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A Lightweight and Generic Data Mediating Architecture for Decision Support Systems Alfonso Pérez Biomedical Informatics Group (IBIME) ITACA.

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Presentation on theme: "A Lightweight and Generic Data Mediating Architecture for Decision Support Systems Alfonso Pérez Biomedical Informatics Group (IBIME) ITACA."— Presentation transcript:

1 A Lightweight and Generic Data Mediating Architecture for Decision Support Systems Alfonso Pérez Biomedical Informatics Group (IBIME) ITACA Institute, Technical University of Valencia Arctic Conference on Dual-Model based Clinical Decision Support and Knowledge Management Tromsø, May 27 th and 28 th, 2014

2 Summary Previous work Data integration in CDSSs CDS-DATOR – Methodology – Data loaders (Generic, Xpath, WebService, SQL) – Mapping definition Case Studies – PROforma – CURIAM – Data Interoperability Conclusions 2

3 Summary Previous work Data integration in CDSSs CDS-DATOR – Methodology – Data loaders (Generic, Xpath, WebService, SQL) – Mapping definition Case Studies – PROforma – CURIAM – Data Interoperability Conclusions 3

4 CDSS Interoperability [1] - [C Sáez, JM García-Gómez, J Vicente, S Tortajada, M Esparza, AT Navarro, E Fuster, M Robles. A generic decision support system featuring an assembled view of predictive models for magnetic resonance and clinical data. European Society for Magnetic Resonance in Medicine and Biology 2008 Congress, Valencia, Info-RESO, 2008] Curiam CDSS [1] – Generic CDSS for clinical and biomedical environments – Connects to databases through a generic data framework

5 CDSS semantic interoperability: HL7-CDA Wrapper 5 CDA_input.xml rules_file.clp binding_file.xml CDA_output.xml CDSS Semantic Interpreter Inference engine (e.g., Jess, Drools) ?BMI setValue (/ ?weight (* (/ ?height 100) (/ ?height 100)))) human/machine interpretable human-maintainable Use of standardized clinical documents (i.e. HL7-CDA) as input/output of CDSS [2] [2] - [C Sáez, A Bresó, J Vicente, M Robles, and JM Garcia-Gomez. An HL7-CDA wrapper for facilitating semantic interoperability to rule- based Clinical Decision Support Systems. Computer Methods and Programs in Biomedicine. Volume 109 (3) 239–249, 2013] HL7-CDA template input/output

6 Proforma data collection 6 PROforma Engine PROforma Engine wrapper guideline.pf dataconfig.xml DB XML (HL7-CDA, EN-13606,…) abab bcbc Transparent extension of the PROforma engine to permit automatic data collection from different sources [3] CDSS [3] - [A. Pérez González. Generación de interfaces gráficos automáticos a partir de ontologías, aplicación a guías clínicas. 2011]

7 Summary Previous work Data integration in CDSSs CDS-DATOR – Methodology – Data loaders (Generic, Xpath, WebService, SQL) – Mapping definition Case Studies – PROforma – CURIAM – Data Interoperability Conclusions 7

8 Data integration in CDSSs 8 Problem – Most of the CDSSs working nowadays focus their data needs in one or few different types of data sources Solution – Develop the new CDSSs independent of the data sources that we want to access What happens to the already existent CDSS? Solution – A mediator architecture able to wrap the data modules/petitions of the CDSSs, and adapt them to different data sources

9 Data integration in CDSSs 9 Clinical Decision Support Data Mediator (CDS- DATOR) – Lightweight and modular data mediator that facilitates the access to different data sources – Allows the CDSSs to decouple their implementations of the necessities imposed by the data – Designed as a non-invasive data wrapper to ease the integration with already working CDSSs

10 Summary Previous work Data integration in CDSSs CDS-DATOR – Methodology – Data loaders (Generic, Xpath, WebService, SQL) – Mapping definition Case Studies – PROforma – CURIAM – Data Interoperability Conclusions 10

11 CDS-DATOR CDS-DATOR connectivity schema – Offers different functionalities depending on the situation in the data flow 11

