Decision aid Dotaz Zobrazit nápovědu
Complex decision making tasks of different natures, e.g. economics, safety engineering, ecology and biology, are based on vague, sparse, partially inconsistent and subjective knowledge. Moreover, decision making economists / engineers are usually not willing to invest too much time into study of complex formal theories. They require such decisions which can be (re)checked by human like common sense reasoning. One important problem related to realistic decision making tasks are incomplete data sets required by the chosen decision making algorithm. This paper presents a relatively simple algorithm how some missing III (input information items) can be generated using mainly decision tree topologies and integrated into incomplete data sets. The algorithm is based on an easy to understand heuristics, e.g. a longer decision tree sub-path is less probable. This heuristic can solve decision problems under total ignorance, i.e. the decision tree topology is the only information available. But in a practice, isolated information items e.g. some vaguely known probabilities (e.g. fuzzy probabilities) are usually available. It means that a realistic problem is analysed under partial ignorance. The proposed algorithm reconciles topology related heuristics and additional fuzzy sets using fuzzy linear programming. The case study, represented by a tree with six lotteries and one fuzzy probability, is presented in details.
CONTEXT: Although screening recommendations for prostate cancer using prostate-specific antigen testing often include shared decision making, the effect of patient decision aids on patients' intention and uptake is unclear. This study aimed to review the effect of decision aids on men's screening intention, screening utilization, and the congruence between intentions and uptake. EVIDENCE ACQUISITION: Data sources were searched through April 6, 2018, and included MEDLINE, Scopus, CENTRAL, CT.gov, Cochrane report, PsycARTICLES, PsycINFO, and reference lists. This study included RCTs and observational studies of decision aids that measured prostate screening intention or behavior. The analysis was completed in April 2018. EVIDENCE SYNTHESIS: Eighteen studies (13 RCTs, four before-after studies, and one non-RCT) reported data on screening intention for ≅8,400 men and screening uptake for 2,385 men. Compared with usual care, the use of decision aids in any format results in fewer men (aged ≥40 years) planning to undergo prostate-specific antigen testing (risk ratio=0.88, 95% CI=0.81, 0.95, p=0.006, I2=66%, p<0.001, n=8). Many men did not follow their screening intentions during the first year after using a decision aid; however, most men who were planning to undergo screening did so (probability that men who wanted to be screened would receive screening was 95%). CONCLUSIONS: Integration of decision aids in clinical practice may result in a decrease in the number of men who elect prostate-specific antigen testing, which may in turn reduce screening uptake. To ensure high congruence between intention and screening utilization, providers should not delay the shared decision-making discussion after patients use a decision aid.
- MeSH
- časná detekce nádoru * MeSH
- kontrolovaná studie before-after MeSH
- lidé středního věku MeSH
- lidé MeSH
- metody pro podporu rozhodování * MeSH
- nádory prostaty diagnóza MeSH
- prostatický specifický antigen MeSH
- randomizované kontrolované studie jako téma MeSH
- rozhodování MeSH
- senioři MeSH
- úmysl MeSH
- zapojení pacienta MeSH
- Check Tag
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- senioři MeSH
- Publikační typ
- časopisecké články MeSH
- metaanalýza MeSH
- práce podpořená grantem MeSH
- Research Support, N.I.H., Extramural MeSH
- systematický přehled MeSH
- Názvy látek
- prostatický specifický antigen MeSH
OBJECTIVE: Shared decision making (SDM) tools can help implement guideline recommendations for patients with atrial fibrillation (AF) considering stroke prevention strategies. We sought to characterize all available SDM tools for this purpose and examine their quality and clinical impact. METHODS: We searched through multiple bibliographic databases, social media, and an SDM tool repository from inception to May 2020 and contacted authors of identified SDM tools. Eligible tools had to offer information about warfarin and ≥1 direct oral anticoagulant. We extracted tool characteristics, assessed their adherence to the International Patient Decision Aids Standards, and obtained information about their efficacy in promoting SDM. RESULTS: We found 14 SDM tools. Most tools provided up-to-date information about the options, but very few included practical considerations (e.g., out-of-pocket cost). Five of these SDM tools, all used by patients prior to the encounter, were tested in trials at high risk of bias and were found to produce small improvements in patient knowledge and reductions in decisional conflict. CONCLUSION: Several SDM tools for stroke prevention in AF are available, but whether they promote high-quality SDM is yet to be known. The implementation of guidelines for SDM in this context requires user-centered development and evaluation of SDM tools that can effectively promote high-quality SDM and improve stroke prevention in patients with AF.
