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The study of clinical work processes in hospitals: methods and applications of the quantitative observational approach

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posted on 29.03.2022, 00:33 by Scott R. Walter
Clinicians work in complex, dynamic work environments where synchronous communication and the management of competing time-constrained demands in a team environment are fundamental to safe healthcare delivery. Previous empirical research on clinical workflow has investigated the characteristics of clinical tasks and the context in which they occur as potential contributors to the risk of error. Strategies adopted by clinicians, such as the use of interrupting and multitasking, have been a particular focus of such study given their prevalence in clinical work and widespread perception of their negative impact on effciency and safety. However, our understanding of the role and effects of these behaviours in complex healthcare settings is far from complete. A major impediment to progressing knowledge has been a lack of quantitative observational methodology, namely the design of studies using direct observations that adequately encompass the complexity of clinical work,and the use of appropriate data analytic techniques. This thesis aimed to advance direct observational methods and related statistical analysis techniques relevant to work processes in non-experimental settings, and to apply those methods to the study of everyday clinical practices. Drawing upon an extensive examination of cross-disciplinary research, a clinically-relevant conceptualisation of the work process was proposed that uniFIes several concepts previously used to study interruptions and multitasking in healthcare. Second, this framework was applied to analyse existing datasets comprising over one thousand hours of observations of clinicians, yielding fresh insights about their work practices. Third, an observational study of doctors was designed around the conceptualisation and conducted in the emergency department of a tertiary hospital. This extended previous approaches to provide a more comprehensive analysis of strategies used by clinicians in response to a range of disruptive events. Fourth,an overarching theme of this thesis is to identify ways in which existing statistical methodology can be both better applied and extended to expand the scope of research questions that can be tackled on work processes in healthcare. The analyses above implemented statistical modelling techniques in a way not previously used to study clinical work. Furthermore, a new technique was developed to assess the impact of disruptive events on task completion time, and was then applied to data from observations of doctors in a range of hospital settings. Through the application of improved observational and statistical methods this thesis has progressed debates about the conceptualisation of clinical workFLow, identified factors that inuence clinicians' strategies to manage disruptive events in a range of healthcare settings, and better quantified the impact of interruptions on task completion time. This has provided a more sophisticated understanding of the relationships between work behaviours, work effciency and error production. Moreover, the methodological progress enables future creation of knowledge necessary for safety improvement.


Table of Contents

1. Introduction -- 2. Methodological challenges for in situ observational studies -- 3. Defining clinical work -- 4. The prompt-response process : a retrospective analysis -- 5. The prompt-response process : a prospective study -- 6. The Poisson mixture model : theoretical details -- 7. The Poisson mixture model : application to observations of doctors in multiple hospital settings -- 8. Discussion -- A. Study documents.


Includes bibliographical references At foot of title: Centre for Health Systems and Safety Research, Australian Institute of Health Innovation, Faculty of Medicine and Health Sciences, Macquarie University. Thesis by publication.

Awarding Institution

Macquarie University

Degree Type

Thesis PhD


PhD, Macquarie University, Faculty of Medicine and Health Sciences, Australian Institute of Health Innovation

Department, Centre or School

Australian Institute of Health Innovation

Year of Award


Principal Supervisor

Johanna I. M. (Johanna Irene Mary) Westbrook

Additional Supervisor 1

William Dunsmuir


Copyright Scott R. Walter 2016. Copyright disclaimer: http://mq.edu.au/library/copyright




1 online resource (xii, 154 pages)

Former Identifiers

mq:69673 http://hdl.handle.net/1959.14/1256608