12 CDS-DATOR 12 Data mediator workflow – Can preload data and store it in an intermediate memory E.g., standardized patient EHR – Data are loaded via Data Loaders which are specified in the mapping file – The data retrieval process is transparent to the CDSS

13 CDS-DATOR 13 Data types

14 Summary Previous work Data integration in CDSSs CDS-DATOR – Methodology – Data loaders (Generic, Xpath, WebService, SQL) – Mapping definition Case Studies – PROforma – CURIAM – Data Interoperability Conclusions 14

15 CDS-DATOR Generic Data Loader – Composed by a set of elements that can be used to define a new DataLoader – The LoaderURI specifies the class that will be used – Any number of parameters (ParameterOption) can be specified – Each parameter can have one (SimpleParameter) or several (MultiParameter) values. – These parameters look up the data using the ValueOption interface 15 UML Schema of the Generic Loader

16 CDS-DATOR Generic Data Loader – Example code (Xpath Loader) 16 es.upv.ibime.bmg.cdsdc.xpathloader.XPathDataLoader C:/patientData.xml //x:observation/x:code patientID '] x=urn:hl7-org:v3

17 CDS-DATOR Generic Data Loader – Methodology working for developing new data loaders – Problem Too complex to be used regularly – Solution Reduce the complexity of the mappings for the most common sources (XML, Web Services, and relational databases. 17

18 CDS-DATOR Xpath Loader – Needs three parameters Url: define the route of the file Xpath: the query applied to the XML file Namespace: used to avoid ambiguities in the query 18 Workflow of the Xpath Loader

19 CDS-DATOR Xpath Loader – Example code 19 file:/C:/patientData.xml patientID x=urn:hl7-org:v3"

20 CDS-DATOR Web Service Loader – It can be connected to a SOAP or a REST service – The mapping parameters depends on the type of service used – It can be used to retrieve the information at the beginning of the execution 20 Workflow of the Web Service Loader

21 CDS-DATOR Web Service Loader – Example code 21 getRecord patientID

22 CDS-DATOR SQL Loader – Allows to define SQL queries to relational databases – Requires two parameters: URL: the connection data to the database SQL: the query that we want to execute (can contain extra mappings) 22 Workflow of the SQL Loader

23 CDS-DATOR SQL Loader – Example code Dynamic query generation 23 jdbc:mysql://localhost/testDB“ SELECT v.value FROM Patients p, Variables v WHERE p.ID="' patientID '" AND p.Variable="SET" AND v.ID IN (SELECT( p.ID || '_' || p.Variable) FROM Patients);

24 Summary Previous work Data integration in CDSSs CDS-DATOR – Methodology – Data loaders (Generic, Xpath, WebService, SQL) – Mapping definition Case Studies – PROforma – CURIAM – Data Interoperability Conclusions 24

25 CDS-DATOR How to create mappings – Identify the data needed from the CDSS – Identify the corresponding data sources – Create the corresponding mapping entry Connecting CDS-DATOR to CDSSs engines – Find the data module from the CDSS – Create a data wrapper (that implements the data loader interface) for the module – Create a wrapper for the engine to override the data queries 25

26 Summary Previous work Data integration in CDSSs CDS-DATOR – Methodology – Data loaders (Generic, Xpath, WebService, SQL) – Mapping definition Case Studies – PROforma – CURIAM – Data Interoperability Conclusions 26

27 PROforma integration The PROforma language – Models the clinical knowledge contained in a guideline as a set of tasks and data items The PROforma engine – Enacts the computer interpretable guideline written in the PROforma language – The execution of the guideline can be automatic or step by step – When the guideline needs external data, the engine has to make a request through an enquiry 27

28 PROforma integration PROforma guideline for COPD diagnosis plan 28

29 PROforma integration Problems – The language is limited to the data sources defined internally – The engine requires data to be introduced manually Solution – Extend the language to add more data sources Tied to updates and changes in the language (not recommended) – Define an external wrapper independent of the language able to automatize the data collection 29

