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  1. Article ; Online: Patient Cohort Identification on Time Series Data Using the OMOP Common Data Model.

    Maier, Christian / Kapsner, Lorenz A / Mate, Sebastian / Prokosch, Hans-Ulrich / Kraus, Stefan

    Applied clinical informatics

    2021  Volume 12, Issue 1, Page(s) 57–64

    Abstract: Background: The identification of patient cohorts for recruiting patients into clinical trials requires an evaluation of study-specific inclusion and exclusion criteria. These criteria are specified depending on corresponding clinical facts. Some of ... ...

    Abstract Background: The identification of patient cohorts for recruiting patients into clinical trials requires an evaluation of study-specific inclusion and exclusion criteria. These criteria are specified depending on corresponding clinical facts. Some of these facts may not be present in the clinical source systems and need to be calculated either in advance or at cohort query runtime (so-called feasibility query).
    Objectives: We use the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) as the repository for our clinical data. However, Atlas, the graphical user interface of OMOP, does not offer the functionality to perform calculations on facts data. Therefore, we were in search for a different approach. The objective of this study is to investigate whether the Arden Syntax can be used for feasibility queries on the OMOP CDM to enable on-the-fly calculations at query runtime, to eliminate the need to precalculate data elements that are involved with researchers' criteria specification.
    Methods: We implemented a service that reads the facts from the OMOP repository and provides it in a form which an Arden Syntax Medical Logic Module (MLM) can process. Then, we implemented an MLM that applies the eligibility criteria to every patient data set and outputs the list of eligible cases (i.e., performs the feasibility query).
    Results: The study resulted in an MLM-based feasibility query that identifies cases of overventilation as an example of how an on-the-fly calculation can be realized. The algorithm is split into two MLMs to provide the reusability of the approach.
    Conclusion: We found that MLMs are a suitable technology for feasibility queries on the OMOP CDM. Our method of performing on-the-fly calculations can be employed with any OMOP instance and without touching existing infrastructure like the Extract, Transform and Load pipeline. Therefore, we think that it is a well-suited method to perform on-the-fly calculations on OMOP.
    MeSH term(s) Algorithms ; Cohort Studies ; Databases, Factual
    Language English
    Publishing date 2021-01-27
    Publishing country Germany
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ISSN 1869-0327
    ISSN (online) 1869-0327
    DOI 10.1055/s-0040-1721481
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article: A Framework for Criteria-Based Selection and Processing of Fast Healthcare Interoperability Resources (FHIR) Data for Statistical Analysis: Design and Implementation Study.

    Gruendner, Julian / Gulden, Christian / Kampf, Marvin / Mate, Sebastian / Prokosch, Hans-Ulrich / Zierk, Jakob

    JMIR medical informatics

    2021  Volume 9, Issue 4, Page(s) e25645

    Abstract: Background: The harmonization and standardization of digital medical information for research purposes is a challenging and ongoing collaborative effort. Current research data repositories typically require extensive efforts in harmonizing and ... ...

