Decision Aid Tool Research Articles

Abstract: One Third of Plastic and Surgical Patients Have Limited Health Literacy: A Systematic Review and Meta-Analysis

INTRODUCTION: Health literacy has been defined as the extent to which patients are able to understand and act upon health information.1 Limited or inadequate health literacy has been shown to have a negative impact on patient satisfaction, clinical outcomes, and risk of hospitalization.2,3 This complex concept is of high importance for surgeons as their patients have to comprehend the nature, risks and benefits of surgical procedures, adhere to strict perioperative rules, and make complex care decisions about interventions or lack thereof.4 The aim of this review was to evaluate the prevalence of reported inadequate health literacy levels and the measurement tools used in the plastic and surgical patient populations. METHODS: A systematic review and meta-analysis was conducted according to the Cochrane guidelines. Relevant studies reporting health literacy measurements in surgical patient populations were identified from MEDLINE and Embase published from inception until January 14th2017. Two-stage screening and data extraction were performed by two independent reviewers. Data on study design, sample size, patient population, health literacy measurement tool, and prevalence of inadequate health literacy were extracted and analyzed. RESULTS: A total of 934 abstracts were screened, 103 articles were reviewed and 57 met inclusion criteria. Five randomized controlled trials, 8 prospective cohorts, 36 cross-sectional studies were included including only 11 (19.0%) studies published before 2010. 18,894 surgical patients were included in these studies and the prevalence of inadequate health literacy was 32.8% (range 2.8–80.7%, 95%CI: 25.9–40.1). Fifteen (26.3%) studies did not present health literacy measurement results. Numerous health literacy measurement tools were used (16 validated, 6 non-validated). Only five studies pertained to the hand surgery and one to the plastic surgery literature. CONCLUSION: Our review demonstrates a high prevalence of limited health literacy within the plastic and overall surgical patient populations. While there is considerable variation in measurement tools currently being used, our review suggests a great need for patient-education and decision-aid tools for surgical patients with limited health literacy. Reference Citations: 1. Nielsen-Bohlman L, Institute of Medicine. Health Literacy: A Prescription to End Confusion. Washington, DC: The National Academies Press; 2004. 2. Berkman ND, Sheridan SL, Donahue KE, Halpern DJ, Viera A, Crotty K, et al. Health literacy interventions and outcomes: an updated systematic review. Evid Report Technology Assess. 2011;199:1–941. 3. Komenaka IK, Nodora JN, Machado L, Hsu CH, Klemens AE, Martinez ME, et al. Health literacy assessment and patient satisfaction in surgical practice. Surgery. 2014;155:374–383. 4. McCaffery KJ, Smith SK, Wolf M. The challenge of shared decision making among patients with lower literacy: a framework for research and development. Med Decis Making. 2010;30:35–44.

Evaluating airline service quality using a combined fuzzy decision-making approach

Developments in the airline industry in the last decade have been forcing airlines to evaluate the quality of their service performance with the goal of improving their competitive advantage. It has also become one of the most challenging tasks potentially influencing airlines' long-term success. This challenge calls for a systematic decision-aid tool that can not only handle the vagueness and conflicting nature of service quality evaluation criteria but also integrates the strengths of various multi-criteria decision-making (MCDM) methods in a fuzzy environment.This paper aims to evaluate airline service quality in Turkey, using a combined fuzzy decision-making approach, for the first time in the literature. For this purpose, it identifies sixteen airline service quality criteria under five dimensions. The paper then describes the fuzzy DEMATEL method to deal with the interactions among the evaluation criteria. In addition, it proposes a fuzzy ANP method to consider the interdependence and calculate the relative importance of each criterion. Finally, it introduces a fuzzy VIKOR method for evaluating and ranking the service quality performance of airlines in Turkey. The paper also implements a sensitivity analysis to validate the proposed solution methodology's usefulness and practicality by testing different parameters of index values.

