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Modeling the Application of IHE QRPH Profiles in Data Integration Centers: A Practical Approach with 3LGM2. Stud Health Technol Inform 2023; 309:126-130. [PMID: 37869821 DOI: 10.3233/shti230755] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2023]
Abstract
The Data Integration Centers (DICs), all part of the German Medical Informatics Initiative (MII), prepare routine care data captured in university hospitals to enable its reuse in clinical research. Tackling this challenging task requires them to maintain multiple data stores, implement the necessary transformation processes, and provide the required terminology services, all while also addressing the use case specific needs researchers might have. An MII wide application of the standardized profiles defined in the IHE QRPH domain might therefore be able to drastically reduce the overhead at any one DIC. The MII DIC reference model built in 3LGM2, a method to describe complex information system architectures, serves as a starting point to evaluate whether such an application is possible. We first extend the IHE modeling capabilities of 3LGM2 to also support the five profiles from the QRPH domain that our experts evaluated as relevant in the MII DIC context. We then expand the DIC reference model by some IHE QRPH actors and transactions, showing that their application could be beneficial in the MII DIC context, provided they surpass their trial status.
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The Leipzig Health Atlas-An Open Platform to Present, Archive, and Share Biomedical Data, Analyses, and Models Online. Methods Inf Med 2022; 61:e103-e115. [PMID: 35915977 PMCID: PMC9788914 DOI: 10.1055/a-1914-1985] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
BACKGROUND Clinical trials, epidemiological studies, clinical registries, and other prospective research projects, together with patient care services, are main sources of data in the medical research domain. They serve often as a basis for secondary research in evidence-based medicine, prediction models for disease, and its progression. This data are often neither sufficiently described nor accessible. Related models are often not accessible as a functional program tool for interested users from the health care and biomedical domains. OBJECTIVE The interdisciplinary project Leipzig Health Atlas (LHA) was developed to close this gap. LHA is an online platform that serves as a sustainable archive providing medical data, metadata, models, and novel phenotypes from clinical trials, epidemiological studies, and other medical research projects. METHODS Data, models, and phenotypes are described by semantically rich metadata. The platform prefers to share data and models presented in original publications but is also open for nonpublished data. LHA provides and associates unique permanent identifiers for each dataset and model. Hence, the platform can be used to share prepared, quality-assured datasets and models while they are referenced in publications. All managed data, models, and phenotypes in LHA follow the FAIR principles, with public availability or restricted access for specific user groups. RESULTS The LHA platform is in productive mode (https://www.health-atlas.de/). It is already used by a variety of clinical trial and research groups and is becoming increasingly popular also in the biomedical community. LHA is an integral part of the forthcoming initiative building a national research data infrastructure for health in Germany.
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A FHIR has been lit on gICS: facilitating the standardised exchange of informed consent in a large network of university medicine. BMC Med Inform Decis Mak 2022; 22:335. [PMID: 36536405 PMCID: PMC9762638 DOI: 10.1186/s12911-022-02081-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2021] [Accepted: 12/09/2022] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND The Federal Ministry of Education and Research of Germany (BMBF) funds a network of university medicines (NUM) to support COVID-19 and pandemic research at national level. The "COVID-19 Data Exchange Platform" (CODEX) as part of NUM establishes a harmonised infrastructure that supports research use of COVID-19 datasets. The broad consent (BC) of the Medical Informatics Initiative (MII) is agreed by all German federal states and forms the legal base for data processing. All 34 participating university hospitals (NUM sites) work upon a harmonised infrastructural as well as legal basis for their data protection-compliant collection and transfer of their research dataset to the central CODEX platform. Each NUM site ensures that the exchanged consent information conforms to the already-balloted HL7 FHIR consent profiles and the interoperability concept of the MII Task Force "Consent Implementation" (TFCI). The Independent Trusted Third-Party (TTP) of the University Medicine Greifswald supports data protection-compliant data processing and provides the consent management solutions gICS. METHODS Based on a stakeholder dialogue a required set of FHIR-functionalities was identified and technically specified supported by official FHIR experts. Next, a "TTP-FHIR Gateway" for the HL7 FHIR-compliant exchange of consent information using gICS was implemented. A last step included external integration tests and the development of a pre-configured consent template for the BC for the NUM sites. RESULTS A FHIR-compliant gICS-release and a corresponding consent template for the BC were provided to all NUM sites in June 2021. All FHIR functionalities comply with the already-balloted FHIR consent profiles of the HL7 Working Group Consent Management. The consent template simplifies the technical BC rollout and the corresponding implementation of the TFCI interoperability concept at the NUM sites. CONCLUSIONS This article shows that a HL7 FHIR-compliant and interoperable nationwide exchange of consent information could be built using of the consent management software gICS and the provided TTP-FHIR Gateway. The initial functional scope of the solution covers the requirements identified in the NUM-CODEX setting. The semantic correctness of these functionalities was validated by project-partners from the Ludwig-Maximilian University in Munich. The production rollout of the solution package to all NUM sites has started successfully.
