SALUS D2.3.2 Report on IPR Management (a) Final …SALUS-FP7-287800• D2.3.2 Final version...

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SALUS-FP7-287800• D2.3.2 Final version 31/01/2014 of 21

SALUS “Scalable, Standard based Interoperability Framework for

Sustainable Proactive Post Market Safety Studies”

SPECIFIC TARGETED RESEARCH PROJECT PRIORITY Objective ICT-2011.5.3b Tools and environments enabling the re-use of electronic health records

SALUS D2.3.2 Report on Intellectual Property Management (a)

Due Date: January 31, 2014 Actual Submission Date: January 31, 2014 Project Dates: Project Start Date : February 01, 2012

Project End Date : January 31, 2015 Project Duration : 36 months

Deliverable Leader: Agfa HealthCare

Project co-funded by the European Commission within the Seventh Framework Programme (2007-2013)

Dissemination Level PU Public X PP Restricted to other programme participants (including the Commission Services) RE Restricted to a group specified by the consortium (including the Commission Services) CO Confidential, only for members of the consortium (including the Commission Services)

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Document History: Version Date Changes From Review

V0.1 December 3, 2013 First Draft Agfa Consortium

V0.2 December 5, 2013 OFFIS confirmed that the document is still up to date

Marco Eichelberg AGFA

V0.3 December 09, 2013 SRDC update Gokce Banu Laleci Erturkmen

AGFA

• V0,4

December 13, 2013 INSERM confirmed that the document is still up to date and ERS update

Gunnar Declerck René Schippers

AGFA

V0.5 December 18, 2013 UMC input Hanna Lindroos AGFA

V0.6 January 10, 2014 ERS update René Schippers AGFA

V0.7 January 15, 2014 Final version with update LISPA contact

Sara Facchinetti Consortium

V1.0 January 31. 2014 Further UMC input Hanna Lindros Consortium

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Contributors (Benef.) Dirk Colaert (AGFA) Kristof Depraetere (AGFA) Jos De Roo (AGFA) Gerard Freriks (ERS) René Schippers (ERS) Jos Devlies (EUROREC) Sajjad Hussain (INSERM) Sara Facchinetti (LISPA) Marco Eichelberg (OFFIS) Frerk Müller (OFFIS) Gokce Banu Laleci Erturkmen (SRDC) Tomas Bergvall (UMC)

Responsible Author Dirk Colaert Email [email protected]

Beneficiary Agfa Phone +32 3444 8408

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SALUS Consortium Contacts:

Beneficiary Name Phone Fax E-Mail SRDC Gokce Banu Laleci

Erturkmen +90 312 2101763 +90(312)2101837 [email protected]

EUROREC Georges De Moor +32 9 2101161 +32 9 3313350 [email protected] UMC Niklas Norén +4618656060 +46 18 65 60 80 [email protected] OFFIS Wilfried Thoben

+49 441 9722131

+49 441 9722111

[email protected]

AGFA Dirk Colaert +32 3 4448408 +32 3 444 8401 [email protected] ERS Gerard Freriks +31 620347088 +31 847371789 [email protected] LISPA Davide Rovera +3902393311

+39 02 39331207 [email protected]

INSERM Marie-Christine Jaulent +33142346983 +33153109201 [email protected]

TUD Peter Schwarz +49 351 458 2715 +49 351 458 7319 [email protected]

ROCHE Jamie Robinson +41 61 687 9433 +41 61 68 88412 [email protected]

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Table of contents

TABLE OF CONTENTS ......................................................................................................................... 5 1. INTRODUCTION ......................................................................................................................... 6

1.1 WHAT IS NEW IN THIS VERSION? .................................................................................................. 6 1.2 CONTENT OF THIS IPR AGREEMENT DOCUMENT ......................................................................... 6 1.3 DESCRIPTION TASK 2.3 MANAGEMENT OF INNOVATION AND INTELLECTUAL PROPERTY ......... 6

2. OVERVIEW OF THE IP CLAIMS ............................................................................................ 7 2.1 BACKGROUND CLAIMS ................................................................................................................. 7

2.1.1 Partner: SRDC ..................................................................................................................... 7 2.1.2 Partner: Roche ..................................................................................................................... 7 2.1.3 Partner: LISPA ..................................................................................................................... 7 2.1.4 Partner: TUD ....................................................................................................................... 7 2.1.5 Partner: OFFIS .................................................................................................................... 7 2.1.6 Partner: EuroRec ................................................................................................................. 8 2.1.7 Partner: ERS ......................................................................................................................... 8 2.1.8 Partner: Agfa ........................................................................................................................ 9 2.1.9 Partner: UMC ....................................................................................................................... 9 2.1.10 Partner: INSERM ............................................................................................................... 10

