Comparison of control charts for monitoring clinical performance using binary data

Abstract

BackgroundTime series charts are increasingly used by clinical teams to monitor their performance, but statistical control charts are not widely used, partly due to uncertainty about which chart to use. Although there is a large literature on methods, there are few systematic comparisons of charts for detecting changes in rates of binary clinical performance data.MethodsWe compared four control charts for binary data: the Shewhart p-chart; the exponentially weighted moving average (EWMA) chart; the cumulative sum (CUSUM) chart; and the g-chart. Charts were set up to have the same long-term false signal rate. Chart performance was then judged according to the expected number of patients treated until a change in rate was detected.ResultsFor large absolute increases in rates (>10%), the Shewhart p-chart and EWMA both had good performance, although not quite as good as the CUSUM. For small absolute increases (<10%), the CUSUM detected changes more rapidly. The g-chart is designed to efficiently detect decreases in low event rates, but it again had less good performance than the CUSUM.ImplicationsThe Shewhart p-chart is the simplest chart to implement and interpret, and performs well for detecting large changes, which may be useful for monitoring processes of care. The g-chart is a useful complement for determining the success of initiatives to reduce low-event rates (eg, adverse events). The CUSUM may be particularly useful for faster detection of problems with patient safety leading to increases in adverse event rates.

Robotic-Assisted Roux-en-Y Gastric Bypass: Learning Curve Assessment Using Cumulative Sum and Literature Review

“…For this series, the learning curve was assessed by the CUSUM. 16 The portion of the curve where the maximal change in slope begins to decrease signifies the completion of the learning curve. 17 The outcome used for the learning curve was the total operative time, starting from skin incision until skin closure.…”

EWMA Control Charts and an Overview of Usage in Health

“…Yöntemler hakkında geniş bir literatür olmasına rağmen çizelgelerin sistematik olarak karşılaştırıldığı az sayıda çalışma bulunmaktadır. 17 ÜSSEL AĞIRLIKLI HAREKETLİ ORTALAMA ÇİZELGESİ İlk kez Roberts (1959) tarafından ileri sürülen EWMA çizelgesi, günümüzde pratikte çok sayıda uygulamada kullanılan en popüler kontrol çizelgelerinden biridir. EWMA çizelgesinin uygulanması basittir ve küçük değişimleri tespit etmek için Shewhart çizelgesinden daha etkili olduğu kabul edilmiştir.…”

“…Yöntemler hakkınd literatür olmasına rağmen çizelgelerin sistematik olarak karşılaştırıldığı az sayı bulunmaktadır. 17…”

“…Ayrıca 'nin değerinin büyümesi EWMA izinin değişime daha hızlı tepki vermesini sağlar. 17 Tıbbi evrim ve dünyadaki artan yaşam kalitesi, yaşam süresinin uzamasına yol açmıştır. Kontrol çizelgeleri ile süreç izleme, sağlık hizmetlerinde genel bir süreç değerlendirme ve iyileştirme çerçevesi içinde önemli bir bileşendir.…”

On the Effect of Estimation Error for the Risk-Adjusted Charts

“…Steiner et al [16] proposed a new CUSUM method for accounting preoperative risk or surgical failure through the use of the likelihood-based weighted scheme. Some more recent work on risk-adjusted charts can be seen in [17][18][19][20][21][22][23][24][25][26][27] and references cited therein.…”