- Klíčová slova
- anticoagulation, atrial fibrillation, cardiovascular prevention, decision aids, shared decision making,
- MeSH
- cévní mozková příhoda * prevence a kontrola MeSH
- fibrilace síní * komplikace MeSH
- lidé MeSH
- metody pro podporu rozhodování MeSH
- rozhodování MeSH
- sdílené rozhodování MeSH
- zapojení pacienta MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- systematický přehled MeSH
In multiple-criteria decision making/aiding/analysis (MCDM/MCDA) weights of criteria constitute a crucial input for finding an optimal solution (alternative). A large number of methods were proposed for criteria weights derivation including direct ranking, point allocation, pairwise comparisons, entropy method, standard deviation method, and so on. However, the problem of correct criteria weights setting persists, especially when the number of criteria is relatively high. The aim of this paper is to approach the problem of determining criteria weights from a different perspective: we examine what weights' values have to be for a given alternative to be ranked the best. We consider a space of all feasible weights from which a large number of weights in the form of n-tuples is drawn randomly via Monte Carlo method. Then, we use predefined dominance relations for comparison and ranking of alternatives, which are based on the set of generated cases. Further on, we provide the estimates for a sample size so the results could be considered robust enough. At last, but not least, we introduce the concept of central weights and the measure of its robustness (stability) as well as the concept of alternatives' multi-dominance, and show their application to a real-world problem of the selection of the best wind turbine.
Interpretation of cardiotocogram (CTG) is a difficult task since its evaluation is complicated by a great inter- and intra-individual variability. Previous studies have predominantly analyzed clinicians' agreement on CTG evaluation based on quantitative measures (e.g. kappa coefficient) that do not offer any insight into clinical decision making. In this paper we aim to examine the agreement on evaluation in detail and provide data-driven analysis of clinical evaluation. For this study, nine obstetricians provided clinical evaluation of 634 CTG recordings (each ca. 60min long). We studied the agreement on evaluation and its dependence on the increasing number of clinicians involved in the final decision. We showed that despite of large number of clinicians the agreement on CTG evaluations is difficult to reach. The main reason is inherent inter- and intra-observer variability of CTG evaluation. Latent class model provides better and more natural way to aggregate the CTG evaluation than the majority voting especially for larger number of clinicians. Significant improvement was reached in particular for the pathological evaluation - giving a new insight into the process of CTG evaluation. Further, the analysis of latent class model revealed that clinicians unconsciously use four classes when evaluating CTG recordings, despite the fact that the clinical evaluation was based on FIGO guidelines where three classes are defined.
- Klíčová slova
- Biomedical informatics, Cardiotocography, Decision making, Fetal heart rate, Latent class analysis, Observer variation,
- MeSH
- kardiotokografie statistika a číselné údaje MeSH
- lidé MeSH
- metody pro podporu rozhodování * MeSH
- odchylka pozorovatele MeSH
- porodnictví statistika a číselné údaje MeSH
- reprodukovatelnost výsledků MeSH
- rozpoznávání automatizované metody MeSH
- senzitivita a specificita MeSH
- systémy pro podporu klinického rozhodování * MeSH
- umělá inteligence * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Our research aims to support decision-making regarding the financing of healthcare projects by structural funds with policies targeting reduction of the development gap among different regions and countries of the European Union as well as the achievement of economic and social cohesion. A fuzzy decision support model for the evaluation and selection of healthcare projects should rank the project applications for the selected region, accounting for the investor's wishes in the form of a regional coefficient in order to reduce the development gap between regions. On the one hand, our proposed model evaluates project applications based on selected criteria, which may be structured, weakly structured, or unstructured. On the other hand, it also incorporates information on the level of healthcare development in the region. The obtained ranking increases the degree of validity of the decision regarding the selection of projects for financing by investors, considering the level of development of the region where the project will be implemented. At the expense of European Union (EU) structural funds, a village, city, region, or state can receive funds for modernization and development of the healthcare sector and all related processes. To minimize risks, it is necessary to implement adequate support systems for decision-making in the assessment of project applications, as well as regional policy in the region where the project will be implemented. The primary goal of this study was to develop a complex fuzzy decision support model for the evaluation and selection of projects in the field of healthcare with the aim of reducing the development gap between regions. Based on the above description, we formed the following scientific hypothesis for this research: if the project selected for financing can successfully achieve its stated goals and increase the level of development of its region, it should be evaluated positively. This evaluation can be obtained using a complex fuzzy model constructed to account for the region's level of development in terms of the availability and quality of healthcare services in the region where the project will be implemented.
Multi-criteria decision-making (MCDM) can be formally implemented by various methods. This study compares suitability of four selected MCDM methods, namely WPM, TOPSIS, VIKOR, and PROMETHEE, for future applications in agent-based computational economic (ACE) models of larger scale (i.e., over 10 000 agents in one geographical region). These four MCDM methods were selected according to their appropriateness for computational processing in ACE applications. Tests of the selected methods were conducted on four hardware configurations. For each method, 100 tests were performed, which represented one testing iteration. With four testing iterations conducted on each hardware setting and separated testing of all configurations with the-server parameter de/activated, altogether, 12800 data points were collected and consequently analyzed. An illustrational decision-making scenario was used which allows the mutual comparison of all of the selected decision making methods. Our test results suggest that although all methods are convenient and can be used in practice, the VIKOR method accomplished the tests with the best results and thus can be recommended as the most suitable for simulations of large-scale agent-based models.