2.2 FOREGROUND CLAIMS ................................................................................................................ 11 2.2.1 Open source: decision on the approach ............................................................................. 11 2.2.2 The Use Cases/scenario’s ................................................................................................... 11 2.2.3 What will be open source? .................................................................................................. 14 2.2.4 How will the open source modules be organised? ............................................................. 20

CONCLUSION ....................................................................................................................................... 20

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1. INTRODUCTION

1.1 What is new in this version?

This version of the IPR document is conceived as an extension of the first version. As most of the content was already in the first document not so much content is added. For the reader’s convenience we have marked new content with a bar at the left side of the text. On top of this, section 2.2 (Foreground claims and open source) has been completed and corrected here and there, The changes or extensions can be summarized as follows:

1- Background IP: only a small change from ERS 2- Foreground IP: the list of SALUS results and software components are updated to the

current status of the technical work. Further, the SALUS use cases are decomposed in a concrete list of software components

3- Small changes have been made on the partner’s contributions and IP-plans, making the document more accurate and aligned with the actual technical work done.

4- Lastly, the consortium made a decision as to how it wants to publish the software code of the components defined as open source.

This document doesn’t contain everything related to IPR. Both the Commercial Exploitation Plan (D2.1.*) and the Non-Commercial Exploitation Plan (D2.2.*) are related to it as well. We refer to these deliverables rather than copying the content in the current document.

1.2 Content of this IPR Agreement document

In this document we listed the brought-in background IP and our approach for foreground IP. As the project proceeds, we start having a better idea on which components the SALUS project will create. As the Description of Work and the Consortium Agreement are quite clear about the IPR approach in SALUS, we refer to them for full details. On a high level, we can summarize the IPR-related paragraphs as follows:

- Each partner can bring in own IP into the project (=background IP). This IP remains the entire property of the specific partner. However, this IP will be made available to other partners if needed for the project and within the scope of the project. After the project this IP can be licensed to a partner wanting to use it. This is subject to a separate bilateral negotiation, outside the context of the consortium.

- ÌP generated by the project is shared by the contributing partners. They can decide to which degree this IP will be shared or made public. In the DoW a specific list indicates the level of “public-ness” of the project deliverables. Not all of the software modules made in this project are explicitly mentioned in this list. In this document the reader will find a more elaborate list, based on the work and experience so far.

1.3 Description task 2.3 Management of Innovation and Intellectual Property

“The Task Leader Agfa will be in charge of maintaining a schedule of innovation produced during the project and assessing the opportunity for applying for patents or declaring copyrights. First, an initial list of reusable and non-reusable pre-existing know-how (background knowledge) will be available at the start of the project. This list will be a

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living IPR management database during the execution of the project and will be updated with new pre-existing know-how (background) and generated knowledge (foreground) contributions as needed.” Commercial exploitation is covered in a specific deliverable (D2.1.*) as well as non-commercial exploitation such as publication of papers and conferences (D2.2.*).

2. OVERVIEW OF THE IP CLAIMS

In Section 2.1 background IP and in Section 2.2 foreground IP is covered.

2.1 Background claims

In the table below we listed all IPR claims, as agreed in the beginning of the project. This is what the individual partners brought into the project. As much as possible we kept the original wording from the partners input, apart from some minor editorial changes.

2.1.1 Partner: SRDC

No IP related to the SALUS Project is to be excluded.

2.1.2 Partner: Roche


2.1.3 Partner: LISPA


2.1.4 Partner: TUD


2.1.5 Partner: OFFIS

2.1.5.1 Description of the IP

MUSTANG ("Multidimensional Statistical Data Analysis Engine") is a software platform that facilitates the implementation of analytical information systems based on a data warehouse. It supports the collection and analysis of multidimensional data to supply information and decision support. For example, MUSTANG is used in the epidemiological cancer registry of Lower Saxony.

2.1.5.2 Evidence for the IP

Article: Koch S, Meister J, Rohde M. MUSTANG - A Framework for Statistical Analyses of Multidimensional Data in Public Health. Proc. 17th International Conference Informatics for Environment Protection, pp. 635-642 (2004).

2.1.5.3 Relevance of the IP to the project

MUSTANG as a software tool will not become part of the overall SALUS system, but the tool may be used to perform an explorative data analysis of anonymized data extracted from the pilot sites, in order to identify meaningful patterns related to ADEs. Therefore, we have

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included it in the list of Background such that access can be granted to project partners in the framework of the project if needed.

