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DESIGNING INTERACTIONS 107 Figure 6.1 A voice-driven interface to an electronic medical record system can use a computational solution relying on speech technologies, or a hybrid approach using communication and information technology. One design solution developed at the University Hospital in Geneva allowed clinical staff to interact with the medical record via a telephone pool of trained operators. Source: Scherrer et al. (1990). that occurs across it for it to operate. In contrast, a computer system would need to explicitly model any dialogue that occurs across it. From this point of view, we can say that there is a continuum of possible model formalization available to us. For a given task, system designers make an explicit choice to model some or all of a process, based upon their perception of costs and benefits. When the choice is to formalize the process substantially we will sometimes find computational solutions are used. When the task is left informal, we should instead find that communication solutions are required. Searching for a similar characterization of the continuum, one can turn to the literature in psychology and linguistics. While much communication research is focused on the specifics of conversational structure, some work does step back and look at the underlying notions of how much of a conversation has been explicitly modelled. In particular, the psychological notion of common ground is a strong match with the notion of relative formality of model construction. Common ground refers to the knowledge shared by two communicating agents. For a conversation to occur, agents have to share knowledge about language as well as knowledge about the subject under discussion. We know intuitively, for example, that discussing a medical problem with a clinical colleague or with a patient results in very different conversations. While messages can be concise and much mutual knowledge can be assumed between colleagues, explaining an issue to a non-expert requires the main message to be
108 STARTING POINTS sent along with the background knowledge needed to make the message understandable. Unsurprisingly then, human agents communicate more easily with others of similar occupation and educational background, since they have similar experiences, beliefs and knowledge. Further, the more individuals communicate, the more similar they become. We can recognize sharing of common ground as a key reason that similar agents find it easy to converse with each other. Further, during the process of any given conversation, there are actually two separate streams of dialogue. The first is concerned with the specifics of the conversation, whilst the second is devoted to checking that messages have been understood, and may result in sharing of common ground when it is clear assumptions about shared knowledge do not hold. Thus building common ground requires mutual effort and consent between participating agents. The notion of common ground holds whether we are discussing a conversational interaction between humans, or a human—computer interaction. For a computationally rendered information system, the system designer must create a model of what the user will want to do with the application. For their part, users will have to learn a model of how to operate the computer application. Where both computer and user share this common ground, the interaction should be succinct and effective. Where the user or system do not share mutual knowledge we run into difficulty. If the user lacks knowledge of the system’s operation, the human—computer dialogue will be ineffective. Where the system does not model its context of use, it will be regarded as an inappropriate intrusion into the work place. Building common ground incurs costs for the participating agents. For example, a computer user spends some time up-front learning the functions of a system in anticipation of having to use them for future interactions. Inevitably, not everything that can be ‘said’ to the computer is learnt in this way, and users also typically learn new features of a system as they interact with it for particular tasks. This means that agents have two broad classes of grounding choice: ■ Pre-emptive grounding: Agents can share knowledge prior to a specific conversational task assuming it will be needed in the future. They elect to bear the grounding cost ahead of time and risk the effort being wasted if it is never used. This is a good strategy when task time is limited. For example, training a medical emergency team on how to interact with each other makes sense because at the time of a real clinical emergency, there is no time for individuals to question each other to understand the meaning of any specific orders or requests. Pre-emptive grounding is a bad strategy when the shared knowledge is never used and the time and effort in grounding becomes wasted. For example, training students with knowledge that is unlikely to be used when they face a task in the workplace is usually a poor allocation of resources. From first principles, the cost of pre-emptive grounding is proportionate to the amount of common ground an agent has to learn. For
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Health Information Management In al
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Health Information Management Integ
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Contents List of illustrations vii
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Illustrations FIGURES 3.1 Medicatio
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Contributors Marc Berg is a physici
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Series preface In almost all Wester
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Acknowledgements I would like to th
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Chapter 1 Introduction In all Weste
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INTRODUCTION 3 touch upon the deplo
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INTRODUCTION 5 can draw upon to mai
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INTRODUCTION 7 Physician Order Entr
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Part I Starting points Understandin
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WAITING FOR GODOT 11 KEY TERMS ■
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WAITING FOR GODOT 13 Netherlands an
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WAITING FOR GODOT 15 facts to show
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WAITING FOR GODOT 17 (Lewinski-Corw
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WAITING FOR GODOT 19 In most cases,
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WAITING FOR GODOT 21 (Anonymous 191
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WAITING FOR GODOT 23 Because of the
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WAITING FOR GODOT 25 they simply sa
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WAITING FOR GODOT 27 expected. Stil
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WAITING FOR GODOT 29 organize their
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WAITING FOR GODOT 31 performance in
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WAITING FOR GODOT 33 different HIS
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WAITING FOR GODOT 35 CONCLUSION: TH
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WAITING FOR GODOT 37 assumption tha
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WAITING FOR GODOT 39 Anonymous (191
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WAITING FOR GODOT 41 Berg, M. (1997
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Chapter 3 Health care work and pati
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HEALTH CARE WORK AND INFORMATION SY
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Page 72 and 73: HEALTH CARE WORK AND INFORMATION SY
Page 78 and 79: THE CONTEXTUAL NATURE OF INFORMATIO
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Page 96 and 97: STARTING POINTS 81 ‘gender, race,
Page 98 and 99: STARTING POINTS 83 Now, imagine an
Page 100 and 101: STARTING POINTS 85 organization,
Page 102 and 103: STARTING POINTS 87 Figure 5.2 Incre
Page 104 and 105: STARTING POINTS 89 already overflow
Page 106 and 107: STARTING POINTS 91 responsibilities
Page 108 and 109: STARTING POINTS 93 answer the quest
Page 110 and 111: STARTING POINTS 95 Kohn, L.T., J.M.
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Page 114 and 115: DESIGNING INTERACTIONS 99 the way t
Page 116 and 117: DESIGNING INTERACTIONS 101 1 Identi
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Page 128 and 129: DESIGNING INTERACTIONS 113 Figure 6
Page 130 and 131: DESIGNING INTERACTIONS 115 Figure 6
Page 132 and 133: DESIGNING INTERACTIONS 117 Covell D
Page 134 and 135: Part II Information strategy, imple
Page 136 and 137: INFORMATION STRATEGY: AN INTRODUCTI
Page 152 and 153: Chapter 8 Developing the informatio
Page 154 and 155: STRATEGY, IMPLEMENTATION AND EVALUA
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Guidelines for information system d
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STRATEGY, IMPLEMENTATION AND EVALUA
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Chapter 9 Implementing information
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IMPLEMENTING INFORMATION SYSTEMS 16
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Chapter 10 Project management of in
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Index accumulation 53-4, 61, 73-4,
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INDEX 223 contingent and emergent c
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INDEX 225 satisfaction 176 patient
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INDEX 227 support 164 technology de
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