title: [Comparing quality measurements Part 2: control charts].
abstract: Comparative quality measurements and evaluations in nursing play significant roles. Quality measures are affected by systematic and random error. Statistical Process Control (SPC) offers a method to take random variation adequately into account. In this article, control charts are introduced. Those are graphical displays to show quality measures over time. Attribute variables can be displayed by p-, u- and c-control charts. Special cause variations within the processes can be detected by rules. If signs for special cause variations are absent, the process in considered being in statistical control showing common cause variation. A deviation of one data point greater than three standard deviations from the arithmetic mean is considered the strongest signal for non random variation within the process. Within quality improvement contexts control charts outperform traditional comparisons of means and spreads.
authors.affiliation: Clinical Research Center for Hair and Skin Science, Klinik für Dermatologie, Venerologie und Allergologie, Charité Universitätsmedizin Berlin, Deutschland. jan.kottner@email.de
authors.forename: Jan
authors.initials: J
authors.lastname: Kottner
authors.forename: Armin
authors.initials: A
authors.lastname: Hauss
mesh_terms: D000704:Analysis of Variance; D003196:Computer Graphics; D005858:Germany; D006801:Humans; D009732:Nursing Care / Q000592:standards*; D017064:Process Assessment, Health Care / Q000706:statistics & numerical data; D011785:Quality Assurance, Health Care / Q000379:methods* / Q000706:statistics & numerical data*; D058996:Quality Improvement / Q000706:statistics & numerical data