ENBIS-18 in Nancy

2 – 25 September 2018; Ecoles des Mines, Nancy (France) Abstract submission: 20 December 2017 – 4 June 2018

Variance-Sensitive Cost-Optimal Control Charts for Healthcare Data

3 September 2018, 14:40 – 15:00


Submitted by
András Zempléni
András Zempléni (Eötvös Loránd University, Budapest), Balázs Dobi (Eötvös Loránd University)
Recently [1], we developed a Markov chain-based method for the economically optimal design of Shewhart-type control charts, which is suitable for real-life medical applications. In this model not only the shift size (i.e. the degradation of the patient's health) can be random, but the sampling interval (due to possible noncompliance) and the effect of the repair (i.e. treatment) too.
Further developing the method, we introduce a target function to be minimised, which also incorporates the variance 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 investigate the sensitivity of the optimal parameters (the critical value and the sampling interval), and the resulting average cost and cost variance 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.
[1] B. Dobi, A. Zempléni, Cost-optimal Control Charts for Healthcare Data. 17th Annual Conference of the European Network for Business and Industrial Statistics, Naples, 2017.
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