2.1.5.4 Possible exploitation

MUSTANG will not be published under open-source licence or sold as a software product, but is already used as part of a service offering consisting of consultancy for customers primarily in the healthcare domain together with data analyses based on the tool (i.e., a hybrid product.)

2.1.6 Partner: EuroRec


2.1.7 Partner: ERS


EHR Integration System, part of CESIL. CESIL is a registered Trade Mark of ERS under which ERS markets a series of tools to create, validate, QA and publish artefacts, markets software (to be summarized as Integration Engines) that supports the extraction, normalization and transformation from multiple data sources and multiple organizations using semantic mediation technologies, markets software (to be summarized as Persistence Engines) to persist data (XML, Relational, Triple store) with querying support (e.g. SPARQL End-Point), markets software (to be summarized as Presentation Engines) to generate Screens and Forms for multiple types of hardware platforms. CESIL can be configured supporting functions like, but not limited to, EHR (local, regional and national), PHR, Population Research, Clinical Research infrastructures and generate/build applications using the above mentioned infrastructures. The use of CESIL is not limited to Healthcare and Life & sciences. SIAMM: Semantic Interoperability Artefact Modeling Method, as published via www.en13606.org. EN13606/ADL1.4 import module for SDRC MDR as used in SALUS as background included.


CESIL is mentioned in the Consortium Agreement as excluded background. SIAMM is now the official name used by ERS for what is mentioned under background included in the Consortium Agreement: “a method of production including tooling of artefacts such as: Detailed Clinical Models/Clinical Statements/Archetypes/Templates”, Ownership of ERS of EN13606/ADL1.4 import module for SDRC MDR Software.


CESIL is mentioned in WP8, exploitation. CESIL is a Reference Model independent platform supportive to EN/ISO 13606 (EHRCom), EN/ISO 13940 System of Concepts to Support Continuity of Care (ContSys) and soon also EN/ISO 12967 Health Informatics Service Architecture (HISA), all ISO standards initially developed in CEN. EN/ISO 13606 and HL7CDA are the base standards for the European Interoperability Framework (EIF) to express/define content in IHE profiles. This means that at some stage SALUS HL7 CDA based solution needs to be mirrored by a solution supportive to EN/ISO 13606. It is expected that at the end of the SALUS project half of the Member States will use EN/ISO 13606 as the official standard for their eHealth infrastructures.

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All ISO 13606 archetypes and SALUS template build for the SALUS project are based on a version of SIAMM. The EN13606/ADL1.4 import module for SRDC MDR allows the import of ISO 13606 archetypes in the SALUS Semantic Mediation Service and the exchange in SALUS of the ISO 13606 defined data.


Many exploitation schemes are possible. Initial fee + maintenance fee, a flat fee, Software As A Service and “pay as you go” are several options, that will be considered in the further exploitation discussions, when ERS has a more clear view on the role of CECIL in the concrete context of SALUS.

2.1.8 Partner: Agfa


(1) Semantic Data Warehouse: A system for creating a semantic data warehouse comprising a convergence service for executing queries to connected data sources, converting data from source to domain semantics and aggregating converted data characterized in that - the convergence service is invoked by an entity graph service that on demand - defines a semantic entity representation, the needed queries and data sources to be queried - and makes available the resulting data in the semantic entity representation. (2) Semantic Application Bridge: A system that exports the entity representations mentioned under (1) to external formats or feeds external data stores.


(1) Semantic Data Warehouse Patent EU 03/09/2012 N°: EP12182778.6, US 4/9/2012 N°: US61/696,309 (2) Semantic Data Source - Application Bridge Patent EU 14/01/2013 N°: EP13151114.9, US 15/01/2013 N°: US61/752472


Agfa wants to use this solution in order to expose the Orbis database as a semantic data source in the SALUS project. It forms the basis of the Semantic Interoperability Layer (SIL), used in SALUS.


Open for discussion and part of the exploitation work in the project. (WP2). Anticipating a bit, Agfa would like to organize, together with SALUS partners, a Semantic Interoperability and Clinical Application Platform to deploy SALUS services and commercially exploit it. The SALUS use cases would be ‘just’ examples of high level clinical services that could make use of such a platform.

2.1.9 Partner: UMC


Temporal pattern discovery is a computational and statistical graphical framework for analyzing longitudinal observational medical data. Its core components include the chronographs, and the ICdelta measure of temporal association. The method to create the chronographs is the IP to be protected.

