Care maps: distributed semantic healthcare workflows
CARE MAPS:DISTRIBUTED SEMANTICHEALTHCAREWORKFLOWSDaniel Aronne ~ George Mason University ~2011
Objective How to provide patients with a seamless healthcare treatment environment? A holistic approach.
Healthcare Industry A highly dynamic industry in a very complex environment. Multiple stakeholders spanning multiple organizations and geographical locations: Laboratories Physicians Clinics Pharmacies Insurance Companies Federal Agencies The Patient Himself!
Healthcare Industry Stakeholders Pharmaceutical Manufacturers Payers/ Medical Devices Regulators Biotech Distributor/ Employer Wholesaler Other Payer Outpatient LTC Facilities Hospitals Regulatory Physicians Agency Integrate d Networks Providers PatientsAHRQ 2007 Annual Conference Presentation: http://www.ahrq.gov/about/annualmtg07/0927slides/juhn/Juhn-contents.html
Current Challenges and Issues Interaction Intra-organizationaland Inter-organizational Orchestration vs. choreography Integration Service discovery and matching Adaptability Adaptive medical workflows Quality of Service (QoS) Reliability, availability, scalability, error handling
Current Challenges and Issues Localization Local jurisdiction requirements Usability How much user interaction? Behavioral A human driven industry How much should we automate without human intervention?
Care Maps A roadmap of a patient’s journey. Consists of a series of steps and decisions points in the management of a condition. Is usually based on medical guidelines, recent evidence and expert consensus. Patient centered.
Multi-Agent Systems Have been recognized as a technology to efficiently build complex systems. Suitable for describing the coordinating and negotiating nature of healthcare service providers and consumers.
Multi-Agent Systems Previous works have demonstrated the added values of agent-based systems in healthcare, and specifically in healthcare workflows : Reusability Reliability Flexibility Robustness Maintainability Adaptability
Multi-Agent Systems Added values (continued): Support the integration of legacy systems Tackle the shortcomings of centralized systems such as: performance bottlenecks resource limitations other kinds of failures
Multi-Agent Systems Shortcomings: Most of the systems are only prototypes. Most are not widely deployed in real environments. Further study is required.
Decentralized WorkflowExecution Supports the dynamic nature of the healthcare industry Ad-hoc adaptation to changing conditions at runtime. Run-time process fragmentation and process migration.
Decentralized Workflow Execution • Process fragmentation vs process migration.Zaplata, Sonja, Kristof Hamann, Kristian Kottke, and Winfried Lamersdorf. "Flexible Execution of Distributed BusinessProcesses Based on Process Instance Migration." Journal of Systems Integration 1.3 (2010): 3-16.
Decentralized WorkflowExecution Enhance existing processes with non-intrusive migration data. Non-modifying annotation of process descriptions: migration meta-model. All potential participants have to provide a compliant interface in order to receive process descriptions from preceding process engines (e.g. XPDL, WS-BPEL) Support encryption and decryption of process fragments and/or migration data for security and privacy purposes.
Distributed Directory Service Inspiration from: Domain Name System (DNS) Namespace hierarchy Authoritative servers Replication P2P protocols (i.e. Bit Torrent) Queryrouting Network overlays No single point of failure, better reliability Scalable
Semantic Matchmaking Match service providers and service consumers. Compute syntactical and semantic similarity among service capability descriptions. Requires use of a semantic model (e.g. ontology) to describe service descriptions.
Proposed frameworkA distributed semantic workflowmanagement, multi-agent system approach
Decentralized Directory Service (DDS):• Resource and service discovery.• Provides support for: • Semantic querying. • Federated query. • Security.• Solves JADE centralized DF.
Healthcare Entity Agent (HEA):• Storefront representative of any healthcareservice provider.• Initiates execution of process instances.• Allocates process fragments to other healthcareentities .• Executes process fragments.• Can migrate process instances to other entities.• Interacts with any BPM engine that supports astandardized workflow definition format (i.e.XPDL).
Broker Agent (BA):• Semantic matchmaker:Matches service requests withservice providers.• Queries local Directory ServiceOntology which containssemantic service descriptions.• If no suitable match, requeststhe Directory Service Agent toroute his query to otherDirectory Services.
Directory Service Agent (DSA)• Storefront for the DirectoryService.• Handles new ServiceProviders registration.• Propagates newly registeredSPs to other Directory Servicenodes.• Routes queries to other BA inthe Distributed DirectoryService.
User Agent (UA)• Acts on behalf of a human person• May be delegated atomic tasks.• May reside in a desktop computer or in amobile device.
Future Work A prototype to test these concepts. Address security and privacy concerns.
References  D. Alexandrou and G. Mentzas. “Research Challenges for Achieving Healthcare Business Process Interoperability”, in Proceedings of the 2009 International Conference on eHealth, Telemedicine, and Social Medicine, ETELEMED 09, IEEE Computer Society.  J. Emanuele and L. Koetter, "Workflow Opportunities and Challenges in Healthcare", in 2007 BPM & Workflow Handbook, 2007.  Song, X., Hwong, B., Matos, G., Rudorfer, A., Nelson, C., Han, M., Girenkov, A., “Understanding Requirements for Computer-aided Healthcare Workflows: Experience and Challenges”, in Proceeding of the 28th international conference on Software engineering, ICSE’06, ACM Press.  Wei Tan, Yushun Fan, "Decentralized Workflow Execution for Virtual Enterprises in Grid Environment," Grid and Cooperative Computing Workshops, International Conference on, pp. 308-314, Fifth International Conference on Grid and Cooperative Computing Workshops, 2006  J. Dang, A. Hedayati, K. Hampel, and C. Toklu. “An ontological knowledge framework for adaptive medical workflow”. Journal of Biomedical Informatics, 41(5):829–836, October 2008.  Z. Maraikar. “Resource and service discovery for mobile agent platforms”. Master’s thesis, Department of Computer Science, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands, August 2006  Zaplata, Sonja, Kristof Hamann, Kristian Kottke, and Winfried Lamersdorf. "Flexible Execution of Distributed Business Processes Based on Process Instance Migration." Journal of Systems Integration 1.3 (2010): 3-16. Print.  Huser, Vojtech, Luke Rasmussen, and Justin Starren. "Representing Clinical Processes in XML Process Definition Language (XPDL)." Web.  Isern, David, David Sanchez, and Antonio Moreno. "Agents Applied in Health Care: A Review."