How To Build A Cloud Computing And Healthcare Based Platform For A Mobile Health Care System



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Managing Healthcare and Medical Information Utilizing Cloud Computing Charalampos Doukas 1, Ilias Maglogiannis 2, Aristotle Chatziioannou 3 1 University of the Aegean, GR 2 University of Central Greece, GR 3 National Hellenic Research Foundation, GR www.eu-egee.org EGEE and glite are registered trademarks

Overview Concept Introduction Cloud Computing & Healthcare Related Work Proposed Platform Framework Architecture Case Study Conclusions 2

Introduction Vast amount of medical and biological data (medical & biological devices, sensors, contextual data, etc.) Demand for: The availability of e-health applications and medical information anywhere Anytime Invisibility of computing Mobile & modern healthcare technologies support: Telemedicine, Patient & personalized monitoring, Location-based medical services, Emergency response and management, Pervasive access to healthcare information. 3

Introduction Requirements for proper realization: Data storage and management (physical storage & availability issues, maintenance, etc.) Interoperability and availability of heterogeneous resources (heterogeneous data, global access seamlessly) Security and privacy (encryption @ storage & transmission, access control) Unified and ubiquitous access (platforms, infrastructures, interfaces) 4

Introduction Potential solution: Cloud Computing + electronic Healthcare Solutions: Access shared resources Common infrastructure in a ubiquitous and pervasive manner In this context: Pervasive healthcare information management system for mobile devices utilizing: Cloud Computing Android Operating System 5

Cloud Computing & Healthcare Enabling Grids for E-sciencE Cloud Computing: Convenient, on-demand network access to a shared group of configurable computing resources (e.g., networks, servers, storage, applications, and services) Rapidly provisioned and released with minimal management effort or service provider interaction Major Characteristics: On-demand self-service (unilaterally obtain access to computing capabilities) Broad network access Resource pooling Rapid elasticity Measured Service 6

Major Benefits: Cloud Computing & Healthcare Enabling Grids for E-sciencE Agility & re-usability Cost (startup infrastructure, centralization of infrastructure in locations with lower costs, etc..) Multi-tenancy (sharing of resources and costs across a large pool of users) Reliability Security Sustainability & Resources utilization Maintenance Examples of existing Cloud Services: icloud, DropBox, GoGrid, Amazon AWS 7

Related Work Mobile & Virtual Environments in Healthcare Virtual health records and mobile access: Sabine Koch, Maria Hägglund, Isabella Scandurra, Dennis Moström, Towards a virtual health record for mobile home care of elderly citizens, presented in MEDINFO 2004, Amsterdam, 2004. Kumar A., Purandare A., Chen J., Meacham A., and Subramanian, L. 2009. ELMR: lightweight mobile health records. In Proceedings of the 35th SIGMOD international Conference on Management of Data (Providence, Rhode Island, USA, June 29 - July 02, 2009). Alvin T.S. Chan, WWW_smart card: towards a mobile health care management system, International Journal of Medical Informatics 57 (2000) 127 137. 8

Related Work Mobile & Virtual Environments in Healthcare MAPID: Distributed information platform allowing wide-area health information exchange based on mobile agents Chuan Jun Su, Mobile multi-agent based, distributed information platform (MADIP) for wide-area e-health monitoring, Computers in Industry 59 (2008) 55 68. Issues: Based on proprietary architectures and communication schemes Require the deployment of specific software components Focus mostly on delivering data to healthcare applications Do not address: management and interoperability 9

Proposed Platform Main purpose: Provide medical experts and patients with a mobile user interface for managing healthcare information Storing, querying and retrieving medical images (e.g., CT scans, MRIs, US etc.), patient health records and patient-related medical data (e.g., biosignals) Data may reside at a distributed Cloud Storage facility, initially uploaded/stored by medical personnel through a Hospital Information System Communication and data exchange has to be performed through non-proprietary, open and interoperable communication standards 10

Proposed Platform @HealthCloud utilizing Web Services connectivity and Android OS supports the following functionality: Seamless connection to Cloud Computing storage utilizing Web Services and the REST API Patient Health Record Management DICOM image viewing support JPEG2000 viewing support Image annotation support Proper user authentication and data encryption 11

Proposed Platform @HealthCloud: 12

Platform Architecture Major Components: Platform front-end interface Cloud Storage Facilities Cloud Platform Interface Cloud Infrastructure Module 13

Platform Architecture Major Components: The Patient Health Record application The Medical Imaging module Cloud Service Client Android OS 14

Case Study Utilizing Amazon Cloud Computing Service Amazon Simple Storage Service (S3) Commercial well established service Interoperable web interfaces for managing data Ability to create custom applications Suitable for healthcare applications -> HIPAA compliant: privacy rule regulations include standards regarding the encryption of all patient-related data in transmission and in storage. 15

Case Study Technical Details: Android OS 1.6 Implemented on Google (HTC) G1 Initial Evaluation: A number of medical images of different modalities (MR, CT, PET, OT and Ultrasound) WLAN and a commercial 3G Network 16

Conclusions Sharing of medical information resources -> key factor for successful adoption of healthcare systems Cloud Computing can provide means for: Better data storage and management Interoperability Availability Maintenance Security @HealthCloud: Prototype implementation of a mobile healthcare information management system based on Cloud Computing and Android OS Future work: Improve security + real scenario evaluation 17