Statistics in quality improvement: Measurement and statistical process control.

healthcare quality evaluation process assessment quality improvement quality improvement Statistics statistical process control

Journal

Paediatric anaesthesia
ISSN: 1460-9592
Titre abrégé: Paediatr Anaesth
Pays: France
ID NLM: 9206575

Informations de publication

Date de publication:
05 2021
Historique:
revised: 12 02 2021
received: 09 10 2020
accepted: 16 02 2021
pubmed: 21 2 2021
medline: 5 8 2021
entrez: 20 2 2021
Statut: ppublish

Résumé

Data are used in healthcare quality improvement endeavors to measure and determine whether the changes made in the course of the work have made the desired impact. The methods used to analyze data in quality improvement differ slightly from those used in classical statistics. Run charts and statistical process control charts are the most common types of graphical representations used to visualize data collected for quality improvement. This review provides a basic introduction to measurement in quality improvement and explains the use of run charts and statistical process control charts with real-life examples.

Identifiants

pubmed: 33609306
doi: 10.1111/pan.14163
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

539-547

Informations de copyright

© 2021 John Wiley & Sons Ltd.

Références

Module 4. Approaches to Quality Improvement. Content last reviewed May 2013. Rockville, MD: Agency for Healthcare Research and Quality. https://www.ahrq.gov/ncepcr/tools/pf-handbook/mod4.html. Accessed June 8, 2020.
Benneyan JC, Lloyd RC, Plsek PE. Statistical process control as a tool for research and healthcare improvement. Qual Saf Health Care. 2003;12(6):458-464.
Langley GL, Moen R, Nolan KM, Nolan TW, Norman CL, Provost LP. The Improvement Guide: A Practical Approach to Enhancing Organizational Performance. (2nd edn) San Francisco: Jossey-Bass Publishers; 2009.
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Perla RJ, Provost LP, Murray SK. The run chart: a simple analytical tool for learning from variation in healthcare processes. BMJ Qual Saf. 2011;20(1):46-51.
Montgomery DC. Introduction to Statistical Quality Control. Jefferson City, MO: John Wiley & Sons; 2007.
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Wheeler TA, Davis JT, Brilli RJ. The aggregate point rule for identifying shifts on P charts and U charts. Pediatr Qual Saf. 2018;3(5):e103.
Ogrinc G, Davies L, Goodman D, Batalden PB, Davidoff F, Stevens D. SQUIRE 2.0 (Standards for QUality Improvement Reporting Excellence): revised publication guidelines from a detailed consensus process. BMJ Qual Saf. 2016;25:986-992.

Auteurs

Heather A Wolfe (HA)

Division of Anesthesiology and Critical Care Medicine, The Children's Hospital of Philadelphia, The University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.

April Taylor (A)

Department of Pediatrics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA.

Rajeev Subramanyam (R)

Division of Anesthesiology and Critical Care Medicine, The Children's Hospital of Philadelphia, The University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA.

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