FREE ENBIS Webinar by Balázs Dobi: "Cost-Optimal Control Charts for Healthcare Data"

20 November 2018; 18:00 – 18:45

Balázs Dobi demonstrates Shewhart-type optimal design by using Markov Chains. The webinar will be moderated by Shirley Coleman.

We present our recently developed Markov chain-based method [1] for the economically optimal design of Shewhart-type control charts, which is suitable for real-life medical applications: we adapted the Markov chain-based approach and developed a method in which not only the shift (i.e. the degradation of the patient’s health) can be random, but the sampling interval (i.e. time between visits) and the effect of the repair (i.e. treatment) too. This means that we do not use the often-present assumption of perfect repair which is usually not applicable for medical treatments. The average cost of the optimal protocol, which consists of the average sampling frequency (i.e. frequency of control visits) and control limits (i.e. optimal medical criteria) can be estimated by the stationary distribution of the Markov chain.

Further developing the method, we introduced a target function to be minimised, which also incorporates the standard deviation of the cost, which is often very important from a process control viewpoint. The resulting model requires several parameters to be estimated, and the accuracy of these estimations may have a significant effect on the results. Because of this, we investigated the sensitivity of the optimal parameters (the critical value and the sampling interval), and the resulting average cost and cost standard deviation on different parameter values. We demonstrate the usefulness of the approach for real-life data of patients treated in Hungary – e.g. monitoring the cholesterol level of patients with cardiovascular event risk.

Reference
[1] A. Zempléni, B. Dobi, Variance-Sensitive Cost-Optimal Control Charts for Healthcare Data. 18th Annual Conference of the European Network for Business and Industrial Statistics, Nancy, 2018.