    Abstract Background: The harmonization and standardization of digital medical information for research purposes is a challenging and ongoing collaborative effort. Current research data repositories typically require extensive efforts in harmonizing and transforming original clinical data. The Fast Healthcare Interoperability Resources (FHIR) format was designed primarily to represent clinical processes; therefore, it closely resembles the clinical data model and is more widely available across modern electronic health records. However, no common standardized data format is directly suitable for statistical analyses, and data need to be preprocessed before statistical analysis.
    Objective: This study aimed to elucidate how FHIR data can be queried directly with a preprocessing service and be used for statistical analyses.
    Methods: We propose that the binary JavaScript Object Notation format of the PostgreSQL (PSQL) open source database is suitable for not only storing FHIR data, but also extending it with preprocessing and filtering services, which directly transform data stored in FHIR format into prepared data subsets for statistical analysis. We specified an interface for this preprocessor, implemented and deployed it at University Hospital Erlangen-Nürnberg, generated 3 sample data sets, and analyzed the available data.
    Results: We imported real-world patient data from 2016 to 2018 into a standard PSQL database, generating a dataset of approximately 35.5 million FHIR resources, including "Patient," "Encounter," "Condition" (diagnoses specified using International Classification of Diseases codes), "Procedure," and "Observation" (laboratory test results). We then integrated the developed preprocessing service with the PSQL database and the locally installed web-based KETOS analysis platform. Advanced statistical analyses were feasible using the developed framework using 3 clinically relevant scenarios (data-driven establishment of hemoglobin reference intervals, assessment of anemia prevalence in patients with cancer, and investigation of the adverse effects of drugs).
    Conclusions: This study shows how the standard open source database PSQL can be used to store FHIR data and be integrated with a specifically developed preprocessing and analysis framework. This enables dataset generation with advanced medical criteria and the integration of subsequent statistical analysis. The web-based preprocessing service can be deployed locally at the hospital level, protecting patients' privacy while being integrated with existing open source data analysis tools currently being developed across Germany.
    Language English
    Publishing date 2021-04-01
    Publishing country Canada
    Document type Journal Article
    ZDB-ID 2798261-0
    ISSN 2291-9694
    ISSN 2291-9694
    DOI 10.2196/25645
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article: Investigating the Capabilities of FHIR Search for Clinical Trial Phenotyping.

    Gulden, Christian / Mate, Sebastian / Prokosch, Hans-Ulrich / Kraus, Stefan

    Studies in health technology and informatics

    2018  Volume 253, Page(s) 3–7

    Abstract: Clinical trials are the foundation of evidence-based medicine and their computerized support has been a recurring theme in medical informatics. One challenging aspect is the representation of eligibility criteria in a machine-readable format to automate ... ...

    Abstract Clinical trials are the foundation of evidence-based medicine and their computerized support has been a recurring theme in medical informatics. One challenging aspect is the representation of eligibility criteria in a machine-readable format to automate the identification of suitable participants. In this study, we investigate the capabilities for expressing trial eligibility criteria via the search functionality specified in HL7 FHIR, an emerging standard for exchanging healthcare information electronically which also defines a set of operations for searching for health record data. Using a randomly sampled subset of 303 eligibility criteria from ClinicalTrials.gov yielded a 34 % success rate in representing them using the FHIR search semantics. While limitations are present, the FHIR search semantics are a viable tool for supporting preliminary trial eligibility assessment.
    MeSH term(s) Clinical Trials as Topic ; Delivery of Health Care ; Electronic Health Records ; Medical Informatics ; Semantics
    Language English
    Publishing date 2018-08-24
    Publishing country Netherlands
    Document type Journal Article
    ISSN 0926-9630
    ISSN 0926-9630
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: A Multi-User Terminology Mapping Toolbox.

    Mate, Sebastian / Seuchter, Susanne A / Ehrenberg, Katharina / Deppenwiese, Noemi / Zierk, Jakob / Prokosch, Hans-Ulrich / Kraska, Detlef / Kapsner, Lorenz A

    Studies in health technology and informatics

    2021  Volume 278, Page(s) 217–223

    Abstract: Semantic interoperability is a major challenge in multi-center data sharing projects, a challenge that the German Initiative for Medical Informatics is taking up. With respect to laboratory data, enriching site-specific tests and measurements with LOINC ... ...

    Abstract Semantic interoperability is a major challenge in multi-center data sharing projects, a challenge that the German Initiative for Medical Informatics is taking up. With respect to laboratory data, enriching site-specific tests and measurements with LOINC codes appears to be a crucial step in supporting cross-institutional research. However, this effort is very time-consuming, as it requires expert knowledge of local site specifics. To ease this process, we developed a generic manual collaborative terminology mapping tool, the MIRACUM Mapper. It allows the creation of arbitrary mapping workflows involving different user roles. A mapping workflow with two user roles has been implemented at University Hospital Erlangen to support the local LOINC mapping. Additionally, the MIRACUM LabVisualizeR provides summary statistics and visualizations of analyte data. We developed a toolbox that facilitates the collaborative creation of mappings and streamlines the review as well as the validation process. The two tools are available under an open source license.
    MeSH term(s) Health Facilities ; Humans ; Information Dissemination ; Laboratories ; Logical Observation Identifiers Names and Codes ; Medical Informatics
    Language English
    Publishing date 2021-05-27
    Publishing country Netherlands
    Document type Journal Article
    ISSN 1879-8365
    ISSN (online) 1879-8365
    DOI 10.3233/SHTI210072
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Book ; Online ; Thesis: Föderierte medizinische Forschungsdatenbanken: Architekturen, Datenintegration und Abfragelogik

