Markov chain‐based cost‐optimal control charts for health care data
نویسندگان
چکیده
منابع مشابه
Control charts for health care monitoring: the heterogeneous case
Attribute data from high quality processes can be monitored adequately by using negative binomial charts. The optimal choice for the number r of failures involved depends on the expected rate of change in failure rate during Out-of-Control. To begin with, such results have been obtained for the case of homogeneous data. But especially in health care monitoring, (groups of) patients will often s...
متن کاملControl charts for health care monitoring under overdispersion
An attractive way to control attribute data from high quality processes is to wait till r ≥ 1 failures have occurred. The choice of r in such negative binomial charts is dictated by how much the failure rate is supposed to change during Outof-Control. However, these results have been derived for the case of homogeneous data. Especially in health care monitoring, (groups of) patients will often ...
متن کاملRisk-Adjusted Control Charts for Health Care Monitoring
Attribute data from high quality processes can be monitored effectively by deciding on whether or not to stop at each time where r ≥ 1 failures have occurred. The smaller the degree of change in failure rate during Out-of-Control one wants to be optimally protected against, the larger r should be. Under homogeneity, the distribution involved is negative binomial. However, in health care monitor...
متن کاملRisk-adjusted control charts based on LR-fuzzy data
Control charts are widely used in industrial processes as well as in health sciences and particularly for monitoring the performance of cardiac surgeon or a group of surgeons based on the preoperative risk of patients. Since the preoperative risk is a vague and nonprecise variable and the anesthesiologists after checking how many risk factors a patient has, determine the risk of mortality befor...
متن کاملRobust control charts for time series data
This article presents a control chart for time series data, based on the one-stepahead forecast errors of the Holt-Winters forecasting method. We use robust techniques to prevent that outliers affect the estimation of the control limits of the chart. Moreover, robustness is important to maintain the reliability of the control chart after the occurrence of alarm observations. The properties of t...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Quality and Reliability Engineering International
سال: 2019
ISSN: 0748-8017,1099-1638
DOI: 10.1002/qre.2518