title: Dynamic probability control limits for risk-adjusted Bernoulli CUSUM charts.
abstract: The risk-adjusted Bernoulli cumulative sum (CUSUM) chart developed by Steiner et al. (2000) is an increasingly popular tool for monitoring clinical and surgical performance. In practice, however, the use of a fixed control limit for the chart leads to a quite variable in-control average run length performance for patient populations with different risk score distributions. To overcome this problem, we determine simulation-based dynamic probability control limits (DPCLs) patient-by-patient for the risk-adjusted Bernoulli CUSUM charts. By maintaining the probability of a false alarm at a constant level conditional on no false alarm for previous observations, our risk-adjusted CUSUM charts with DPCLs have consistent in-control performance at the desired level with approximately geometrically distributed run lengths. Our simulation results demonstrate that our method does not rely on any information or assumptions about the patients' risk distributions. The use of DPCLs for risk-adjusted Bernoulli CUSUM charts allows each chart to be designed for the corresponding particular sequence of patients for a surgeon or hospital.
authors.affiliation: Department of Statistics, Virginia Tech, Blacksburg, VA, U.S.A.
authors.forename: Xiang
authors.initials: X
authors.lastname: Zhang
authors.affiliation: Department of Statistics, Virginia Tech, Blacksburg, VA, U.S.A.
authors.forename: William H
authors.initials: WH
authors.lastname: Woodall
mesh_terms: D016010:Binomial Distribution; D003198:Computer Simulation; D006302:Health Services Research / Q000379:methods*; D006801:Humans; D016015:Logistic Models; D015233:Models, Statistical; D011336:Probability; D020379:Risk Adjustment / Q000379:methods*; D066231:Surgeons
keywords: average run length (ARL); false alarm rate; run length distribution; statistical process control; surgical performance