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Interrupted Time Series Versus Statistical Process Control in Quality Improvement Projects
University of Borås, Sweden.
Jönköping University, Sweden.
Linköping University, Department of Management and Engineering, Logistics & Quality Management. Linköping University, Faculty of Science & Engineering. Linköping University, HELIX Vinn Excellence Centre.ORCID iD: 0000-0003-4730-5453
2016 (English)In: Journal of Nursing Care Quality, ISSN 1057-3631, E-ISSN 1550-5065, Vol. 31, no 1, E1-E8 p.Article in journal (Refereed) PublishedText
Abstract [en]

To measure the effect of quality improvement interventions, it is appropriate to use analysis methods that measure data over time. Examples of such methods include statistical process control analysis and interrupted time series with segmented regression analysis. This article compares the use of statistical process control analysis and interrupted time series with segmented regression analysis for evaluating the longitudinal effects of quality improvement interventions, using an example study on an evaluation of a computerized decision support system.

Place, publisher, year, edition, pages
LIPPINCOTT WILLIAMS & WILKINS , 2016. Vol. 31, no 1, E1-E8 p.
Keyword [en]
computerized decision support system; quality improvement; segmented regression; statistical process control; time series
National Category
Probability Theory and Statistics
URN: urn:nbn:se:liu:diva-130319DOI: 10.1097/NCQ.0000000000000130ISI: 000378245700001PubMedID: 26018566OAI: diva2:950482
Available from: 2016-07-31 Created: 2016-07-28 Last updated: 2016-07-31

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Elg, Mattias
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