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Norén GN, Hopstadius J, Bate A, Star K, Edwards IR. Temporal pattern discovery in longitudinal electronic patient records. Data Mining and Knowledge Discovery, 2010. 20(3):361-387. Norén GN, Bate A, Hopstadius J, Star K, Edwards IR. Temporal Pattern Discovery for Trends and Transient Effects: Its Application to Patient Records. Proceedings of the Fourteenth International Conference on Knowledge Discovery and Data Mining SIGKDD 2008, pages 963-971. Las Vegas NV, 2008.


The temporal pattern discovery methodology can be a core component of a framework for exploratory analysis in EHRs through the SALUS architecture; it may be applied both for exploratory analysis around a safety issue identified in spontaneous reports originating from SALUS and directly in the collection of patient records.


The UMC is interested in active exploitation of SALUS (to use the system for pharmacovigilance work). There are currently no plans for the exploitation of the chronograph method.

2.1.10 Partner: INSERM


(1) Proof-level Ontology Matching (POM) is a software tool that finds an alignment between source ontologies by finding a proof-based similarity between both atomic and complex entities. (2) A software tool for detecting and resolving inconsistencies in both evolving and networked ontologies. (3) OntoADR is an ontologized version of MedDRA INSERM has built in the context of PROTECT project. OntoADR stores mappings between MedDRA and Snomed-CT (more than 50% of MedDRA is covered).


(1) SajjadHussain, Jos De Roo, Marie-Christine Jaulent. Proof-based Ontology Matching: Finding semantic similarities between ancestor graph structures. In Sixth IEEE International Conference on Semantic Computing, Palermo, Italy (September 19-21, 2012). SajjadHussain. K-MORPH: Knowledge Morphing via Reconciliation of Contextualized Sub-ontologies. PhD thesis, Dalhousie University, Halifax, April 2011. (2) Sajjad Hussain, Jos De Roo, Ali Daniyal, S S R Abidi. Detecting and resolving inconsistencies in ontologies using contradiction derivations. In 34th Annual IEEE Computer Software and Applications Conference, Munich, Germany (July 18-22 2011). (3) Declerck G, Bousquet C, Jaulent MC. Automatic generation of MedDRA terms groupings using an ontology. Stud Health Technol Inform 2012;180:73-7.


(1) POM can be used as a software tool in SALUS for finding alignments between SALUS ontologies. (2)This tool can be used for ensuring consistent mapping and mediation between the SALUS Core Ontology (SCO), SALUS CDE ontology, and different EHR-DDOs by detecting and

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resolving inconsistencies in the SALUS harmonized ontology and identifying which of the mappings (to/from the EHR-DDOs) are causing the inconsistencies. (3) MedDRA – Snomed-CT mappings made available by OntoADR ontology are used by the SALUS Terminology Server.


(1) & (2) Those tools have applications not only in the sub-domains of healthcare, but also in other domains such as finance, travel planning, social networks, telecommunications, etc. We realize this tool scalable to other domains and projects, thus plan to utilize this tool in other domains and projects. (3) Part of the mappings stored in OntoADR have been built by INSERM, but other come for other sources, like UMLS. When they come from other sources they have been checked by experts and sometimes modified. Making available MedDRA mappings can raise license issues.

2.2 Foreground claims

2.2.1 Open source: decision on the approach

Regarding the open source the partners have decided on a common approach. There are two classes of free software licenses: a permissive free software license and a copy-left license.1 A permissive free software license is a class of free software license with minimal requirements about how the software can be redistributed. This is in contrast to copy-left licenses (http://en.wikipedia.org/wiki/Wikipedia:No_original_research) which have reciprocity / share-alike requirements. Both sets of free software licenses offer the same freedom in terms of how the software can be used, studied and privately modified. A major difference is that when the software is being redistributed (either modified or unmodified) permissive licenses permit the redistributor to combine the licensed material with other licence terms, potentially adding further restrictions to a derived work, while copyleft licenses do not allow further restrictions (among other possible differences). Agfa organized a mail poll on November 26, 2012 to find out whether there would be a consensus for the permissive license. This turned out to be the case, although in a later stage the consortium can still agree that specific modules would follow another approach.