Multicriteria decision aid tool for the operational management of an industry: a constructivist case

The objective of this work is to construct a performance evaluation model to provide support to a production director in the management of the productive operations of a furniture industry. In this sense, we sought through the Multicriteria Decision Aid Constructivist Methodology (i) to identify the factors considered important by the production director for evaluating the performance of productive operations, (ii) to measure each criterion of performance evaluation, (iii) to integrate the criteria to allow the evaluation of organizational performance at the tactical and strategic levels and (iv) to develop a process to manage the actions of productive operations improvement.As a research result we have a performance evaluation model for supporting the management of the productive operations. We conclude that the MCDA-C allowed for building the knowledge of the decision-maker on how to identify and measure the critical variables and manage the performance of the productive operations.

Development of tools to facilitate palliative and supportive care referral for patients with idiopathic pulmonary fibrosis

ObjectivesPalliative care is underused in non-malignant respiratory diseases, including interstitial lung diseases (ILDs). We investigated current practices around palliative and supportive care and explored the impact of a supportive care...

Optimization-Based Design of Departure and Arrival Routes in Terminal Maneuvering Area

The efficient design of departure and arrival routes in the airspace surrounding airports, called the terminal maneuvering area, is crucial for increasing the capacity of such areas, thus alleviating congestion around airports caused by worldwide air traffic growth. In this paper, an efficient method of designing departure and arrival routes in the terminal maneuvering area is proposed, taking into account the configuration of the airport and the nearby environment, as well as related operational constraints, such as obstacle avoidance and route separation. Each route is modeled in three dimensions, and it consists of two components: a curve in the horizontal plane, and a cone in the vertical plane. A branch-and-bound-based approach is developed, for which the branching strategies are tailored to how the obstacles are avoided. Routes are generated sequentially, and each route is initially built in isolation. If the route is found to be in conflict with previously generated routes, it is perturbed locally around the conflict zones. Numerical tests, performed on artificially generated problems and the terminal maneuvering area of Paris’s Charles de Gaulle Airport, demonstrate that the proposed method is efficient and could be embedded in a decision-aid tool for procedure design.

355 Evaluating service need for a patient decision aid tool (PtDA) for patients considering lung transplantation in a UK-based NHS cystic fibrosis service: an assessment of patients' and clinicians' perspectives

355 Evaluating service need for a patient decision aid tool (PtDA) for patients considering lung transplantation in a UK-based NHS cystic fibrosis service: an assessment of patients' and clinicians' perspectives

An integrated approach for the planning of dredging operations in estuaries

Ports are often located in naturally sheltered areas such as estuaries. The strong tidal currents that occur in many of these areas drive a dynamic morphodynamic regime, with the result that the approach channels to these ports are gradually infilled. Periodic dredging is therefore necessary to maintain the operativity of the port. A case in point is Ribadeo (NW Spain), an important port for the economy of the area. In this work, the sediment transport patterns of the estuary (Ria de Ribadeo) are investigated through high-resolution numerical modelling and field measurements covering a 4-year period. On this basis, a decision-aid tool is developed that enables to predict the time evolution of the approach channel and thus contributes to the planning of dredging operations and, more generally, the maintenance of adequate operativity levels in a cost-effective way.

Time-dependent green vehicle routing problem with stochastic vehicle speeds: An approximate dynamic programming algorithm

This paper addresses a Time Dependent Capacitated Vehicle Routing Problem with stochastic vehicle speeds and environmental concerns. The problem has been formulated as a Markovian Decision Process. As distinct from the traditional attempts on the problem, while estimating the amount of fuel consumption and emissions, the model takes time-dependency and stochasticity of the vehicle speeds into account. The Time Dependent Capacitated Vehicle Routing Problem is known to be NP-Hard for even deterministic settings. Incorporating uncertainty to the problem increases complexity, which renders classical optimization methods infeasible. Therefore, we propose an Approximate Dynamic Programming based heuristic as a decision aid tool for the problem. The proposed Markovian Decision Model and Approximate Dynamic Programming based heuristic are flexible in terms that more environmentally friendly solutions can be obtained by changing the objective function from cost minimization to emissions minimization. The added values of the proposed decision support tools have been shown through computational analyses on several instances. The computational analyses show that incorporating vehicle speed stochasticity into decision support models has potential to improve the performance of resulting routes in terms of travel duration, emissions and travel cost. In addition, the proposed heuristic provides promising results within relatively short computation times.

