Phase I risk-adjusted Bernoulli chart in multistage healthcare processes based on the state-space model

Healthcare processes comprise multiple stages in practice. Also, few researchers have addressed Phase I monitoring of healthcare outcomes. Hence, the purpose of the proposed method is Phase I monitoring by two risk adjusted control charts in multistage healthcare processes. The proposed control char...

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Bibliographic Details
Published in:Journal of statistical computation and simulation Vol. 91; no. 3; pp. 522 - 542
Main Authors: Sogandi, Fatemeh, Aminnayeri, Majid, Mohammadpour, Adel, Amiri, Amirhossein
Format: Journal Article
Language:English
Published: Abingdon Taylor & Francis 11.02.2021
Taylor & Francis Ltd
Subjects:
Algorithms
Bernoulli state-space model
Control charts
expectation-maximization algorithm
Health care
Kalman filter and smoother
Kalman filters
Likelihood ratio
Monitoring
multistage healthcare processes
Parameter estimation
Phase I
Risk management
State space models
Telemedicine
Test methods
ISSN:0094-9655, 1563-5163
Online Access:Get full text
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Summary:Healthcare processes comprise multiple stages in practice. Also, few researchers have addressed Phase I monitoring of healthcare outcomes. Hence, the purpose of the proposed method is Phase I monitoring by two risk adjusted control charts in multistage healthcare processes. The proposed control charts are based on the Bernoulli state space model and consider other categorical covariates in addition to patient's risk. To estimate the model parameters, an expectation-maximization algorithm is applied in a Kalman filter and smoother framework. The performance of the proposed monitoring schemes is compared in two and three stages. The simulation results show that the standardized likelihood ratio test method has competitive performance relative to Hotelling's chart under different step shifts and drift. Also, Hotelling's chart is superior to the standardized likelihood ratio test method in for outlier patients. Finally, a real case is utilized to show the applicability of the proposed risk adjusted charts.
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ISSN:0094-9655
1563-5163
DOI:10.1080/00949655.2020.1820503