## 5 Opportunities and Future Directions
* RQ4: State-of-the-art techniques that integrate blockchain and AI have demonstrated their relevance in improving the efficiency of HIE systems, particularly in terms of security and privacy. While blockchain and AI technologies show the potential to revolutionize HIE systems, challenges such as applicability, complexity, scalability, interoperability, regulatory and legal implications, security risks, implementation cost, and human factor must be acknowledged. We believe that the future of the SSHIE is more promising with the integration of more emerging technologies such as big data analytics, edge/fog computing, 5G, IoT, digital twins, and others that can advance the capabilities of AI and blockchain and ensure patient outcomes while increasing efficiency and profitability. Thus, to answer RQ5, we provide a long-term vision for the evolution of smart and secure HIE systems aiming to enhance their efficiency and performance. * Big data analytics: The healthcare sector is one of the largest contributors of big data nowadays. Health data are also characterized by their heterogeneity such as numerical for collecting vital signs and image/video for performing patient operations. This leads to complex data storage in the blockchain nodes and huge processing when applying AI models. Recently, big data analytics have demonstrated their potential in handling huge storage and processing of personal health records. Thus, integrating big data analytics into AI-blockchain HIE systems will be two-fold: first, distributed data storage ecosystems, such as Hadoop and Spark, can securely maintain immutable healthcare records in the blockchain networks due the replication transaction process. Second, such systems ensure a distributed processing for data analysis, which can enhance the execution time of AI models. Therefore, designing new systems that integrate big data analytical tools, AI and blockchain will highly enhance the performance of HIE, particularly in terms of security and latency. * Edge/Fog computing: Sharing large volumes of EHRs among diverse healthcare companies is challenging due to network congestion and data size. Current EHR management options are limited by scalability, computing costs, and response times. Edge/fog computing may offer a solution to these challenges by processing vast amounts of data from multiple locations, as it involves a network of servers/computers. Edge/Fog processing provides advantages such as large data storage, extensive networking, and high computing power, while also enabling secure and regulated scaling for distributed EHR applications. Despite its benefits, edge computing has drawbacks, including security vulnerabilities during message transmission and data integrity issues. Blockchain-based solutions also face challenges, such as storage limitations, scalability, block size constraints, and block creation time, which edge computing can address. Combining decentralized technologies can enhance privacy, security, and resource management automatically. For instance, blockchain can implement distributed controls across multiple edge/fog nodes, with the blockchain mining process ensuring the accuracy, consistency, and dependability of data. User privacy can be further enhanced by allowing individuals to control their data using cryptographic keys. Additionally, edge computing enables secure resource sharing across nodes through blockchain-based smart contracts. * Internet of Things (IoT): Connected healthcare has recently emerged as a low-cost solution for healthcare applications. It is a combination of Internet of Things (IoT) and sensor devices that allow continuous monitoring of health-related data for a given patient through bio-medical sensors. By connecting various healthcare entities via a medical device network, IoT allows medical staff to receive real-time health updates from patients in remote locations, avoiding any unnecessary travel to the hospital and reducing the general health care costs.