Automated infection risks assessments (AIRa) for decision-making using a blockchain-based alert system: A case study in a representative building.

Indoor air quality (IAQ) is an important parameter in protecting the occupants of an indoor environment. Previous studies have shown that an indoor environment with poor ventilation increases airborne virus transmission. Existing research has concluded that high ventilation rates can reduce the risk of individuals in indoor environments being infected. However, most existing ventilation systems are designed to be efficient under non-pandemic conditions. Ultimately, indoor environments will become hotspots for the transmission of airborne viruses. Current infection risk assessments can estimate virus transmission via airborne routes, but with limited information sharing among stakeholders. Our own research did not identify any systems that integrate risk assessments with smart sensors in order to support information sharing with experts in indoor environments in their decision-making process. To fill this gap, we designed a blockchain-based prototype (AIRa) that integrates CO2 smart sensor data with infection risk assessments from a post-pandemic perspective. This system generates two types of alerts: (1) P-Alert and (2) R0-Alert for decision-making by building owners, such as increasing the ventilation rate or track and trace, as needed. AIRa shows various benefits over three existing infection-control alert systems. Our solution stores and shares information such as the timestamp and room number, instead of storing building user's personal information. Our approach does not require a QR code to be scanned or a mobile app to be downloaded in order to enable track and trace. However, AIRa is still an early prototype for evaluating the risks of airborne virus transmission in smart building environments. Multidisciplinary knowledge and technological research will be vital in formulating different alerts in the future.

Reducing Alert Fatigue by Sharing Low-Level Alerts With Patients and Enhancing Collaborative Decision Making Using Blockchain Technology: Scoping Review and Proposed Framework (MedAlert).

BACKGROUND: Clinical decision support (CDS) is a tool that helps clinicians in decision making by generating clinical alerts to supplement their previous knowledge and experience. However, CDS generates a high volume of irrelevant alerts, resulting in alert fatigue among clinicians. Alert fatigue is the mental state of alerts consuming too much time and mental energy, which often results in relevant alerts being overridden unjustifiably, along with clinically irrelevant ones. Consequently, clinicians become less responsive to important alerts, which opens the door to medication errors. OBJECTIVE: This study aims to explore how a blockchain-based solution can reduce alert fatigue through collaborative alert sharing in the health sector, thus improving overall health care quality for both patients and clinicians. METHODS: We have designed a 4-step approach to answer this research question. First, we identified five potential challenges based on the published literature through a scoping review. Second, a framework is designed to reduce alert fatigue by addressing the identified challenges with different digital components. Third, an evaluation is made by comparing MedAlert with other proposed solutions. Finally, the limitations and future work are also discussed. RESULTS: Of the 341 academic papers collected, 8 were selected and analyzed. MedAlert securely distributes low-level (nonlife-threatening) clinical alerts to patients, enabling a collaborative clinical decision. Among the solutions in our framework, Hyperledger (private permissioned blockchain) and BankID (federated digital identity management) have been selected to overcome challenges such as data integrity, user identity, and privacy issues. CONCLUSIONS: MedAlert can reduce alert fatigue by attracting the attention of patients and clinicians, instead of solely reducing the total number of alerts. MedAlert offers other advantages, such as ensuring a higher degree of patient privacy and faster transaction times compared with other frameworks. This framework may not be suitable for elderly patients who are not technology savvy or in-patients. Future work in validating this framework based on real health care scenarios is needed to provide the performance evaluations of MedAlert and thus gain support for the better development of this idea.