    Mate, Sebastian [Verfasser] / Prokosch, Hans-Ulrich [Akademischer Betreuer] / Prokosch, Hans-Ulrich [Gutachter] / Riehle, Dirk [Gutachter]

    2021  

    Author's details Sebastian Mate ; Gutachter: Hans-Ulrich Prokosch, Dirk Riehle ; Betreuer: Hans-Ulrich Prokosch
    Keywords Medizin, Gesundheit ; Medicine, Health
    Subject code sg610
    Language German
    Publisher Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)
    Publishing place Erlangen
    Document type Book ; Online ; Thesis
    Database Digital theses on the web

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  6. Article ; Online: A Framework for Criteria-Based Selection and Processing of Fast Healthcare Interoperability Resources (FIHR) Data for Statistical Analysis

    Gruendner, Julian / Gulden, Christian / Kampf, Marvin / Mate, Sebastian / Prokosch, Hans-Ulrich / Zierk, Jakob

    JMIR Medical Informatics, Vol 9, Iss 4, p e

    Design and Implementation Study

    2021  Volume 25645

    Abstract: BackgroundThe harmonization and standardization of digital medical information for research purposes is a challenging and ongoing collaborative effort. Current research data repositories typically require extensive efforts in harmonizing and transforming ...

    Abstract BackgroundThe harmonization and standardization of digital medical information for research purposes is a challenging and ongoing collaborative effort. Current research data repositories typically require extensive efforts in harmonizing and transforming original clinical data. The Fast Healthcare Interoperability Resources (FHIR) format was designed primarily to represent clinical processes; therefore, it closely resembles the clinical data model and is more widely available across modern electronic health records. However, no common standardized data format is directly suitable for statistical analyses, and data need to be preprocessed before statistical analysis. ObjectiveThis study aimed to elucidate how FHIR data can be queried directly with a preprocessing service and be used for statistical analyses. MethodsWe propose that the binary JavaScript Object Notation format of the PostgreSQL (PSQL) open source database is suitable for not only storing FHIR data, but also extending it with preprocessing and filtering services, which directly transform data stored in FHIR format into prepared data subsets for statistical analysis. We specified an interface for this preprocessor, implemented and deployed it at University Hospital Erlangen-Nürnberg, generated 3 sample data sets, and analyzed the available data. ResultsWe imported real-world patient data from 2016 to 2018 into a standard PSQL database, generating a dataset of approximately 35.5 million FHIR resources, including “Patient,” “Encounter,” “Condition” (diagnoses specified using International Classification of Diseases codes), “Procedure,” and “Observation” (laboratory test results). We then integrated the developed preprocessing service with the PSQL database and the locally installed web-based KETOS analysis platform. Advanced statistical analyses were feasible using the developed framework using 3 clinically relevant scenarios (data-driven establishment of hemoglobin reference intervals, assessment of anemia prevalence in patients with cancer, and ...
    Keywords Computer applications to medicine. Medical informatics ; R858-859.7
    Subject code 310
    Language English
    Publishing date 2021-04-01T00:00:00Z
    Publisher JMIR Publications
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  7. Article: Patient Cohort Identification on Time Series Data Using the OMOP Common Data Model

    Maier, Christian / Kapsner, Lorenz A. / Mate, Sebastian / Prokosch, Hans-Ulrich / Kraus, Stefan

    Applied Clinical Informatics

    2021  Volume 12, Issue 01, Page(s) 57–64

    Abstract: Background: The identification of patient cohorts for recruiting patients into clinical trials requires an evaluation of study-specific inclusion and exclusion criteria. These criteria are specified depending on corresponding clinical facts. Some of ... ...