2.2.2 The Use Cases/scenario’s

In the table below we have listed the use cases, implemented in the SALUS project. All foreground IP, whether in document-like deliverables as in software modules, is somehow connected to one or more of these scenario’s. SCENARIOS Strengthening the already existing signal detection methods based on Spontaneous Reporting

1 http://en.wikipedia.org/wiki/Permissive_free_software_licence

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1 Enabling Semi-automatic Notification of Suspected ADEs and Reporting ADEs within a Hospital

a. Enabling Notification of Suspected ADEs (ADE notification) b. Enabling Semi-automatic ADE Reporting (ICSR)

2 Supporting Clinical Evaluation of a Potential Signal through Accessing the EHRs

a. Characterizing the cases and contrasting them to a background population (CSC)

b. Temporal pattern characterization (TPC)

Supporting complementary approaches to spontaneous reporting through continuous screening of EHRs for safety monitoring 3 Running Exploratory Analysis Studies over EHRs for Signal Detection

a. Temporal association screening on EHRs (TAS) b. Manual clinical review of relevant medical history

4 Using EHRs as secondary use data sources for Post Marketing safety studies a. Estimate incidence rates of chronic heart failure (CHF) in diabetic

patients with a recent acute coronary syndrome (ACS) event on different diabetic medications

In the following table the use cases are decomposed into their software components:

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2.2.3 What will be open source?

In the following sections, the different software modules, as identified so far are listed per partner. Please, keep in mind that, as long as the project evolves and the technical work is not finished, this list can still change.

2.2.3.1 AGFA Semantic Interoperability Layer: Open Source: The following services running on the Semantic Interoperability Layer are made by other partners and will use Athena which Agfa intends to release as open source. Athena is a generic service to produce inferred entities using the EYE reasoner. EYE is a generic reasoner built by Agfa and published as a formal open source project (eulersharp.sourceforge.net/). This is the list of services, using Athena: Safety Analysis Subscription Manager Safety Analysis Query Manager OMOP Content Model Converter ROCHE Content Model Converter OMOP Content Model Formatter ROCHE Content Model Formatter For a more detailed description of the services using Athena, please refer to the section of the partner, building the solution. Closed Source: Orbis Semantic Interoperability Data Service Orbis SPARQL Endpoint These data services expose the inner data structure of ORBIS, Agfa’s Clinical Information System. It is not the wish of Agfa to make this public nor is it needed for the project or for further exploitation. Semantic Resource Set: Open Source: Ontologies Terminologies within the constraints of existing licenses Domain Entity Models, patterns based on third party ontologies enabling reusability Closed Source: Orbis Content Model Ontology (DDO) Orbis Mapping rule files (DDO to entity models) Orbis Data Entity Models These data services expose the inner data structure of ORBIS, Agfa’s Clinical Information System. It is not the wish of Agfa to make this public nor is it needed for the project or for further exploitation.

2.2.3.2 ERS

All ISO 13606 archetypes and SALUS template as developed for the SALUS project are ERS foreground.

2.2.3.3 INSERM

ICSR reporting tool Open Source:

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SALUS ICSR reporting tool (IRT) supports the reporting of adverse drug events (ADE) to regulatory authorities with services enabling automatic pre-population of individual case safety reports (ICSR) by extracting data available in the patient’s Electronic Health Record (EHR) and providing assistance to the manual completion of information that couldn’t be automatically prefilled. The main objective of this tool is to reduce the time necessary to complete ICSRs and the errors due to double data entry. If the data needed to complete the ICSR form is available in the EHR of the patient, IRT will enable automatic filling of the form with this data. SALUS IRT supports semi-automatic reporting of ADE to regulatory authorities using two data models: (1) the ICH E2B(R2) data model (which is also a protocol for electronic reporting of ADE); (2) the AIFA data model used in Italy to report ADE to local authorities. SALUS IRT is composed of several subcomponents (ICSR reporting tool and related Web GUIs, ICSR reporting manager, ICSR report generator, ICSR content model converter) that work closely with other components of the whole SALUS platform: (i) Semantic Interoperability Data Service (SIL-DS), (ii) Terminology Server, (iii) De-identification/pseudonymisation service, (iv) ADE Notification tool. SALUS platform ensures the possibility of extracting patient data needed to pre-populate ICSR forms, by converting the information model data elements used in the patient data warehouse (DWH) to the E2B data model. The two main components of SALUS platform enabling this function are Technical Interoperability Data Service (TIL-DS) and SIL-DS. TIL-DS handles the interaction of the SALUS platform with the local DWH and enables query transactions necessary to extract patient data needed for the filling of the ICSR. SIL-DS is responsible to handle the conversions between the different information models, in that case between the information models used to encode patient data in the local EHR or DWH (typically HL7 CDA PCC information model) and the E2B(R2) information model. Since national pharmacovigilance policies in Europe require the ICSR forms to be de-identified and pseudonymized before their transmission to the pharmacovigilance regulatory authorities, SALUS IRT also ensures transactions with the SALUS components performing those functions: SALUS De-identification Service, which removes or replaces in the ICSR form the data that could potentially be able to identify the patient; SALUS Pseudonymization Service which generates a replacement identifier for the patient ID. IRT is thus designed to ensure (a) all transactions with other SALUS platform components necessary to extract patient data from the EHR to prepopulate the ICSR; (b) all operations necessary to complete the filling of the ICSR in compliance with E2B(R2) specifications and its correct transmission to the pharmacovigilance regulatory authorities. IRT also supports several additional functionalities: recording an ICSR to be completed and reported later; accessing previously sent and waiting to be completed ICSRs; updating and sending an ICSR reported in a previous session; finalizing and sending an ICSR. The ICSR prepopulation process is always triggered following the HP decision, but this can be done in two different circumstances: (i) the HP detects an ADE on the basis of his own expertise and decides to report it; (ii) the ADE notification tool, a complementary SALUS component performing real-time screening of EHR data, detects a potential ADE and displays an alert message to the HP, proposing him to report the case. But in both cases, the ADE notification tool triggers the IRT (calling its web service) and provides it with the data necessary for creating a new prepopulated ICSR, especially the PID of the patient. Three conference papers describing ICSR reporting tool have been presented / accepted (one at SWAT4LS 2012 and two at MedInfo 2013). A fourth paper has been submitted to Methods of Information in Medicine. SWAT4LS paper has been written with SRDC, because it also describes SALUS semantic mediation framework. MIM paper has been written with SRDC and AGFA because it describes SALUS semantic interoperability platform.

