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Interrupted time series versus statistical process control in quality improvement projects
School of Health Sciences, University of Borås, Sweden.
Jönköping University, School of Health and Welfare, The Jönköping Academy for Improvement of Health and Welfare. Jönköping University, School of Health and Welfare, HHJ. IMPROVE (Improvement, innovation, and leadership in health and welfare).
Division of Quality Technology and Management, Linköping University, Sweden.
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) Published
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
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
Nursing Information Systems
Identifiers
URN: urn:nbn:se:hj:diva-28753DOI: 10.1097/NCQ.0000000000000130PubMedID: 26018566Scopus ID: 2-s2.0-84948460041ISBN: 1550-5065 (Electronic) 1057-3631 (Linking) (print)OAI: oai:DiVA.org:hj-28753DiVA: diva2:888185
Available from: 2015-12-22 Created: 2015-12-22 Last updated: 2017-04-20Bibliographically approved

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Andersson-Gäre, BoelElg, Mattias
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  • Other locale
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