    Abstract Background: The identification of patient cohorts for recruiting patients into clinical trials requires an evaluation of study-specific inclusion and exclusion criteria. These criteria are specified depending on corresponding clinical facts. Some of these facts may not be present in the clinical source systems and need to be calculated either in advance or at cohort query runtime (so-called feasibility query).
    Objectives: We use the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) as the repository for our clinical data. However, Atlas, the graphical user interface of OMOP, does not offer the functionality to perform calculations on facts data. Therefore, we were in search for a different approach. The objective of this study is to investigate whether the Arden Syntax can be used for feasibility queries on the OMOP CDM to enable on-the-fly calculations at query runtime, to eliminate the need to precalculate data elements that are involved with researchers' criteria specification.
    Methods: We implemented a service that reads the facts from the OMOP repository and provides it in a form which an Arden Syntax Medical Logic Module (MLM) can process. Then, we implemented an MLM that applies the eligibility criteria to every patient data set and outputs the list of eligible cases (i.e., performs the feasibility query).
    Results: The study resulted in an MLM-based feasibility query that identifies cases of overventilation as an example of how an on-the-fly calculation can be realized. The algorithm is split into two MLMs to provide the reusability of the approach.
    Conclusion: We found that MLMs are a suitable technology for feasibility queries on the OMOP CDM. Our method of performing on-the-fly calculations can be employed with any OMOP instance and without touching existing infrastructure like the Extract, Transform and Load pipeline. Therefore, we think that it is a well-suited method to perform on-the-fly calculations on OMOP.
    Keywords information storage and retrieval ; clinical data ; electronic health records ; Arden Syntax ; Medical Logic Modules
    Language English
    Publishing date 2021-01-01
    Publisher Georg Thieme Verlag KG
    Publishing place Stuttgart ; New York
    Document type Article
    ISSN 1869-0327
    ISSN (online) 1869-0327
    DOI 10.1055/s-0040-1721481
    Database Thieme publisher's database

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  8. Article ; Online: Mapping the Entire Record-An Alternative Approach to Data Access from Medical Logic Modules.

    Kraus, Stefan / Toddenroth, Dennis / Staudigel, Martin / Rödle, Wolfgang / Unberath, Philipp / Griebel, Lena / Prokosch, Hans-Ulrich / Mate, Sebastian

    Applied clinical informatics

    2020  Volume 11, Issue 2, Page(s) 342–349

    Abstract: Objectives: This study aimed to describe an alternative approach for accessing electronic medical records (EMRs) from clinical decision support (CDS) functions based on Arden Syntax Medical Logic Modules, which can be paraphrased as "map the entire ... ...

    Abstract Objectives: This study aimed to describe an alternative approach for accessing electronic medical records (EMRs) from clinical decision support (CDS) functions based on Arden Syntax Medical Logic Modules, which can be paraphrased as "map the entire record."
    Methods: Based on an experimental Arden Syntax processor, we implemented a method to transform patient data from a commercial patient data management system (PDMS) to tree-structured documents termed CDS EMRs. They are encoded in a specific XML format that can be directly transformed to Arden Syntax data types by a mapper natively integrated into the processor. The internal structure of a CDS EMR reflects the tabbed view of an EMR in the graphical user interface of the PDMS.
    Results: The study resulted in an architecture that provides CDS EMRs in the form of a network service. The approach enables uniform data access from all Medical Logic Modules and requires no mapping parameters except a case number. Measurements within a CDS EMR can be addressed with straightforward path expressions. The approach is in routine use at a German university hospital for more than 2 years.
    Conclusion: This practical approach facilitates the use of CDS functions in the clinical routine at our local hospital. It is transferrable to standard-compliant Arden Syntax processors with moderate effort. Its comprehensibility can also facilitate teaching and development. Moreover, it may lower the entry barrier for the application of the Arden Syntax standard and could therefore promote its dissemination.
    MeSH term(s) Electronic Health Records ; Logic ; Time Factors
    Language English
    Publishing date 2020-05-13
    Publishing country Germany
    Document type Journal Article
    ISSN 1869-0327
    ISSN (online) 1869-0327
    DOI 10.1055/s-0040-1709708
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article: Standards-Based Procedural Phenotyping: The Arden Syntax on i2b2.