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2.2.3.4 OFFIS

IHE QED Module Extension Open Source: The IHE QED Extension module is a software component which implements the IHE Query for Existing Data profile and a set of extensions to this profile to solve the SALUS use cases. This module allows querying of medical data from a remote system by using Web-Services in a standardized manner. The IHE QED profile is an already well known standard but does not allow querying for population based content. Therefore also HQMF-documents where integrated to the profile. Next to this EN13606 based content can be transported via this extension. As this module is an extension to an already known profile it is planned to offer this extension to the IHE as a proposal and also to release the module as Open Source software to the community. This implementation offers the transport of medical data from one system via Web-Service to another and is not connected to any data sources or data consumer. Therefore this module can be integrated whenever as communication between two medical systems is needed based on the content the profile defines. Within the SALUS project this module is always used when LISPA database is queried as it defines the only interface to the LISPA-connector to proof SALUS interoperability by using standard based communication profiles. IHE Care Management Module Extension Open Source: The IHE CM Extension module is a software component which implements the IHE Care Management profile and a set of extensions to this profile to solve the SALUS use cases. This module allows subscription to medical data from a remote system by using Web-Services in a standardized manner. The IHE CM profile is an already well known standard but does not allow querying for population based content. Therefore also HQMF-documents where integrated to the profile. Next to this EN13606 based content can be transported via this extension. As this module is an extension to an already known profile it is planned to offer this extension to the IHE as a proposal and also to release the module as Open Source software to the community. This implementation offers the subscription and transport of medical data from one system via Web-Service to another and is not connected to any data sources or data consumer. Therefore this module can be integrated whenever as communication between two medical systems is needed based on the content the profile defines. Within the SALUS project this module is always used when a subscription to data of the LISPA database is required as it defines the only subscription based interface to the LISPA-connector to proof SALUS interoperability by using standard based communication profiles. LISPA Connector Open Source: The LISPA connector is a software component which connects the IHE QED and also the IHE CM extension to the LISPA database. If a query is sent through one of these IHE profiles it ends up at the LISPA connector. This software interprets the query/subscription and maps it to the corresponding SQL queries to be performed on the LISPA database. The result set is than produced for the IHE profile starting the query and returned. As this mapping is directly depending to the LISPA database schema it is not useful to release it as Open Source software, yet it will be freely available for LISPA after the project ends. In fact it can be used after the project end date to offer LISPA a standard based interoperability interface to other systems. Even if the extensions will not leave the draft state of the IHE profile proposal, this