Applying modern portfolio theory for a dynamic energy portfolio allocation in electricity markets

In deregulated electricity markets, a Generation Company (Genco) has to optimally allocate their energy among different markets including spot, local and bilateral contract markets. Modern portfolio theory (MPT) allows a Genco to achieve their goal by maximizing their profit and decreasing their associated risk. Combining MPT with an adequate tool to forecast energy prices makes it possible for a Genco to vary the optimal allocation of their portfolio even on a daily basis. This paper proposes two MPT models, one applying the Mean Variance Criterion (MVC) and the other one the Conditional Value at Risk (CVaR). The MPT models are combined with a generalized autoregressive conditional heteroskedastic (GARCH) prediction technique for a Genco to optimally diversify their energy portfolio. The two models are applied to a real PJM electricity market showing not only their capabilities but also useful comparisons between them in order to help decision makers to use them as decision-aid tools.

EP-1061: Towards a validated Decision Aid Tool for advanced larynx cancer patients

EP-1061: Towards a validated Decision Aid Tool for advanced larynx cancer patients

Integration of smart grid mechanisms on microgrids energy modelling

Due to security reasons, when assessing long-term planning in isolated microgrids, it is crucial to consider, the system's short-term variability. In this way, the need to develop modelling and planning decision-aid tools for grid managers, towards an optimal integration of renewable energy in isolated microgrids, is emerging. These tools shall combine short-term variability with long-term planning, while addressing multiple smart grid integration challenges.The present work proposes the evolution of an economic dispatch model to an integrated modelling tool, adding planning features. These consist in the implementation and sizing of different renewable and storage energy systems, and the development of demand scenarios, as the introduction of electric vehicles, demand response strategies, and/or residential efficiency measures. Levelized cost of electricity, operation costs, CO2 emissions and renewable shares are quantified.Terceira Island in Azores, is adopted as case study to validate the model. Results show that this tool has a great potential for supporting planning decisions, obtaining valuable parameters to analyze the proposed strategies, as the storage suitability, need of renewable curtailment or cost increase due to electric vehicles deployment. The integrated features allow understanding whether a new technology, besides being technically feasible, is economically viable with respect to the existing system.

Supporting the multi-criteria decision aiding process: R and the MCDA package

Reaching a decision when multiple, possibly conflicting, criteria are taken into account is often a difficult task. This normally requires the intervention of an analyst to aid the decision maker in following a clear methodology with respect to the steps that need to be taken, as well as the use of different algorithms and software tools. Most of these tools focus on one or a small number of algorithms, some are difficult to adapt and interface with other tools, while only a few belong to dynamic communities of contributors allowing them to expand in use and functionality. In this paper, we address these issues by proposing to use the R statistical environment and the MCDA package of decision aiding algorithms and tools. This package is meant to provide a wide range of MCDA algorithms that may be used by an analyst to tailor a decision aiding process to their needs, while the choice of R takes advantage of the yet poorly explored opportunity to interface data analysis and decision aiding. We additionally demonstrate the use of this tool on a practical application following a well-defined decision aiding process.

Design and manufacturing of a single-phase induction motor: A decision aid tool approach

Design and manufacturing of a single-phase induction motor: A decision aid tool approach

Content validity testing of the ESAT©: A decision aid tool for performing endotracheal suction in children

