considered when determining where stroke patients are discharged for postacute care. These factors may be useful in developing a decision support tool for use in clinical settings.

The CEP Crosswalk: A community energy planning tool for interdepartmental alignment and stakeholder engagement

Community Energy Planning is a still-maturing practice that has great potential to help achieve climate goals, stimulate economic development, and realize health and social benefits. Community Energy Plans (CEPs) in Canada often encounter barriers to implementation that can be mitigated through use of decision support tools (QUEST, 2015). Planning tools are needed to help municipal staff improve the quality and quantity of stakeholder engagement during the CEP process, set priorities, and increase inter-departmental collaboration on climate and energy goals. In this paper, we present the Crosswalk Document, tool designed to support the Community Energy Planning process by identifying “points of contact” between the guiding policy documents of a given jurisdiction. We discuss the method used to construct the Crosswalk, and share insights from Community Energy practitioners at the Halifax Regional Municipality and the Town of Oakville who used it to the benefit their Community Energy Planning processes.
  
  
  
  

The impact of negotiators’ motivation on the use of decision support tools in preparation for negotiations

AbstractThorough preparation for a negotiation is considered critical for the achievement of successful relational and substantive results. Careful specification of preferences and determining the negotiation offer scoring systems is one of the most important preparation activities. To facilitate this process, preference elicitation aids have been designed and implemented in decision and negotiation support systems (NSSs). This paper shows that negotiators’ motivation affects the use of simple elicitation aid and elicited preferences. We identify three types of motivations: epistemic, social, identity, and assign the factors that describe them. Then, using the dataset from electronic negotiation experiments, we apply logistic regression to identify those motivations that allow distinguishing negotiators who make errors in the determination of the scoring systems from those who do not make them. The key result allows us to identify relational‐ and learning‐oriented goals of the identity motivation as having a significant and direct impact on the negotiators’ classification. Accommodating and competing approaches of social motivation impact agents' accuracy with the differences observed for gender. Surprisingly, epistemic motivation represented by rationality and experientiality factors does not affect users’ accuracy in the prenegotiation phase. The results obtained can be used to design decision support tools adjusted to the motivational profiles of the NSS users.

A framework to assess impacts of path dependence on urban planning outcomes, induced through the use of decision-support tools

Urban planning stakeholders can use decision-support tools (DST) to foster transformation towards sustainable urban morphologies. This paper proposes an analytical framework to support urban planning practitioners in assessing how the use of DST might impact planning outcomes due to path dependence. We identify five key dimensions of path dependence in a spatial socio-technical system as analytical framework to assess the influence of DST on planning outcomes. Potential impacts on urban planning outcomes are analysed by applying the proposed framework to a particular spatial socio-technical system, namely New Zealand's use of DST to support urban planning decision-making towards sustainable urban morphologies. The assessment framework and comparative case study analysis illustrate how the interaction between planning culture and some DST features can influence decisions pertaining to urban morphologies and raise awareness about DST-induced path dependence.

A novel Neutrosophic-based machine learning approach for maintenance prioritization in healthcare facilities

The development of decision support tools for use in the maintenance management and renewal prioritization of healthcare facility assets is considered a highly challenging task due to the multiplicity of uncertainties and subjectivity levels available in such a decision-making process. Accordingly, this study utilizes a combination of Neutrosophic logic, Analytic Network Process (ANP) and Multi-Attribute Utility Theory (MAUT) to reduce the subjectivity pertaining to expert-driven decisions and produce a reliable ranking of hospital building assets based on their variable criticality levels and performance deficiencies. This is further integrated with the novel use of machine learning algorithms in this field, namely: Decision Trees, K-Nearest Neighbors and Naïve Bayes to automate the priority setting process and make it reproducible diminishing the need for additional expert judgments. The developed model was applied to Canadian healthcare facilities, and its corresponding predictive performance was validated by means of comparison against a previously established model, and its excelling capability was clearly demonstrated. Accordingly, the developed integrated framework is expected to aid in creating a consistent, unbiased and automated prioritization scheme for hospital asset renewals, which in turn is expected to contribute to an efficient, informed and sound resources allocation process.

