Potato cyst nematodes (PCN) are in the Northern Netherlands and the Weser-Ems Region in Germany a major issue for farmers. The yearly average damage by PCN is about 100 Euros/hectare for farmers. Infestations of potato cyst nematodes can be controlled in a sustainable way by proper potato variety selection. Potato varieties vary in the degree of tolerance and resistance to PCN. However, this knowledge is used by only a small fraction of the farmers. The AGROBIOKON project, which is funded by the INTERREG EDR-region, the Landwirtschaftskammer Niedersachsen and the Dutch farmers association, have developed a decision support system for potato variety selection based upon population dynamic models for PCN: OPTIRas. The scientific principles and the model behind the decision support system will be presented. The model will be applied to PCN field experiments in the Weser-Ems region. Experience of using this decision support system in farmer study groups in the Netherlands and Germany will be shared.
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ABSTRACT Purpose: Polypharmacy is a known risk factor for potentially inappropriate prescribing. Recently there is an increasing interest in clinical decision support systems (CDSS) to improve prescribing. The objective of this study was to evaluate the impact of a CDSS, with the START-STOPP criteria as main content in the setting of a geriatric ward. Endpoints were 1) appropriateness of prescribing and 2) acceptance rate of recommendations. Methods: This prospective study comparing the use of a CDSS with usual care involved patients admitted to geriatric wards in two teaching hospitals in the Netherlands. Patients were included from January to May 2017. The medications of 64 patients in the first six weeks was assessed according to the current standard, whereas the medications of 61 patients in the second six weeks were also assessed by using a CDSS. Medication appropriateness was assessed with the Medication Appropriateness Index (MAI). Results: The medications of 125 patients (median age 83 years) were reviewed. In both the usual care group and the intervention group MAI scores decreased significantly from admission to discharge (within group analyses, p<0.001). This effect was significantly larger in the intervention group (p<0.05). MAI scores at discharge in the usual care group and the intervention group were respectively 9.95±6.70 and 7.26±5.07. The CDSS generated 193 recommendations, of which 71 concerned START criteria, 45 STOPP criteria, and 77 potential interactions. Overall, 31.6% of the recommendations were accepted. Conclusion: This study shows that a CDSS to improve prescribing has additional value in the setting of a geriatric ward. Almost one third of the software-generated recommendations were interpreted as clinically relevant and accepted, on average one per patient.
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During the past two decades the implementation and adoption of information technology has rapidly increased. As a consequence the way businesses operate has changed dramatically. For example, the amount of data has grown exponentially. Companies are looking for ways to use this data to add value to their business. This has implications for the manner in which (financial) governance needs to be organized. The main purpose of this study is to obtain insight in the changing role of controllers in order to add value to the business by means of data analytics. To answer the research question a literature study was performed to establish a theoretical foundation concerning data analytics and its potential use. Second, nineteen interviews were conducted with controllers, data scientists and academics in the financial domain. Thirdly, a focus group with experts was organized in which additional data were gathered. Based on the literature study and the participants responses it is clear that the challenge of the data explosion consist of converting data into information, knowledge and meaningful insights to support decision-making processes. Performing data analyses enables the controller to support rational decision making to complement the intuitive decision making by (senior) management. In this way, the controller has the opportunity to be in the lead of the information provision within an organization. However, controllers need to have more advanced data science and statistic competences to be able to provide management with effective analysis. Specifically, we found that an important skill regarding statistics is the visualization and communication of statistical analysis. This is needed for controllers in order to grow in their role as business partner..
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In this thesis several studies are presented that have targeted decision making about case management plans in probation. In a case management plan probation officers describe the goals and interventions that should help offenders stop reoffending, and the specific measures necessary to reduce acute risks of recidivism and harm. Such a plan is embedded in a judicial framework, a sanction or advice about the sanction in which these interventions and measures should be executed. The topic of this thesis is the use of structured decision support, and the question is if this can improve decision making about case management plans in probation and subsequently improve the effectiveness of offender supervision. In this chapter we first sketch why structured decision making was introduced in the Dutch probation services. Next we describe the instrument for risk and needs assessment as well as the procedure to develop case management plans that are used by the Dutch probation services and that are investigated in this thesis. Then we describe the setting of the studies and the research questions, and we conclude with an overview of this thesis.
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A Nursing Process-Clinical Decision Support System (NP-CDSS) Standard with 25 criteria to guide future developments of Nursing Process-Clinical Decision Support Systems was developed. The NP-CDSS Standards' content validity was established in qualitative interviews yielding fourteen categories that demonstrate international expert consensus. All experts judged the Advanced Nursing Process being the centerpiece for Nursing Process-Clinical Decision Support System that should suggest research-based, pre-defined nursing diagnoses and correct linkages between diagnoses, evidence-based interventions and patient outcomes.
