Understanding clinical workflow through direct continuous observation: addressing the unique statistical challenges

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review


Direct observation of clinicians is an effective way to study the inner workings of clinical work. Of the many observational approaches, workflow time studies generate a continuous, fine-grained record of individuals’ tasks and interactions, providing a foundation from which to explore a wide range of research questions within a quantitative framework. Although the concept of recording time-stamped tasks according to predefined categories is relatively simple, the complexity of the settings to which workflow time studies are applied often generates data that are not amenable to conventional statistical analysis methods. In this chapter, we examine some of the fundamental considerations for analysis of such data, with a particular focus on the use of nonparametric methods as a way to circumvent limitations with standard methods. This includes sampling strategies, inter-observer reliability assessment, calculating confidence intervals and performing hypothesis tests. We also discuss nonparametric possibilities for multivariate analysis. While quantitative observational studies of clinical work have great potential to help us understand clinical workflow, it is essential to apply statistical methods with care, to acknowledge their limitations and to identify areas where bespoke methodology needs to be developed. To improve the integrity of such research then requires more explicit and open discussion of quantitative methodology, and this chapter aims to initiate these discussions.
Original languageEnglish
Title of host publicationCognitive informatics
Subtitle of host publicationreengineering clinical workflow for safer and more efficient care
EditorsKai Zheng, Johanna Westbrook, Thomas G. Kannampallil, Vimla L. Patel
Place of PublicationSwitzerland
Number of pages20
ISBN (Electronic)9783030169169
ISBN (Print)9783030169152
Publication statusPublished - 2019

Publication series

NameHealth Informatics
ISSN (Print)1431-1917
ISSN (Electronic)2197-3741


  • workflow time studies
  • time and motion studies
  • observational studies
  • statistical methods
  • nonparametric statistics
  • clinical workflow


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