Permissioned Blockchain Network for Proactive Access Control to Electronic Health Records

Abstract

Abstract Background As digital healthcare services handle increasingly more sensitive health data, robust access control methods are required. Especially in emergency conditions, where the patient’s health situation is in peril, different healthcare providers associated with critical cases may need to be granted permission to acquire access to Electronic Health Records (EHRs) of patients. The research objective of our work is to develop a proactive access control method that can grant emergency clinicians access to sensitive health data, guaranteeing the integrity and security of the data, and generating trust without the need for a trusted third party.Methods To enable proactivity, we apply Long Short Term Memory (LSTM) Neural Networks (NNs) that utilize patient’s recent health history to prognose the next two-hour health metrics values. Fuzzy logic is used to evaluate the severity of the patient’s health state. These techniques are incorporated in a private and permissioned Hyperledger-Fabric blockchain network, capable of securing patient’s sensitive information in the blockchain network.Results Integrating this predictive mechanism within the blockchain network proved to be a robust tool to enhance the performance of the access control mechanism. Furthermore, our blockchain network can record the history of who and when had access to a specific patient’s sensitive EHRs, guaranteeing the integrity and security of the data.Conclusions Our proposed mechanism informs proactively the emergency team about patients’ critical situations by combining fuzzy and predictive techniques, and it exploits the distributed data of the blockchain network, guaranteeing the integrity and security of the data, and enhancing the users’ trust to the mechanism.