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Artificial Intelligence systems are more and more being introduced into first response; however, this introduction needs to be done responsibly. While generic claims on what this entails already exist, more details are required to understand the exact nature of responsible application of AI within the first response domain. The context in which AI systems are applied largely determines the ethical, legal, and societal impact and how to deal with this impact responsibly. For that reason, we empirically investigate relevant human values that are affected by the introduction of a specific AI-based Decision Aid (AIDA), a decision support system under development for Fire Services in the Netherlands. We held 10 expert group sessions and discussed the impact of AIDA on different stakeholders. This paper presents the design and implementation of the study and, as we are still in process of analyzing the sessions in detail, summarizes preliminary insights and steps forward.
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Mobile Rapid DNA technology is close to being incorporated into crime scene investigations, with the potential to identify a perpetrator within hours. However, the use of these techniques entails the risk of losing the sample and potential evidence, because the device not only consumes the inserted sample, it is also is less sensitive than traditional technologies used in forensic laboratories. Scene of Crime Officers (SoCOs) therefore will face a ‘time/success rate trade-off’ issue when making a decision to apply this technology.In this study we designed and experimentally tested a Decision Support System (DSS) for the use of Rapid DNA technologies based on Rational Decision Theory (RDT). In a vignette study, where SoCOs had to decide on the use of a Rapid DNA analysis device, participating SoCOs were assigned to either the control group (making decisions under standard conditions), the Success Rate (SR) group (making decisions with additional information on DNA success rates of traces), or the DSS group (making decisions supported by introduction to RDT, including information on DNA success rates of traces).This study provides positive evidence that a systematic approach for decision-making on using Rapid DNA analysis assists SoCOs in the decision to use the rapid device. The results demonstrated that participants using a DSS made different and more transparent decisions on the use of Rapid DNA analysis when different case characteristics were explicitly considered. In the DSS group the decision to apply Rapid DNA analysis was influenced by the factors “time pressure” and “trace characteristics” like DNA success rates. In the SR group, the decisions depended solely on the trace characteristics and in the control group the decisions did not show any systematic differences on crime type or trace characteristic.Guiding complex decisions on the use of Rapid DNA analyses with a DSS could be an important step towards the use of these devices at the crime scene.
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Both gaming and group (decision) support systems (GDSS) are frequently used to support decision-making and policymaking in multi-actor settings. Despite the fact that there are a number of ways in which gaming and GDSS can be used in a complementary manner, there are only sporadic examples of their combined use. No systematic overview or framework exists in which GDSS are related to the functions of gaming or vice versa. In this article, we examine, why, how and for what purpose GDSS can be used to enrich and improve gaming simulation for decision support, and vice versa. In addition to a review of examples found in the literature, four games are discussed where we combined gaming and GDSS for complex decision-making in a multi actor context: INCODELTA, a game about transportation corridors; INFRASTRATEGO, a game about a liberalizing electricity market; CONTAINERS A DRIFT, a game about the planning of a container terminal, and; DUBES, a game about sustainable urban renewal. Based on the literature and these four experiences, a classification is presented of (at least) four ways in which GDSS and gaming can be used in a complementary or even mutually corrective, manner: the use of GDSS for game design, for game evaluation, for game operation and the use of gaming for research, testing and training of GDSS.
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Redesigning IT systems for specific user groups encompasses a lot of effort with respect to analysing and understanding user behaviour. The goal of this paper is to provide insights into patterns of behaviour of agricultural users, during the usage of a decision support system called OPTIRas (TM). This system aids agricultural users in their cultivar selection activities. We analyse logs resulting from OPTIRas (TM), and we get insights into user's navigational patterns. We claim that the results of our analysis can be used to support the redesign of decision support systems in order to address specific agricultural users' characteristics.
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Nurses are accountable to apply the nursing process, which is key for patient care: It is a problem-solving process providing the structure for care plans and documentation. The state-of-the art nursing process is based on classifications that contain standardized concepts, and therefore, it is named Advanced Nursing Process. It contains valid assessments, nursing diagnoses, interventions, and nursing-sensitive patient outcomes. Electronic decision support systems can assist nurses to apply the Advanced Nursing Process. However, nursing decision support systems are missing, and no "gold standard" is available. The study aim is to develop a valid Nursing Process-Clinical Decision Support System Standard to guide future developments of clinical decision support systems. In a multistep approach, a Nursing Process-Clinical Decision Support System Standard with 28 criteria was developed. After pilot testing (N = 29 nurses), the criteria were reduced to 25. The Nursing Process-Clinical Decision Support System Standard was then presented to eight internationally known experts, who performed qualitative interviews according to Mayring. Fourteen categories demonstrate expert consensus on the Nursing Process-Clinical Decision Support System Standard and its content validity. All experts agreed the Advanced Nursing Process should be the centerpiece for the Nursing Process-Clinical Decision Support System and should suggest research-based, predefined nursing diagnoses and correct linkages between diagnoses, evidence-based interventions, and patient outcomes.
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