Alerting patients via health information system considering trust-dependent patient adherence

The internet of things has ushered in a world of possibilities in chronic disease management. Connected to the health information network, a health device can monitor and provide intervention recommendations to patients in real time. However, this new health information system may face the risk of patients not following the system's recommendations depending on their perception of the system. In this paper, we consider patients' trust in the system a key factor driving their adherence to the system's recommendation and develop an analytical model to design the optimal alerting strategy in the context of asthma management. Our method acknowledges that patient's trust may change over time based on their experience of using the system, which may influence their future adherence behavior. We derive a set of structural properties of our solution and demonstrate that our approach can significantly improve patients' quality of life compared to the current practice of asthma management. Furthermore, we investigate various real-world scenarios, such as the case that patients may have different level of tolerance for receiving alerts. Based on our findings, valuable insights can be shared with patients, healthcare practitioners, and companies in the technology-enabled healthcare business sector.

Automated summary

This paper explores how patients' trust in the health information system in the IoT era affects their adherence to system recommendations, aiming to improve asthma management by designing optimal alerting strategies. The study concludes that patient trust can change over time based on experience, influencing future adherence behavior. The approach significantly enhances patients' quality of life and provides valuable insights for patients, healthcare practitioners, and technology-enabled healthcare companies.