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Provenance in Distr. Organ Transplant Management Applying Provenance in Distributed Organ Management Sergio Álvarez, Javier Vázquez-Salceda, Tamás Kifor,

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Presentation on theme: "Provenance in Distr. Organ Transplant Management Applying Provenance in Distributed Organ Management Sergio Álvarez, Javier Vázquez-Salceda, Tamás Kifor,"— Presentation transcript:

1 Provenance in Distr. Organ Transplant Management Applying Provenance in Distributed Organ Management Sergio Álvarez, Javier Vázquez-Salceda, Tamás Kifor, László Z. Varga, Steven Willmott

2 OTM application 2 Contents Problem Domain Provenance handling in the OTM Application Provenance representation Provenance questions Issues to solve An example Conclusions

3 Provenance in Distr. Organ Transplant Management Problem Domain

4 OTM application 4 Problem Domain distributed medical applications In distributed medical applications the following information is split into different administration domains (islands of information) medical data The medical data (HC history of patients) workflows The workflows (of the corresponding processes carried out to patients) logs The logs (recording meaningful events) integrated viewfor workflows and logs is needed An integrated view, not only for data but also for workflows and logs is needed To have an integrated view of a patient’s treatment across all institutions To analyse the performance of distributed HC services to detect problems to solve To carry out audits of the system, if requested by medical or legal authorities.

5 OTM application 5 Problem Domain Need: to trace back originsdecisionsprocesses The origins of (medical) decisions and processes information available The (medical) information available a each step originsinformation The origins of such information provenance_aware Idea: make the distributed medical system provenance_aware Our def: “Provenance of a piece of data is the process that lead to the data” provenance-based logging services Convert standard logs into provenance-based logging services capable to record information about the workflow execution and the data, and their provenance. Adapt the medical systems Adapt the medical systems to provide provenance information. tools to properly reconstruct Have tools to properly reconstruct the full provenance of data

6 OTM application 6 Hospital D Lab_1 Lab_2 Lab_3 Hospital A (donor side) Hospital B (recipient side)Hospital C Lab_ALab_B OTA General Practice Center Transplant Unit General Practice Center WL EHCR

7 Provenance in Distr. Organ Transplant Management Provenance Handling in the OTM Application

8 OTM application 8 Provenance representation Provenance architecture from EU PROVENANCE service In OTM, each organisational unit is represented by a service. GUI interface Staff connect to the unit’s service through a GUI interface actorsmessages Services are seen as actors exchanging messages p-assertions Provenance of data represented by p-assertions: Interaction p-assertionsInteraction p-assertions (about contents of messages) Relationship p-assertionsRelationship p-assertions (about relation between an actor’s input and output messages) Actor-state p-assertionsActor-state p-assertions (about actor’s internal state in the context of an interaction) provenance stores P-assertions are stored and organised inside provenance stores.

9 OTM application 9 Provenance questions Examples of types of queries Where did the medical information used in step X came from? Which medical actor was the source of information A? When a given medical process was carried out? Who was responsible for a given medical process? When decision Y was taken? What was the bases for decision Y? Which medical actors were involved in the decision? Which medical actor refused to provide medical data for a decision?

10 OTM application 10 Issues to solve not a computational servicereal people in the real world The provenance of most of data is not a computational service, but decisions and actions carried out by real people in the real world. enough information minimise interference Make sure the electronic system gets enough information from the real processes but trying to minimise interference to medical actors. Past treatments may be relevant Past treatments of a given patient in other institutions may be relevant to, e.g., current decision in current institution connected somehow to current p- assertions p-assertions about the processes underwent in previous treatments should be connected somehow to current p- assertions Securityprivacy Security and privacy issues

11 OTM application 11 Transplant Unit User Interface Test Lab. User Interface EHCR Hospital A OTM Donor Data Collector TU.1 Data Collection request TU.2 Serology Test request TU.3 Brain Death Notification + report TU.4 Decision request TU.5 Decision + report EHCR Hospital B OTM.1 Donor Data request OTM.2 Donor Data HC.1 Patient Data request HC.2 Patient Data OTM.3 Serology test request OTM.4 Serology test result + report An Example

12 OTM application 12 Author A authored by Author C authored by Author B authored by User X is logged in User Z is logged in User X is logged in User W is logged in User Y is logged in caused by Serology Test Request TU.2 justified by Brain Death report TU.3 response to Decision Request TU.4 Donation Decision TU.5 caused by response to Data Collection Request TU.1 Donor Data Request OTM.1 caused by response to contains parts of Patient Data Request HC.1 Patient Data Hospital B HC.2 response to Serology Test Request OTM.3 caused by Decision report TU.5 justified by based on based on based on Brain Death Notification TU.3 Donor Data OTM.2 Serology Test Result OTM.4 caused by justified by Serology report OTM.4

13 OTM application 13

14 Provenance in Distr. Organ Transplant Management Conclusions and ongoing work

15 OTM application 15 Conclusions and future work provenancedistributed medical systems We present an application of provenance in distributed medical systems Distributed allocation of human organs Domain: Distributed allocation of human organs for transplantation purposes Provenance useful to trace back trace back the origin of medical decisions provide an integrated view provide an integrated view of a patient’s treatment Issues electronicreal Connect an electronic computational process with real world past and current Connect past and current electronic computational processes building a full demonstrator Currently building a full demonstrator for the Catalan OTA as a use case for EU PROVENANCE Evaluation Evaluation is planned with some hospital and transplant coordinators in the Barcelona area.

16 OTM application 16 EU PROVENANCE project IBM United Kingdom Limited University of Southampton University of Wales, Cardiff Deutsches Zentrum fur Luft- und Raumfahrt s.V Universitat Politècnica de Catalunya MTA SZTAKI


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