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interface can still be used as the two extensions developed both are backwards compatible to the original IHE QED or IHE CM profiles. In case a standardized interoperability profile is needed on LISPA side the LISPA connector can be still used further on. The LISPA connector is used during the project for every query that has to be answered by the LISPA database. Workflow Management Module Open Source: The Workflow Management Module is a light weight software component to organize workflow tasks optimized for XML communication. This software component is used to trigger the IHE profile extensions IHE QED ext and IHE CM ext. A query produced by native JAVA software is sent through the workflow management to one of the IHE profiles, transported to the remote part of the profile, handed over to the database connector via Workflow Management and returned the same way. This module can be used whenever a workflow management based on native JAVA source code is needed. It also offers a graphical user interface to follow the workflow steps in possible many workflows at the same time and also to check the structure of the workflows during implementation. This software module should be, as the IHE profile extensions, released as Open Source software and be presented to the community. It is also integrated to the IHE QED ext and IHE CM ext modules. Therefore it should follow the same licensing as these modules. ADE-Notification-Tool Open Source: The ADE-Notification-Tool is a software component to use data-mining-algorithms on clinical data sources to semi-automatically detect adverse drug events. This software tries both on the one hand to detect already known side effects as also currently not known side effects of drugs. Therefore several data sources about known ADEs, as also medical knowledge about detecting side effects, has been integrated to the software. The tool communicates with external data sources via a SPARQL endpoint, which makes it easy to adapt the tool to further information systems. Within SALUS project these SPARQL queries might be translated to IHE profile based queries to query for example LISPA system, but in case of TUD database, these queries can be performed directly. Any data source offering a SPARQL endpoint can be therefore directly queried by the ADE notification tool. This component will be released as Open Source software by the project to the community. This software can be used then as an ADE detection tool for medical professionals, but also as a framework for further research on side effects and medication issues to handle big data.

2.2.3.5 SRDC

Semantic Interoperability Layer Open Source: LISPA Semantic Interoperability Service: This Semantic Interoperability Service is capable of converting medical summaries represented through HL7 CCD based templates (identified in D4.1.1) to SALUS Common Information Model. We do not intend to apply for a patent for this tool. We have already covered some of its functionalities in a number of publication efforts. In addition to this a PhD Thesis is completed covering this service. We aim to make this tool available as a part of public SALUS GIT repository. It is being used in all of the SALUS Pilot scenarios that are going to be deployed at LISPA pilot site.

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Ontmalizer Tool: Ontmalizer is a tool developed by the SRDC team that is able to perform comprehensive transformations of XML Schemas (XSD) and XML data to RDF/OWL automatically. Through this tool, it is possible to create RDF/OWL representation of XML Schemas, and XML instances that comply with such XML Schemas. We do not intend to apply for a patent for this tool. The aim is to establish a sustainable open source community for this project. It is already being served over GIT Repository (https://github.com/srdc/ontmalizer). It is being used in all of the SALUS Pilot scenarios that are going to be deployed at LISPA pilot site. Semantic MDR Tool: The SALUS Semantic MDR, which is the underlying technology of CDE Repository, provides a federated metadata registry architecture where machine-processable definitions of common data elements across domains can be shared, re-used, and semantically interlinked with each other to address the semantic interoperability challenge. We do not intend to apply for a patent for this tool. The aim is to establish a sustainable open source community for this project. We have already covered some of its functionalities in a number of publication efforts. In addition to this a PhD Thesis is continuing covering this tool. It is already being served over GIT Repository. (https://github.com/srdc/semanticMDR). The Tool is now available with GPL license. We aim to demonstrate its functionalities particularly in “1.b” and “4.a” use cases. SRDC aims to provide an extended version of this tool, as closed code as “Enterprise Edition” with additional capabilities such as advanced user management, access control mechanisms, collaborative multi-user development of CDEs, role based GUIs, advanced search, multilingual GUI. Security and Privacy Services Open Source: De-Identification and Pseudonymization services: SALUS De-Identification and pseudonymization services enable the anonymization of medical data sets (that could be shared as RDF or XML content) through a modularly implemented de-identification methods (like redaction, substitution, generalization and fuzzing). We do not intend to apply for a patent for this tool. We have already covered some of its functionalities in a number of publication efforts. In addition to this a Masters Thesis is continuing covering these services. We aim to make this tool available as a part of public SALUS GIT repository. It is being used in the “3.b” and “4.a” use cases Audit Record Repository (ARR): SALUS Audit Record Repository is an implementation of IHE ATNA profile and provides mechanisms to store, filter and view of audit logs. The implementation is already based on OpenATNA open source implementation2. Hence the option for patent application is not applicable. The SALUS ARR client will be available as a part of public SALUS GIT repository. It is being used in the “1.b”, “2.a”, “2.b”, “3.a”, “3.b”, “4.a” use cases. Safety Analysis Tools Open Source: Case Series Characterization Tool: Case Series Characterization Tool is a web based tool to query of data sources for electronic health records of selected patient populations to characterize ADE cases that originate from SALUS EHR data and compares the statistics against a custom background population. We do not intend to apply for a patent for this tool. We have already covered some of its functionalities in a number of publication efforts. We aim

