A Continuous‐Time Markov Chain Model–Based Business Analytics Approach for Estimating Patient Transition States in Online Health Infomediary

ABSTRACT Online health infomediaries are emerging as a critical element in the healthcare sector to support and influence individuals’ health and wellness decisions. The business success and effectiveness of health infomediaries depend on the active and sustained engagement of patients. Although the...

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Veröffentlicht in:	Decision sciences 2020-02, Vol.51 (1), p.181-208
Hauptverfasser:	Lim, Sanghee, Yim, Dobin, Khuntia, Jiban, Tanniru, Mohan
Format:	Artikel
Sprache:	eng
Schlagworte:	Business analytics Churn Rate Decisions Health Health care Health care industry Infomediary Markov analysis Markov chains Markov Model Modelling Online data bases Patient Engagement Patients Plastic surgery Reconstructive surgery Robustness Surgery Transition probabilities User behavior Workflow
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