Paper Number
2460
Paper Type
Complete
Description
The emerging telehealth platforms connect patients with physicians using telecommunication technologies and are transforming the traditional healthcare delivery process. Meanwhile, patient care journeys spreading across online and offline health service channels call for new research methodologies. Using a dataset from a telehealth platform, we develop a novel Poisson-factor-marked Hawkes process to model such a journey and quantify the mutual-modulating effects of various patient activities. Our estimation results demonstrate the disparate impacts of the patient’s health conditions and physician characteristics on choosing care channels. Taking advantage of the self-generation property of our model, we simulate policy and strategic interventions, which highlights the practical value of the proposed model and offers implications for better patient routing and service design for telehealth platforms.
Recommended Citation
Zhang, Quan and Liu, Yixuan, "Understanding Patient Journeys with Telehealth: A Poisson-Factor-Marked Hawkes Process" (2022). ICIS 2022 Proceedings. 21.
https://aisel.aisnet.org/icis2022/is_health/is_health/21
Understanding Patient Journeys with Telehealth: A Poisson-Factor-Marked Hawkes Process
The emerging telehealth platforms connect patients with physicians using telecommunication technologies and are transforming the traditional healthcare delivery process. Meanwhile, patient care journeys spreading across online and offline health service channels call for new research methodologies. Using a dataset from a telehealth platform, we develop a novel Poisson-factor-marked Hawkes process to model such a journey and quantify the mutual-modulating effects of various patient activities. Our estimation results demonstrate the disparate impacts of the patient’s health conditions and physician characteristics on choosing care channels. Taking advantage of the self-generation property of our model, we simulate policy and strategic interventions, which highlights the practical value of the proposed model and offers implications for better patient routing and service design for telehealth platforms.
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Comments
16-HealthCare