Distributed cognition: An alternative model of cognition for medical informatics

https://doi.org/10.1016/j.ijmedinf.2007.04.008Get rights and content

Abstract

Background

Medical informatics has been guided by an individual-centered model of human cognition, inherited from classical theory of mind, in which knowledge, problem-solving, and information-processing responsible for intelligent behavior all derive from the inner workings of an individual agent.

Objectives and results

In this paper we argue that medical informatics commitment to the classical model of cognition conflates the processing performed by the minds of individual agents with the processing performed by the larger distributed activity systems within which individuals operate. We review trends in cognitive science that seek to close the gap between general-purpose models of cognition and applied considerations of real-world human performance. One outcome is the theory of distributed cognition, in which the unit of analysis for understanding performance is the activity system which comprises a group of human actors, their tools and environment, and is organized by a particular history of goal-directed action and interaction.

Conclusion

We describe and argue for the relevance of distributed cognition to medical informatics, both for the study of human performance in healthcare and for the design of technologies meant to enhance this performance.

Introduction

The field of medical informatics emerged from the practical information technology challenges of real-world health care delivery operations [1]. These origins have defined its main identity as an applied field of information technology engineering while, as an academic discipline, broader questions about the human performance that determines successful care delivery have also been a focus. We believe that medical informatics has been guided by a model of human cognition – whether implicit in technology applications and process designs, or explicit in academic pedagogy – in which the individual mind is the locus of knowledge, problem-solving, and information processing responsible for intelligent behavior. In this paper we consider the consequences of this commitment to an individual-centered model of cognition. We claim that this commitment conflates the processing performed within the minds of individual human agents with the processing performed by a distributed activity system in which these individuals are embedded. This conflation generates misunderstandings about the bases for human performance, and these misunderstandings can become incorporated into technologies and processes intended to enhance that performance but often having a much different effect. We survey developments in applied cognitive science that question the traditional, individual-centered model for explaining human cognition and performance in real-world settings. We suggest that an alternative model of cognition, distributed cognition is relevant to understanding cognitive processes in healthcare and will be useful in addressing the challenges of technology and process design to enhance performance.

Section snippets

The gap between classical theory of cognition and accounts of situated action

A gap exists between (a) classical cognitive theory that attempts to capture general principles of human performance through models of a general-purpose human cognitive architecture, and (b) on-the-ground, context-specific, and applied questions about human performance that reflect real-world dynamics, complexities, and circumstances. This gap has significant consequences for workplace technology and process interventions that typically derive from more or less explicit notions of

Developments in cognitive science research that begin to bridge the gap

The field of human factors research addresses some of the gap between conceptualizations of general-purpose cognitive architecture and human performance in complex work activities by addressing real-world tasks, as opposed to purely artificial tasks. The field's practical concerns relate directly to human performance in specific settings, including efforts to improve safety and increase effectiveness in industrial, military, and healthcare environments [20], [21], [22]. This research to improve

Distributed cognition

The framework of distributed cognition has its roots in cognitive anthropology, cognitive science, and more recently, the CSCW community. Traditional cognitive science has a long history of studying the relationship between individuals’ internal organizations and their behaviors in terms of information processing properties of the central nervous system [3]. Distributed cognition, by contrast, treats the activity system, rather than the individual, as the unit of cognitive analysis [16], [38],

Discussion

Although the classical paradigm of cognition has advanced our understanding of human behavior through modeling phenomena internal to individuals, this paradigm has had limited success bridging the gap that exists between models of a general-purpose cognitive architecture and explanations of human performance in complex, real-world situations. The concepts of distributed cognition address this gap by introducing a new unit of cognitive analysis. An activity system comprises a group of human

Conclusions

Human performance nearly always involves use of technology. The framework of distributed cognition prescribes a new unit of analysis for research to understand human performance: the activity system, including actors, their technologies and artifacts, and the rules and understandings for interactions among them that support task work. Technology and process designs for healthcare that are intended to enhance human performance can benefit from systematic research that takes the activity system

Acknowledgements

This material is based upon work supported by the National Science Foundation under grant number IIS-0534797 and the Agency for Healthcare Research and Quality grant number 5 R01 HS12003.

References (56)

  • A. Newell et al.

    Computer science as empirical enquiry: symbols and search

  • C. Geertz

    The growth of culture and the evolution of mind

  • V.L. Patel et al.

    A primer on aspects of cognition for medical informatics

    J. Am. Med. Inform. Assoc.

    (2001)
  • R.S. Ledley et al.

    Reasoning foundations of medical diagnosis; symbolic logic, probability, and value theory aid our understanding of how physicians reason

    Science

    (1959)
  • A.S. Elstein et al.

    Medical Problem Solving: An Analysis of Clinical Reasoning

    (1978)
  • R.A. Miller et al.

    Internist-1, an experimental computer-based diagnostic consultant for general internal medicine

    N. Engl. J. Med.

    (1982)
  • B.G. Buchanan et al.

    Rule-based Expert Systems: The MYCIN Experiments of the Stanford Heuristic Programming Project

    (1984)
  • C.P. Friedman et al.

    Enhancement of clinicians’ diagnostic reasoning by computer-based consultation: a multisite study of 2 systems

    JAMA

    (1999)
  • R. Koppel et al.

    Role of computerized physician order entry systems in facilitating medication errors

    JAMA

    (2005)
  • Y.Y. Han et al.

    Unexpected increased mortality after implementation of a commercially sold computerized physician order entry system

    Pediatrics

    (2005)
  • C.J. McDonald

    Computerization can create safety hazards: a bar-coding near miss

    Ann. Intern. Med.

    (2006)
  • Office of the National Coordinator for Health Information Technology (ONC), Legislative Testimony on Health Information...
  • E. Hutchins

    Cognition in the Wild

    (1996)
  • M. Cole

    Cultural Psychology

    (1996)
  • L. Suchman

    Plans and Situated Actions. The problem of Human–Machine Communication

    (1987)
  • B. Hazlehurst et al.

    Orienting frames and private routines: the role of cultural process in critical care safety

    Int. J. Med. Inform.

    (2006)
  • J. Reason

    Human Error

    (1990)
  • Cited by (82)

    • Identifying best practices in electronic health record documentation to support interprofessional communication for the prevention of central line–associated bloodstream infections

      2020, American Journal of Infection Control
      Citation Excerpt :

      This deductive approach begins with identifying initial coding categories based on concepts or variables from the guiding theoretical frameworks.16 For this study, the coding categories represented concepts from the guiding theoretical frameworks of distributed cognition11 and Coiera's12 communication space. The round 2 survey developed from the directed content analysis was sent electronically to participants.

    • Driven to distraction: The nature and apparent purpose of interruptions in critical care and implications for HIT

      2017, Journal of Biomedical Informatics
      Citation Excerpt :

      In contrast to the mind-centric view of cognition, DC suggested that only a part of human cognitive activity happens within an individual mind, isolated from the individual’s physical, social, and cultural environment. The proponents of DC reframed cognition as a property of complex dynamic sociotechnical activity systems that included human as well as non-human actors, such as resources and materials in the physical world [25,23]. Moreover, DC viewed cognitive systems as distributed socially, in that they are bounded by the underlying social structures of organizations; embodied, in that cognition is shaped not only by the human mind, but also by the way humans perceive and interact with the physical world; and culturally-sensitive, in that these systems are deeply impacted by values, influences, and traditions within their cultural environments [26].

    View all citing articles on Scopus
    View full text