Background and purposeEndotracheal tube suction performed in children can affect clinical stability. Previous research has identified clinical indicators used to perform endotracheal suction. These were used to develop the Endotracheal Suction Assessment Tool© (ESAT©). This study sought to evaluate the degree to which the ESAT© items as a whole constitute an operational definition of the construct used to determine whether a paediatric intensive care nurse should perform the endotracheal tube suction procedure. MethodsLynn's process for calculation of content validity and scale content validity index using a team of expert reviewers was adopted. Experts were drawn from paediatric intensive care units in Australia (n=6), United Kingdom (n=1), Switzerland (n=1) and Canada (n=1). These experts established the content validity index of the Endotracheal Suction Assessment Tool© using a minimum preset a-priori criterion agreement of 0.78 and a scale content validity index of 0.8. Scale content validity index was used to enhance the interpretability of the content validity data. ResultsAll 15 items achieved the preset a-priori agreement for apparent internal consistency. Minor adjustments were required to improve the clarity of four items. The content validity index ranged from 0.8 to 1.0 and scale content validity index ranged from 0.9 to 1.0 for all items. ConclusionItem and scale content validity indexes of the tool were established. Further psychometric testing for construct validity and stability over time is required to establish clinical utility of the tool and practice of novice paediatric intensive care nurses and other PIC health professionals.

A new modeling approach for the biobjective exact optimization of satellite payload configuration

AbstractCommunication satellites have the crucial role to forward signals to customers. They filter and amplify uplink signals coming from Earth stations to improve the signal quality before reaching customers. These operations are performed by the payload component of the satellite that embeds reconfigurable components (e.g., switches). These components route signals to appropriate signal processing components (e.g., amplifiers, filters) and lead amplified signals to the output antenna. In order to route the channels that compose signals, satellite engineers can remotely modify switch states. These are typically updated when one or more new channels must be connected or when failures occur. However, satellites embed always more switches to answer customer demands, which makes their reconfiguration time consuming and error prone without appropriate decision aid tools. Power transmission is a crucial objective to ensure a maximum quality of service at reasonable cost. This is why satellite operators aim at minimizing incoming power signals while guaranteeing a maximum factor of amplification at the output antenna. This problem is referred to as the “satellite payload power problem.” Previous works have outlined the difficulty to solve exactly large instances of this problem. This work proposes to improve the existing mathematical formulation of the switch network. We show that it can be modeled as a static network and switch states can be deduced after optimization, thus limiting the combinatorial explosion. Computational experiments on different sizes of realistic instances using the adaptive ε‐constraint method demonstrate the computational time gain with this new model and the possibility to solve larger instances.

Supply chain analytics for enhancing the maritime security

Seaports across the world can be a frequent target for illegal activities such as contraband, weapon smuggling, drug trafficking, human trafficking, piracy, and terrorist attacks. Despite the increasing risk of those illegal activities, many ports are not equipped to deal with unforeseen security breaches. Although the use of X-ray scanning technology for cargo inspection has been on the rise due to its effectiveness in detecting potential security breaches, it alone cannot protect the port and its surrounding areas from illegal activities. To maximise the full benefit of X-ray based cargo inspection through enhanced maritime logistics visibility, we propose supply chain analytics which can not only add business intelligence to the cargo inspection process, but also guide the port authority to make informed decisions regarding security protocols. This decision-aid tool is designed to improve port security and productivity by systematically gathering, storing, analysing, and updating big data related to cargo movement, port infrastructure, and ocean-going vessel traffic. This paper is one of the first to embed supply chain analytics within the maritime security system and gauge its usefulness for enhancing maritime security in global supply chain operations.

Primary Care Provider and Patient Perspectives on Lung Cancer Screening. A Qualitative Study.

The U.S. Preventive Services Task Force recommends annual low-dose computed tomography (LDCT) for lung cancer screening in high-risk individuals. Preventive healthcare is provided predominantly by primary care providers (PCPs). Successful implementation of a screening program requires acceptance and participation by both providers and patients, with available collaboration with pulmonologists. To identify perceptions of and perspectives on lung cancer screening and implementation among PCPs and eligible veteran patients at high risk for lung cancer. We conducted a qualitative study using grounded theory in which 28 veterans and 13 PCPs completed a questionnaire and participated in focus groups. Sessions were recorded, transcribed verbatim, and analyzed with NVivo 10 software. Counts and percentages were used to report questionnaire results. While 58% percent of providers were aware of lung cancer screening guidelines, many could not recall the exact patient eligibility criteria. Most patients were willing to undergo LDCT screening and identified smoking as a risk factor for lung cancer, but they did not recall their PCP explaining the reason for the testing. All providers assessed smoking behavior, but only 23% referred active smokers for formal cessation services. Patients volunteered information regarding their hurdles with smoking cessation while discussing risk factors for cancer. PCPs cited time constraints as a reason for lack of appropriate counseling and shared decision making. Both parties were willing to explore modalities and decision aid tools to improve shared decision making; however, while patients were interested in individual risk prediction, few PCPs believed statistical approaches to counseling would confuse patients. While patients and providers are receptive to LDCT screening, efforts are needed to improve guideline knowledge and adherence among providers. System-level interventions are necessary to facilitate time and resources for shared decision making and smoking cessation counseling and treatment. Further research is needed to identify optimal strategies for effective lung cancer screening in the community.