2 https://www.projects.openhealthtools.org/sf/projects/openatna/

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to make this tool available as a part of public SALUS GIT repository. It is being used in “2.a” use case. Temporal Pattern Characterization Tool: Temporal Pattern Characterization Tool is a web based tool to calculate and provide a visual representation of the temporal pattern between a selected drug of interest and a medical condition of interest. We do not intend to apply for a patent for this tool. We may cover some of its functionalities in future publication efforts. We aim to make this tool available as a part of public SALUS GIT repository. It is being used in “2.b” use case. Temporal Association screening Tool: The Temporal Association Screening tool (TAS) is a web based tool that enables broad scale screening for potential signals of SALUS EHR data. We do not intend to apply for a patent for this tool. We may cover some of its functionalities in future publication efforts. We aim to make this tool available as a part of public SALUS GIT repository. It is being used in “3.a” use case. Patient History Tool: Patient History Tool is a web based tool to view individual patient histories which is essential for ensuring that the evidence of a possible causal association between a drug and an event is not confounded by something in the patient during signal evaluation. We do not intend to apply for a patent for this tool. We may cover some of its functionalities in future publication efforts. We aim to make this tool available as a part of public SALUS GIT repository. It is being used in “3.b” use case. Post Marketing Safety Study Tool: Post Marketing Safety study Tool is a web based tool to run safety analysis studies focusing on few drugs and conditions such as estimating the incidence rates of Congestive Heart Failure (CHF) in diabetic patients with a recent acute coronary syndrome (ACS) event. We do not intend to apply for a patent for this tool. We may cover some of its functionalities in future publication efforts. We aim to make this tool available as a part of public SALUS GIT repository. It is being used in “4.a” use case. After the proof of concept pilot is validated in SALUS project, SRDC is interested in commercial exploitation of extended versions of both Patient History Tool and Post Market Safety Study Tools if the tools are evaluated favorably as a result of clinical validation.

2.2.3.6 UMC

The UMC is interested in active exploitation of SALUS (to use the system for pharmacovigilance work). On the concrete organization of Open Source modules (e.g. on Sourceforge.com) UMC indicated that they can make the code and documentation available but can’t commit to keep a real open-source project running on sourceForge. The actual modules used in the different use cases and which are intended to be provided as open source are listed below: Case Series Characterization Tool: UMC doesn’t intend to apply for a patent for this tool. They aim to make this tool available as a part of public SALUS GIT repository. It is being used in “2.a” use case. Temporal Pattern Characterization Tool: UMC doesn’t intend to apply for a patent for this tool. They aim to make this tool available as a part of public SALUS GIT repository. It is being used

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in “2.b” use case. We will however not provide the method to create the chronographs as open source. Temporal Association Screening Tool: UMC doesn’t intend to apply for a patent for this tool. They aim to make this tool available as a part of public SALUS GIT repository. It is being used in “3.a” use case. Patient History Tool: UMC doesn’t intend to apply for a patent for this tool. They aim to make this tool available as a part of public SALUS GIT repository. It is being used in “3.b” use case. In addition to these, as part of the PROTECT project, UMC has developed an integrated information system that collects longitudinal patient record data from the Health Improvement Network Database (THIN) and is capable of visualizing and analyzing this data, as well as facilitating signal detection of ADRs. The current implementation of this system requires patient record data to be stored according to the proprietary THIN specification. The system architecture in SALUS however, stores patient data according to a standardized data model, the OMOP Common data Model. Therefore, we are going to adapt the system to adhere to this standard, which will allow it to be used and provide added value in the SALUS project. UMC aims to exploit the adapted system.

2.2.4 How will the open source modules be organised?

The consensus of the partners is to use a "private" repository for development purposes, and only publish "stable" releases of the software. In the private repository, there is already a structure that should roughly relate to the list of Foreground modules. Stable releases are copied and made available for download via the SALUS website. The consortium decided to not initiate an official open source project (e.g. on sourceforge.net) because of the large overhead and the maintenance after the project. Currently 2 modules are already downloadable: - SemanticMDR is a semantic implementation of an ISO/IEC 11179 based Metadata Registry/Repository. - Ontmalizer is a tool for comprehensive transformations of XML Schemas (XSD) and XML data to RDF/OWL automatically.

CONCLUSION

The SALUS consortium wishes to contribute to the general advance in Health Care IT and therefore opens a great part of its project results to the community, both in terms of dissemination and in terms of concrete software code. However, being a small consortium with a limited project lifetime and fearing a lack of resources to maintain a formal open source project, the consortium decided to “keep code available” for interested parties without the overhead of a formal open source project. No patents are currently considered, other than the ones identified as the background IP. However, the consortium still wants to exploit the SALUS results by actually establishing and running services supporting the SALUS use cases. We refer to the exploitation deliverables (D2.1.*) for more information.

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