Why is it so difficult to measure the effects of interruptions in healthcare?

Farah MAGRABI; Yau Wai, Simon LI; Adam G. DUNN; Enrico COIERA

doi:10.3233/978-1-60750-588-4-784

Why is it so difficult to measure the effects of interruptions in healthcare?

Farah MAGRABI, Yau Wai, Simon LI, Adam G. DUNN, Enrico COIERA

Department of Applied Psychology

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Research › peer-review

11 Citations (Scopus)

Abstract

Interruptions are a complex phenomenon where multiple variables including the characteristics of primary tasks, the interruptions themselves, and the environment may influence patient safety and workflow outcomes. Observational studies present significant challenges for recording many of the process variables that influence the effects of interruptions. Controlled experiments provide an opportunity to examine the specific effects of variables on errors and efficiency. Computational models can be used to identify the situations in which interruptions to clinical tasks could be disruptive and to investigate the aggregate effects of interruptions.

Original language	English
Title of host publication	MEDINFO 2010: Proceedings of the 13th World Congress on Medical Informatics
Publisher	IOS Press
Pages	784-788
Number of pages	5
ISBN (Print)	9781607505877
DOIs	https://doi.org/10.3233/978-1-60750-588-4-784
Publication status	Published - 1 Sept 2010

Keywords

Computer simulation
Efficiency
Evaluation studies
Interruption
Medical error
Observation
Safety

Access to Document

10.3233/978-1-60750-588-4-784

Cite this

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title = "Why is it so difficult to measure the effects of interruptions in healthcare?",

abstract = "Interruptions are a complex phenomenon where multiple variables including the characteristics of primary tasks, the interruptions themselves, and the environment may influence patient safety and workflow outcomes. Observational studies present significant challenges for recording many of the process variables that influence the effects of interruptions. Controlled experiments provide an opportunity to examine the specific effects of variables on errors and efficiency. Computational models can be used to identify the situations in which interruptions to clinical tasks could be disruptive and to investigate the aggregate effects of interruptions.",

keywords = "Computer simulation, Efficiency, Evaluation studies, Interruption, Medical error, Observation, Safety",

author = "Farah MAGRABI and LI, {Yau Wai, Simon} and DUNN, {Adam G.} and Enrico COIERA",

year = "2010",

month = sep,

day = "1",

doi = "10.3233/978-1-60750-588-4-784",

language = "English",

isbn = "9781607505877",

pages = "784--788",

booktitle = "MEDINFO 2010: Proceedings of the 13th World Congress on Medical Informatics",