- MeSH
- ekonomické modely MeSH
- lidé MeSH
- metody pro podporu rozhodování MeSH
- rozhodování * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
This article briefly describes the development of the I-COP tool, which is designed to promote education and decision making of clinical oncologists. It is based on real data from medical facilities, which are processed, stored in database, analyzed and finally displayed in an interactive software application. Used data sources are shortly described in individual sections together with the functionality of developed tools. The final goal of this project is to provide support for work and education within each involved partner center. Clinical oncologists are therefore supposed to be the authors and users at the same time.
- MeSH
- algoritmy MeSH
- data mining metody MeSH
- elektronické zdravotní záznamy * MeSH
- lidé MeSH
- metody pro podporu rozhodování MeSH
- nádory diagnóza terapie MeSH
- navrhování softwaru MeSH
- registrace * MeSH
- software * MeSH
- systémy pro podporu klinického rozhodování * MeSH
- zdravotní záznamy osobní * MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Geografické názvy
- Česká republika MeSH
Various research endeavours are designed to identify ecosystem services, assess their spatial distribution, and prioritize them in a given forest landscape. The Turkish State Forest Organization has introduced an ecosystem-based multiple-use forest management philosophy since 2008, which emphasizes the need for identifying and allocating ecosystem services to each forest planning unit. This paper aims to investigate the use of Multiple Criteria Decision Analysis (MCDA) techniques and explores their effectiveness and suitability in identifying and allocating ecosystem services to forest units, considering scientific suitability, stakeholder engagement and the sustainability concept in the context of ecosystem-based forest management decision-making processes in a case study area of Turkey. We propose a framework that entails an iterative process comprising various stages, starting from identifying ecosystem services (ES) to allocating them to forest stands with a participatory approach. We employed the Analytical Hierarchy Process (AHP) and the Delphi method to determine stakeholder preferences and allocate ecosystem services to forest stands. This was achieved through an equation newly developed using scientific suitability, stakeholder preferences, and the sustainability concept. The landscape percentage allocated primarily to ES was as follows: water regulation (55.44%), soil protection (16.47%), biodiversity conservation (14.03%), wood production (13.08%), and aesthetic-recreation (0.84%). Notably, no allocations were made for national defence and climate regulation services. In conclusion, the stratification of Posof forests into zones was efficiently achieved a priori, considering both scientific-technical and socio-cultural criteria through MCDA techniques based on stakeholder preferences. This study streamlines the decision-making process involved in spatially allocating ecosystem services and provides crucial information instrumental in determining management objectives and optimal forest activities.
- Klíčová slova
- Ecosystem services, Forest management planning, Multi-criteria decision making approach, Spatial allocation,
- MeSH
- biodiverzita MeSH
- ekosystém * MeSH
- lesnictví * metody MeSH
- lesy * MeSH
- metody pro podporu rozhodování * MeSH
- rozhodování MeSH
- účast zainteresovaných stran MeSH
- zachování přírodních zdrojů * metody MeSH
- Publikační typ
- časopisecké články MeSH
- Geografické názvy
- Turecko MeSH
BACKGROUND: Positive findings on early detection and early intervention services have been consistently reported from many different countries. The aim of this study, conducted within the European Brain Council project "The Value of Treatment", was to estimate costs and the potential cost- savings associated with adopting these services within the context of the Czech mental health care reform. METHODS: Czech epidemiological data, probabilities derived from meta-analyses, and data on costs of mental health services in the Czech Republic were used to populate a decision analytical model. From the health care and societal perspectives, costs associated with health care services and productivity lost were taken into account. One-way sensitivity analyses were conducted to explore the uncertainty around the key parameters. RESULTS: It was estimated that annual costs associated with care as usual for people with the first episode of psychosis were as high as 46 million Euro in the Czech Republic 2016. These annual costs could be reduced by 25% if ED services were adopted, 33% if EI services were adopted, and 40% if both, ED and EI services, were adopted in the country. Cost-savings would be generated due to decreased hospitalisations and better employment outcomes in people with psychoses. CONCLUSIONS: Adopting early detection and early intervention services in mental health systems based on psychiatric hospitals and with limited access to acute and community care could generate considerable cost- savings. Although the results of this modelling study needs to be taken with caution, early detection and early intervention services are recommended for multi-centre pilot testing accompanied by full economic evaluation in the region of Central and Eastern Europe.
- Klíčová slova
- Early detection, Early intervention, Health economics, Psychosis, Schizophrenia,
- MeSH
- analýza nákladů a výnosů MeSH
- časná diagnóza MeSH
- hospitalizace ekonomika MeSH
- lidé MeSH
- metody pro podporu rozhodování MeSH
- náklady na zdravotní péči * MeSH
- psychotické poruchy diagnóza MeSH
- schizofrenie diagnóza MeSH
- služby péče o duševní zdraví ekonomika MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Geografické názvy
- Česká republika MeSH
