## 4 Research Efforts
### Cloud-based Storage Solutions, HIT Applications and Systems  
There has been some work carried out in designing storage and file management systems for e-Health Cloud. [PERSON] _et al._[53] proposed a Cloud-based intelligent hospital file management system (HFMS) that aims to improve some of the limitations which characterize the traditional hospital management systems (HMS). Such limitations include limited storage capacity of some of the hardware devices and slow performance of the hardware due to the huge amount of data, the backup models, and the resource sharing across different platforms. The proposed Cloud-based HFMS consists of a master server and multiple blocks of servers. Large files are divided into fixed-sized blocks and each block is backed up by three blocks. The master server manages the file system meta-data that includes namespace, access control, file-block mapping and physical address of relevant information. This model is claimed to adopt low-cost server clusters with the flexibility to allow the applications to overcome the physical boundaries, maximizing the utilization of total systems resources as needed.  
[PERSON] _et al._[54] proposed to store patients' data in the Cloud to meet the growing demands of storage space for EMR and at the same time to fulfill the significant requirements for data security and privacy protection. The proposed method suggests storing distributed EMR at a local storage system and other two different commercial clouds using the algorithm of RAID 3 (redundant array of inexpensive/independent disks). Using RAID 3, the segmented data stored in each Cloud will be meaningless and useless. To ensure the integrity of data upload and download, a cryptographic hash function (MD5: Message-Digest algorithm 5) is used in association with RAID-3.  
[PERSON] _et al._[15] provided a long term off-site medical image archive solution for digital imaging and communication in medicine (DICOM). One of the biggest challenges which the healthcare industry struggles with, is the growing cost of managing long-term onsite medical imaging archives. The continually increasing need for high volumes of medical images is resulting in scalability and maintenance issues with picture archiving and communication systems (PACS). The tools and functionalities of the Windows Azure Cloud platform were used to develop and deploy the prototype of DICOM image archive service. The prototype system was tested with a variety of public domain DICOM images. The tested image series were successfully sent from clients, received and indexed by the server in the Cloud, retrieved as requested in queries and returned. With the rich features and supports of Azure, the system has the potential to reduce the cost of image archives storage and management and to enhance the disaster recovery capabilities.  
In addition, [PERSON] _et al._[55] proposed a solution to automate the process of patients' critical data collection, distribution and processing. This is to reduce manual efforts, eliminate typing errors, and improve patients' data accessibility. The proposed automatic solution uses a network of sensorsconnected to legacy medical devices to collect patients' vital data and deliver it to the e-Health Cloud for storage, processing, and distribution. Finally, a group developed a cloud-based Early Warning Service (EWS) [56] that enables the simulation of patients' data. EWS has the potential of fully automating the process of calculating the patient's risk index by capturing vital signs using medical sensors, transmitting the captured values to data buckets in the Cloud, constantly monitoring the patient's status, and notifying clinicians by calling or messaging their mobile phones when necessary.