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Er is behoefte aan meer kennis en ondersteuning bij het implementeren van effectieve valpreventieinterventies in de wijk, waar ouderen zelfstandig thuis wonen. Omdat vallen een multifactorieel probleem is en er vele soorten valpreventie-interventies bestaan, is interprofessionele samenwerking gewenst. Door literatuuronderzoek en in focusgroep-bijeenkomsten met verschillende professionals is onderzocht wat bevorderende en belemmerende factoren zijn bij succesvolle interprofessionele samenwerking op het gebied van valpreventie, en welke strategieën effectief zijn. De belangrijkste conclusie is, dat voor het bevorderen van interprofessionele samenwerking coördinatie, communicatie en informatie cruciale factoren zijn. Daarnaast is ook uitwisseling van evidence based kennis en samenwerking met andere stakeholders belangrijk.
The following paper presents a methodology we developed for addressing the case of a multi-modal network to be implemented in the future. The methodology is based on a simulation approach and presents some characteristics that make a challenge to be verified and validated. To overcome this limitation, we proposed a novel methodology that implies interaction with subjectmatter experts, revision of current data, collection and assessment of future performance and educated assumptions. With that methodology we could construct the complete passenger trajectory Door to door in Europe. The results indicate that the approach allows to approach infrastructure analysis at an early stage to have an initial estimation of the upper boundary of performance indicators. To exemplify this, we present the results for a case study in Europe.
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Predictive models and decision support toolsallow information sharing, common situational awarenessand real-time collaborative decision-making betweenairports and ground transport stakeholders. To supportthis general goal, IMHOTEP has developed a set of modelsable to anticipate the evolution of an airport’s passengerflows within the day of operations. This is to assess theoperational impact of different management measures onthe airport processes and the ground transport system. Twomodels covering the passenger flows inside the terminal andof passengers accessing and egressing the airport have beenintegrated to provide a holistic view of the passengerjourney from door-to-gate and vice versa.This paper describes IMHOTEP’s application at two casestudy airports, Palma de Mallorca (PMI) and London City(LCY), at Proof of Concept (PoC-level) assessing impactand service improvements for passengers, airport operatorsand other key stakeholders.For the first time onemeasurable process is created to open up opportunities forbetter communication across all associated stakeholders.Ultimately the successful implementation will lead to areduction of the carbon footprint of the passenger journeyby better use of existing facilities and surface transportservices, and the delay or omission of additional airportfacility capacities.
In case of a major cyber incident, organizations usually rely on external providers of Cyber Incident Response (CIR) services. CIR consultants operate in a dynamic and constantly changing environment in which they must actively engage in information management and problem solving while adapting to complex circumstances. In this challenging environment CIR consultants need to make critical decisions about what to advise clients that are impacted by a major cyber incident. Despite its relevance, CIR decision making is an understudied topic. The objective of this preliminary investigation is therefore to understand what decision-making strategies experienced CIR consultants use during challenging incidents and to offer suggestions for training and decision-aiding. A general understanding of operational decision making under pressure, uncertainty, and high stakes was established by reviewing the body of knowledge known as Naturalistic Decision Making (NDM). The general conclusion of NDM research is that experts usually make adequate decisions based on (fast) recognition of the situation and applying the most obvious (default) response pattern that has worked in similar situations in the past. In exceptional situations, however, this way of recognition-primed decision-making results in suboptimal decisions as experts are likely to miss conflicting cues once the situation is quickly recognized under pressure. Understanding the default response pattern and the rare occasions in which this response pattern could be ineffective is therefore key for improving and aiding cyber incident response decision making. Therefore, we interviewed six experienced CIR consultants and used the critical decision method (CDM) to learn how they made decisions under challenging conditions. The main conclusion is that the default response pattern for CIR consultants during cyber breaches is to reduce uncertainty as much as possible by gathering and investigating data and thus delay decision making about eradication until the investigation is completed. According to the respondents, this strategy usually works well and provides the most assurance that the threat actor can be completely removed from the network. However, the majority of respondents could recall at least one case in which this strategy (in hindsight) resulted in unnecessary theft of data or damage. Interestingly, this finding is strikingly different from other operational decision-making domains such as the military, police and fire service in which there is a general tendency to act rapidly instead of searching for more information. The main advice is that training and decision aiding of (novice) cyber incident responders should be aimed at the following: (a) make cyber incident responders aware of how recognition-primed decision making works; (b) discuss the default response strategy that typically works well in several scenarios; (c) explain the exception and how the exception can be recognized; (d) provide alternative response strategies that work better in exceptional situations.
The operations of take-off and landing at hub airports are often subject to a wide variety of delays; the effects of these delays impact not only the related stakeholders, such as aircraft operators, air-traffic control unity and ground handlers but as part of the European network, delays are propagated through the network. As a result, Airport Collaborative Decision Making (A-CDM) is being employed as a methodology for increasing the efficiency of Air Traffic Management (ATM), through the involvement of partners within the airports. Under CDM, there are some strategic common objectives regardless the airport or the partner specific interest to improve operational efficiency, predictability and punctuality to the ATM network and airport stakeholders. Monitoring and controlling some strategic areas such as, Efficiency, Capacity, Safety and Environment is needed to achieve the benefits. Therefore, the present work aims to provide a framework to monitor the accuracy of capacity in the three main flight phases. It aims to provide a comprehensible and practical approach to monitoring capacity by identifying and proposing Key Performance Indicators (KPIs) based on the A-CDM Milestone Approach to optimise the use of available capacity. To illustrate our approach, Amsterdam Airport Schiphol is used as case study as a full A-CDM airport.
This study introduces a novel methodology for the post-analysis of operational predictability by leveraging timestamps collected through the Airport Collaborative Decision Making (A-CDM) framework. Focusing on the start-up and departure phases, the analysis highlights the importance of accurately planning and managing key timestamps, such as the Target Off-Block Time (TOBT) and Target Start-Up Approval Time (TSAT), which are critical for operational efficiency. Using one week of sample data from Schiphol Airport, this research demonstrates the potential benefits of the proposed framework in improving predictability during the start-up phase, particularly by identifying and analyzing outliers and anomalies. The start-up phase, a critical component of the outbound process, was broken down into subphases to allow for a more detailed assessment. The findings suggest that while 96% of flights maintain TOBT accuracy within ±20 minutes, 68% of flights miss their TOBT by 2 to 17.5 minutes, with 364 notable outliers. These deviations highlight areas for further investigation, with future work aiming to explore the impact of influencing factors such as weather, resource availability, and support tools. The proposed framework serves as a foundation for improving operational predictability and efficiency at airports.