    Mate, Sebastian / Castellanos, Ixchel / Ganslandt, Thomas / Prokosch, Hans-Ulrich / Kraus, Stefan

    Studies in health technology and informatics

    2017  Volume 243, Page(s) 37–41

    Abstract: Phenotyping, or the identification of patient cohorts, is a recurring challenge in medical informatics. While there are open source tools such as i2b2 that address this problem by providing user-friendly querying interfaces, these platforms lack semantic ...

    Abstract Phenotyping, or the identification of patient cohorts, is a recurring challenge in medical informatics. While there are open source tools such as i2b2 that address this problem by providing user-friendly querying interfaces, these platforms lack semantic expressiveness to model complex phenotyping algorithms. The Arden Syntax provides procedural programming language construct, designed specifically for medical decision support and knowledge transfer. In this work, we investigate how language constructs of the Arden Syntax can be used for generic phenotyping. We implemented a prototypical tool to integrate i2b2 with an open source Arden execution environment. To demonstrate the applicability of our approach, we used the tool together with an Arden-based phenotyping algorithm to derive statistics about ICU-acquired hypernatremia. Finally, we discuss how the combination of i2b2's user-friendly cohort pre-selection and Arden's procedural expressiveness could benefit phenotyping.
    Language English
    Publishing date 2017
    Publishing country Netherlands
    Document type Journal Article
    ISSN 0926-9630
    ISSN 0926-9630
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article ; Online: Linking a Consortium-Wide Data Quality Assessment Tool with the MIRACUM Metadata Repository.

    Kapsner, Lorenz A / Mang, Jonathan M / Mate, Sebastian / Seuchter, Susanne A / Vengadeswaran, Abishaa / Bathelt, Franziska / Deppenwiese, Noemi / Kadioglu, Dennis / Kraska, Detlef / Prokosch, Hans-Ulrich

    Applied clinical informatics

    2021  Volume 12, Issue 4, Page(s) 826–835

    Abstract: Background: Many research initiatives aim at using data from electronic health records (EHRs) in observational studies. Participating sites of the German Medical Informatics Initiative (MII) established data integration centers to integrate EHR data ... ...

    Abstract Background: Many research initiatives aim at using data from electronic health records (EHRs) in observational studies. Participating sites of the German Medical Informatics Initiative (MII) established data integration centers to integrate EHR data within research data repositories to support local and federated analyses. To address concerns regarding possible data quality (DQ) issues of hospital routine data compared with data specifically collected for scientific purposes, we have previously presented a data quality assessment (DQA) tool providing a standardized approach to assess DQ of the research data repositories at the MIRACUM consortium's partner sites.
    Objectives: Major limitations of the former approach included manual interpretation of the results and hard coding of analyses, making their expansion to new data elements and databases time-consuming and error prone. We here present an enhanced version of the DQA tool by linking it to common data element definitions stored in a metadata repository (MDR), adopting the harmonized DQA framework from Kahn et al and its application within the MIRACUM consortium.
    Methods: Data quality checks were consequently aligned to a harmonized DQA terminology. Database-specific information were systematically identified and represented in an MDR. Furthermore, a structured representation of logical relations between data elements was developed to model plausibility-statements in the MDR.
    Results: The MIRACUM DQA tool was linked to data element definitions stored in a consortium-wide MDR. Additional databases used within MIRACUM were linked to the DQ checks by extending the respective data elements in the MDR with the required information. The evaluation of DQ checks was automated. An adaptable software implementation is provided with the R package
    Conclusion: The enhancements of the DQA tool facilitate the future integration of new data elements and make the tool scalable to other databases and data models. It has been provided to all ten MIRACUM partners and was successfully deployed and integrated into their respective data integration center infrastructure.
    MeSH term(s) Data Accuracy ; Databases, Factual ; Electronic Health Records ; Medical Informatics ; Metadata
    Language English
    Publishing date 2021-08-25
    Publishing country Germany
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ISSN 1869-0327
    ISSN (online) 1869-0327
    DOI 10.1055/s-0041-1733847
    Database MEDical Literature Analysis and Retrieval System OnLINE

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