Pre-requisites for large scale coordination

Johansson, Björn; Hollnagel, Erik

doi:10.1007/s10111-006-0050-z

Cited by 27 publications

(15 citation statements)

References 10 publications

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“…We find multiple similarities between Joint Cognitive Systems (JCSs; Johansson and Hollnagel 2006) and CIS. Both constructs seek to describe the challenges of information shaping and sharing across multiple actors.…”

Section: Common Information Spacesmentioning

confidence: 99%

Identifying patients at risk of deterioration in the Joint Emergency Department

Schmidt

Wiil

2015

Cogn Tech Work

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In recent years, Danish hospitals have merged their emergency facilities into Joint Emergency Departments. This poses new collaborative challenges across traditionally separated specialized departments, which now have to collaborate in a shared environment. Despite established protocols and patient monitoring regimes, as many as 31 % of non-critical patients deteriorate with potentially severe consequences. To understand why this may be, we conduct a field study with the aim of investigating what factors external to patients relate to the clinicians' ability to notice adverse events. We look at the case through the lenses of common information spaces. In particular, we apply Bossen's seven-parameter framework to discover new dimensions of how Emergency Departments and individual clinicians identify and respond to unforeseen events, and how they handle the associated cognitive challenges. We complement these findings with a review of a novel taxonomy for patient monitoring. Our contribution is the identification of four improvement areas for patient monitoring platforms in terms of support for the identification of patient deterioration.

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Section: Common Information Spacesmentioning

confidence: 99%

Identifying patients at risk of deterioration in the Joint Emergency Department

Schmidt

Wiil

2015

Cogn Tech Work

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“…Consequently, responding to disturbances in a timely manner in order to restore services rapidly has become an important objective. To do so, operators must assess the nature and state of the disruption and adjust operations before it becomes impossible to control (Johansson and Hollnagel 2007). Under the influence of restructuring policies, the Dutch railway system has undergone major changes over the past decades, resulting in the separation of infrastructure management and rail operations activities.…”

Section: Introductionmentioning

confidence: 99%

“…Coordination can be achieved through predefined plans and procedures, but given the dynamic and uncertain environment in which operators work, real-time adaptation of plans is often necessary (Johansson and Hollnagel 2007). In practice, situations during a disruption often changed faster than the involved parties could communicate and the decentralized control made it difficult to manage disruptions with a national impact (Goodwin et al 2012).…”

Section: Introductionmentioning

confidence: 99%

“…It also depends on how geographically and organizationally separated teams carry out their roles and manage interdependencies across the different levels of control (Johansson and Hollnagel 2007;Woods and Branlat 2010). During the past year, there have been several largescale disruptions in the Dutch railway system where the situation became 'out of control' and no one really knew what was going on or what should be done.…”

Section: Introductionmentioning

confidence: 99%

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Challenges to multiteam system leadership: an analysis of leadership during the management of railway disruptions

Schipper

2017

Cogn Tech Work

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Rail traffic is controlled by operators working in multiple control centres. Although each of these control centres enjoy quite some autonomy and authority, their activities are highly interdependent. This is especially the case during the management of disruptions. In this study, we look at the role of leader teams with system-wide responsibilities and the task of synchronizing the control centres' activities. Research on leadership in this multiteam setting of networked control centres, which operate in a dynamic and time-compressed environment, is limited. Hence, this study explores the behaviours and functions of these leader teams during the management of two largescale disruptions in the Dutch railway system. We will show how various factors influence the ability to provide leadership within this specific real-world context. This study demonstrates that combining insights from the literature on multiteam systems and resilience engineering can contribute to our knowledge of the critical challenges of control in polycentric adaptive systems.

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“…a faster, reactive response by a maintenance operator to an imminent failure, as opposed to the longer proactive strategic response of a maintenance planner). This has potential parallels with the ECOM (Extended Control Model) model (Hollnagel, 2007). While advice generation presents the highest level of synthesis and analysis of data presented to the operator, the architecture emphasises it should be possible to access data at any stage of this process.…”

Section: Intelligent Infrastructurementioning

confidence: 99%

A framework to support human factors of automation in railway intelligent infrastructure

Dadashi¹,

Wilson²,

Golightly³

et al. 2014

Ergonomics

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Technological and organisational advances have increased the potential for remote access and proactive monitoring of the infrastructure in various domains and sectorswater and sewage, oil and gas, and transport. Intelligent Infrastructure (II) is an architecture that potentially enables the generation of timely and relevant information about the state of any type of infrastructure asset, providing a basis for reliable decision making. This paper reports an exploratory study to understand the concepts and human factors associated with II in the railway, largely drawing from structured interviews with key industry decision makers and attachment to pilot projects. Outputs from the study include a data processing framework defining the key human factors at different levels of the data structure within a railway II system and a system level representation. The framework and other study findings will form a basis for human factors contributions to systems design elements such as information interfaces and role specifications. Practitioner summaryThe framework reported in this paper can become the basis for human factors guidance of engineers, developers and business analysts in developing appropriate levels of information display, automation and decision aid into rail II. Guidance will be aimed at the different functions and activities within multi-layered, multi-agent control.

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Pre-requisites for large scale coordination

Cited by 27 publications

References 10 publications

Identifying patients at risk of deterioration in the Joint Emergency Department

Identifying patients at risk of deterioration in the Joint Emergency Department

Challenges to multiteam system leadership: an analysis of leadership during the management of railway disruptions

A framework to support human factors of automation in railway intelligent infrastructure

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