Simulation-based evaluation of operating room management policies

BackgroundSince operating rooms are a major bottleneck resource and an important revenue driver in hospitals, it is important to use these resources efficiently. Studies estimate that between 60 and 70% of hospital admissions are due to surgeries. Furthermore, staffing cannot be changed daily to respond to changing demands. The resulting high complexity in operating room management necessitates perpetual process evaluation and the use of decision support tools. In this study, we evaluate several management policies and their consequences for the operating theater of the University Hospital Augsburg.MethodsBased on a data set with 12,946 surgeries, we evaluate management policies such as parallel induction of anesthesia with varying levels of staff support, the use of a dedicated emergency room, extending operating room hours reserved as buffer capacity, and different elective patient sequencing policies. We develop a detailed simulation model that serves to capture the process flow in the entire operating theater: scheduling surgeries from a dynamically managed waiting list, handling various types of schedule disruptions, rescheduling and prioritizing postponed and deferred surgeries, and reallocating operating room capacity. The system performance is measured by indicators such as patient waiting time, idle time, staff overtime, and the number of deferred surgeries.ResultsWe identify significant trade-offs between expected waiting times for different patient urgency categories when operating rooms are opened longer to serve as end-of-day buffers. The introduction of parallel induction of anesthesia allows for additional patients to be scheduled and operated on during regular hours. However, this comes with a higher number of expected deferrals, which can be partially mitigated by employing additional anesthesia teams. Changes to the sequencing of elective patients according to their expected surgery duration cause expectable outcomes for a multitude of performance indicators.ConclusionsOur simulation-based approach allows operating theater managers to test a multitude of potential changes in operating room management without disrupting the ongoing workflow. The close collaboration between management and researchers in the design of the simulation framework and the data analysis has yielded immediate benefits for the scheduling policies and data collection efforts at our practice partner.

Suggestions for Developing Tools to Improve the Effectiveness of Management in the Context of Epidemics

The article is devoted to the consideration of methods for modeling epidemics in relation to COVID-19 and substantiation of ways to improve the efficiency of management decisions, taking into account the predicted consequences. The paper provides an overview of modeling methods for predicting and assessing the consequences of the epidemiological situation. The scientific novelty of the work lies in the use of decision support tools for the operational assessment of the situation and forecast of its development. For the task at hand, it is proposed to use a multi-agent approach to simulation.

Improving early detection of infection in nursing home residents in South Africa

This paper sets out key challenges related to detection and management of infection in nursing home residents, and then explores the situation in South Africa, and use of decision support tools as a mechanism to improve this area of practice.In line with global trends, concerns have been raised about the rapidly increasing aging population in South Africa and the ability of the current healthcare system to keep pace with patient demand, particularly nursing home residents. Nursing home residents, who often exhibit atypical signs and symptoms, are at increased risk of infection and unplanned admissions, which account for 65% of all bed days, and cost the US healthcare economy more than a trillion dollars a year. Evidence suggests that the current workforce in South Africa receive limited training in this area and are largely unprepared to meet the demands of the aging population. Building the capacity and skills of the workforce in South Africa is one approach that could help to improve the early detection of infection and assist the nursing home workforce to provide more effective and timely care, particularly during the current COVID-19 pandemic.Decision support tools, such as the Early Detection of Infection Scale, can help ensure consistency and ensure more timely treatment, minimising unplanned admissions and healthcare expenditure. However, the potential benefits or indeed how easily this could be integrated in to nursing homes in South Africa is unknown. An important first step, as in other parts of the world, is therefore to explore views and opinions of how infections are detected and managed in practice by nurses, care workers and managers in nursing homes.