30 PROforma integration Definition of the engine wrapper Task manager extension Data petitions pass through the CDS- DATOR 30 PFEngine Wrapper Task adapter CDS-DATOR listener n n 1 1

31 PROforma case study 31

32 Summary Previous work Data integration in CDSSs CDS-DATOR – Methodology – Data loaders (Generic, Xpath, WebService, SQL) – Mapping definition Case Studies – PROforma – CURIAM – Data Interoperability Conclusions 32

33 Curiam – Curiam BT Curiam is a generic CDSS framework – Generic data and GUI components – Curiam eases the inclusion of new predictive models using a generic classification framework [4] Curiam BT [5,6] is a CDSS for brain tumor diagnosis based on the generic Curiam CDSS The purpose for this case study is to provide Curiam BT access to the data stored in a generic relational database [4] - [C Sáez, JM García-Gómez, J Vicente, S Tortajada, J Luts, D Dupplaw, SV Huffel, M Robles. A generic and extensible automatic classification framework applied to brain tumour diagnosis in HealthAgents. The Knowledge Engineering Review 26 (3), ] [5] - [C Sáez, JM García-Gómez, J Vicente, S Tortajada, M Esparza, A Navarro, E Fuster, M Robles. Curiam BT, Decision Support System for Brain Tumour Diagnosis. European Society for Magnetic Resonance in Medicine and Biology 2009 Congress, Antalya, Turkey, Info-RESO, 2009] [6] - [C Sáez, L Martí-Bonmatí, Á Alberich-Bayarri, M Robles, JM García-Gómez. Randomized pilot study and qualitative evaluation of a clinical decision support system for brain tumour diagnosis based on SV 1H MRS: Evaluation as an additional information procedure for novice radiologists. Computers in Biology and Medicine 45, ]

34 Curiam case study Data flow 34

35 Curiam integration 35 Data wrapper that communicates with CDS-DATOR

36 Curiam case study The data expected by Curiam BT is a raw signal Data signals are stored as 512 points arrays in the generic database 36 IDVariable 1STE 1LTE 3 4STE IDValue 1_STE … 1_LTE … 3_LTE … 4_STE … PatientVariables + CuriamBT Database tables

37 CDS-DATOR SQL Loader 37 jdbc:mysql://localhost/testDB“ SELECT v.value FROM Patients p, Variables v WHERE p.ID="' patientID '" AND p.Variable="SET" AND v.ID IN (SELECT( p.ID || '_' || p.Variable) FROM Patients);

38 Summary Previous work Data integration in CDSSs CDS-DATOR – Methodology – Data loaders (Generic, Xpath, WebService, SQL) – Mapping definition Case Studies – PROforma – CURIAM – Data Interoperability Conclusions 38

39 Data interoperability Combining PROforma with linkEHR – The mediator doesn’t manage the data at a semantic level – A complete integration between data sources and CDSSs can be achieved combining CDS-DATOR with semantic systems – This mixed functionality was tested in a prototype for the determination of patient eligibility based on clinical data stored in a real-life EHR system [7] The patient eligibility is determined by a CDSS developed in the PROforma language The mediator provides a data layer that allowed the PROforma engine to access the XML documents generated by the semantic tool LinkEHR. 39 [7][Mar Marcos, José A. Maldonado, Begoña Martínez-Salvador, Diego Boscá, Montserrat Robles. Interoperability of clinical decision-support systems and electronic health records using archetypes: A case study in clinical trial eligibility. Journal of Biomedical Informatics, 46(4): , 2013]

40 Summary Previous work Data integration in CDSSs CDS-DATOR – Methodology – Data loaders (Generic, Xpath, WebService, SQL) – Mapping definition Case Studies – PROforma – CURIAM – Data Interoperability Conclusions 40

41 Conclusions CDS-Dator provides: – Separation between raw and semantic treatment of data – Separation between the CDSS encoding process and the mapping definition – Mappings for common data sources and easy extension to new ones – Data mediation or wrapping with any CDSS with minimal integration effort Evaluated in three use cases – PROforma engine – Curiam CDSS – PROforma + linkEHR interoperability 41

42 Thank you for your attention! Questions?


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