Applying computational intelligence methods for predicting the sales of newly published books in a real editorial business management environment

When a new book is launched the publisher faces the problem of how many books should be printed for delivery to bookstores; printing too many is the main issue, since it implies a loss of investment due to inventory excess, but printing too few will also have a negative economic impact. In this paper, we are tackling the problem of predicting total sales in order to print the right amount of books and doing so even before the book has reached the stores. A real dataset including the complete sales data for books published in Spain across several years has been used. We have conducted an analysis in three stages: an initial exploratory analysis, by means of data visualisation techniques; a feature selection process, using different techniques to find out what are the variables that have more impact on sales; and a regression or prediction stage, in which a set of machine learning methods has been applied to create forecasting models for book sales. The obtained models are able to predict sales from pre-publication data with remarkable accuracy, and can be visualised as simple decision trees. Thus, these can be used as decision-aid tools for publishers, which can provide a reliable guidance on the decision process of publishing a book. This is also shown in the paper by addressing four example cases of representative publishers, regarding their number of sales and the number of different books they sell.

'It made you think twice' - an interview study of women's perception of a web-based decision aid concerning screening and diagnostic testing for fetal anomalies.

BackgroundEnabling women to make informed decisions is a key objective in the guidelines governing prenatal screening and diagnostics. Despite efforts to provide information, research shows that women’s choice of prenatal screening is often not based on informed decisions. The aim of this study was to investigate pregnant women’s perceptions of the use of an interactive web-based DA, developed to initiate a process of reflection and deliberate decision-making concerning screening and testing for fetal anomalies.MethodsA qualitative study was applied and individual interviews were conducted. Seventeen pregnant women attending antenatal healthcare in Uppsala County, Sweden, who had access to the decision aid were interviewed. Eleven opted to use the decision aid and six did not. Data were analysed by systematic text condensation.ResultsWomen appreciated the decision aid, as it was easily accessible; moreover, they emphasised the importance of a reliable source. It helped them to clarify their own standpoints and engaged their partner in the decision-making process. Women described the decision aid as enhancing their awareness that participating in prenatal screening and diagnostics was a conscious choice. Those who chose not to use the web-based decision aid when offered reported that they already had sufficient knowledge.ConclusionsThe decision aid was able to initiate a process of deliberate decision-making in pregnant women as a result of their interaction with the tool. Access to a web-based decision aid tool can be valuable to expectant parents in making quality decisions regarding screening for fetal anomalies.

Determining the Distribution of Coast Guard Vessels

A typical coast guard has complex responsibilities, subject to its multiple missions in maritime jurisdiction regions. These maritime jurisdiction regions can be partitioned into responsibility areas, and each type of coast guard vessel has a set of attributes for each responsibility area. The distribution of coast guard assets deployed in their respective areas of responsibility should be linked to the types of events occurring in these areas. The objective of this study is to determine the appropriate distribution of coast guard assets in various maritime zones; we do this by evaluating models that assign coast guard surface vessel types to missions in these maritime zones. We use the analytic network process model to compare various vessel types and determine the task-type weights for each vessel type. Weighted goal programming allows us to combine data, including the weights we derive from the use of other decision-aid tools. Our objective is to determine the best compromise solution for distributing coast guard assets into four main responsibility zones. The Turkish Coast Guard implemented the model in 2014, and decided to use it once a year prior to executing the main process in which it allocates coast guard assets.