Tıpta kalite kontrolü her geçen gün daha fazla ilgi görmektedir. Bir kontrol çizelgesi, istatistiksel olarak belirlenen limitlere göre ölçülen bir işlemin performansını grafiksel olarak temsil eden veri noktaları içerir. Kontrol çizelgelerinin amacı, bir sürecin kontrol altında olup olmadığını ve bu süreçteki varyasyonun ortak veya özel nedenlerden kaynaklanıp kaynaklanmadığını tespit etmektir. Kontrol çizelgesi, 1920'lerin başlarında Shewhart tarafından geliştirilen, en başarılı istatistiksel süreç kontrol aracıdır. Kontrol çizelgesinin kullanılmasının temel amacı, değişimi ve kaynağını inceleyerek zaman içinde süreç performansını izlemek, kontrol etmek ve iyileştirmektir. Literatürde çok sayıda farklı kontrol çizelgesi mevcuttur. EWMA ve CUSUM dışındaki grafikler, bir histogram üzerinde çizildiğinde simetrik ve çan şeklindeki normal dağılıma sahip veriler için en uygun olanlardır. EWMA ve CUSUM çizelgeleri ise Lognormal, Exponential, Binomial, Poisson ve Geometrik rasgele değişkenler de dahil olmak üzere diğer veri türleri için geliştirilmiştir. Bu yazının odak noktası EWMA çizelgesidir. Bu yazıda EWMA istatistiksel süreç kontrol metodolojisi ve tıp alanındaki uygulamaları gözden geçirilecektir. EWMA çizelgesi, verilerdeki küçük değişiklikleri belirleyebildiğinden ve çarpık veri dağılımları ile iyi performans gösterdiğinden seçilmiştir. EWMA çizelgesi, süreç parametrelerindeki küçük ve orta düzeydeki değişimleri saptamadaki mükemmel yeteneği nedeniyle şu anda yaygın bir şekilde kullanılmaktadır. Küçük değişiklikleri saptamak için çok esnek ve etkili bir çizelgedir ve normal dağılımın söz konusu olmadığı durumlarda sağlamlık gösterme avantajına sahiptir.
Anahtar Kelimeler: Kontrol çizelgesi; EWMA; istatistiksel süreç kontrolü
Quality control in medicine is generating more and more interest everyday. A control chart contains data points that graphically represent the performance of a process, measured against statistically determined limits. The purpose of control charts is to ascertain whether a process is in control or out of control and, therefore, whether variation within that process is due to common or special causes. Control chart is the most successful statistical process control tool, originally developed by Shewhart in the early 1920s. The main purpose of using a control chart is to monitor, control, and improve process performance over time by studying variation and its source. There are a multitude of different types of control charts available in the literature. Charts, other than Exponentially Weighted Moving Average (EWMA) and CUSUM (Cumulative Sum) are most appropriate for normally distributed data, which are symmetric and bell shaped when plotted on a histogram. EWMA and CUSUM charts have been developed for other types of data as well, including Lognormal, Exponential, Binomial, Poisson, and Geometric random variables. The focus of this paper is the EWMA chart. In this paper, will review the methodology of EWMA statistical process control and its application in medical practice. The EWMA chart was selected since it is able to detect small shifts in the data and perform well with skewed data distributions. The EWMA chart has now been widely used because of its excellent ability to detect small to moderate shifts in the process parameters. It is a very flexible and effective chart for detecting small changes and has the advantage of showing robustness to non normality.
Keywords: Control chart; EWMA; statistical process control
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