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3LGM2IHE: Requirements for Data-Protection-Compliant Research Infrastructures-A Systematic Comparison of Theory and Practice-Oriented Implementation. Methods Inf Med 2022; 61:e134-e148. [PMID: 36150711 PMCID: PMC9788907 DOI: 10.1055/a-1950-2791] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
OBJECTIVES The TMF (Technology, Methods, and Infrastructure for Networked Medical Research) Data Protection Guide (TMF-DP) makes path-breaking recommendations on the subject of data protection in research projects. It includes comprehensive requirements for applications such as patient lists, pseudonymization services, and consent management services. Nevertheless, it lacks a structured, categorized list of requirements for simplified application in research projects and systematic evaluation. The 3LGM2IHE ("Three-layer Graphbased meta model - Integrating the Healthcare Enterprise [IHE] " ) project is funded by the German Research Foundation (DFG). 3LGM2IHE aims to define modeling paradigms and implement modeling tools for planning health care information systems. In addition, one of the goals is to create and publish 3LGM2 information system architecture design patterns (short "design patterns") for the community as design models in terms of a framework. A structured list of data protection-related requirements based on the TMF-DP is a precondition to integrate functions (3LGM2 Domain Layer) and building blocks (3LGM2 Logical Tool Layer) in 3LGM2 design patterns. METHODS In order to structure the continuous text of the TMF-DP, requirement types were defined in a first step. In a second step, dependencies and delineations of the definitions were identified. In a third step, the requirements from the TMF-DP were systematically extracted. Based on the identified lists of requirements, a fourth step included the comparison of the identified requirements with exemplary open source tools as provided by the "Independent Trusted Third Party of the University Medicine Greifswald" (TTP tools). RESULTS As a result, four lists of requirements were created, which contain requirements for the "patient list", the "pseudonymization service", and the "consent management", as well as cross-component requirements from the TMF-DP chapter 6 in a structured form. Further to requirements (1), possible variants (2) of implementations (to fulfill a single requirement) and recommendations (3) were identified. A comparison of the requirements lists with the functional scopes of the open source tools E-PIX (record linkage), gPAS (pseudonym management), and gICS (consent management) has shown that these fulfill more than 80% of the requirements. CONCLUSIONS A structured set of data protection-related requirements facilitates a systematic evaluation of implementations with respect to the fulfillment of the TMF-DP guidelines. These re-usable lists provide a decision aid for the selection of suitable tools for new research projects. As a result, these lists form the basis for the development of data protection-related 3LGM2 design patterns as part of the 3LGM2IHE project.
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A Formal Model for the FAIR4Health Information Architecture. Stud Health Technol Inform 2022; 295:446-449. [PMID: 35773907 DOI: 10.3233/shti220761] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
In the EU project FAIR4Health, a ETL pipeline for the FAIRification of structured health data as well as an agent-based, distributed query platform for the analysis of research hypotheses and the training of machine learning models were developed. The system has been successfully tested in two clinical use cases with patient data from five university hospitals. Currently, the solution is also being considered for use in other hospitals. However, configuring the system and deploying it in the local IT architecture is non-trivial and meets with understandable concerns about security. This paper presents a model for describing the information architecture based on a formal approach, the 3LGM metamodel. The model was evaluated by the developers. As a result, the clear separation of tasks and the software components that implement them as well as the rich description of interactions via interfaces were positively emphasized.
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ToolPool Gesundheitsforschung - A Repository for Software and Services Focused on Supporting Clinical and Epidemiological Research. Stud Health Technol Inform 2022; 293:19-27. [PMID: 35592955 DOI: 10.3233/shti220342] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
The academic research environment is characterized by self-developed, innovative, customized solutions, which are often free to use for third parties with open-source code and open licenses. On the other hand, they are maintained only to a very limited extent after the end of project funding. The ToolPool Gesundheitsforschung addresses the problem of finding ready to use solutions by building a registry of proven and supported tools, services, concepts and consulting offers. The goal is to provide an up-to-date selection of "relevant" solutions for a given domain that are immediately usable and that are actually used by third parties, rather than aiming at a complete list of all solutions which belong to that domain. Proof of relevance and usage must be provided, for example, by concrete application scenarios, experience reports by uninvolved third parties, references in publications or workshops held. Quality assurance is carried out for new entries by an agreed list of admission criteria, for existing entries at least once a year by a special task force. Currently, 79 solutions are represented, this number is to be significantly expanded by involving of new editors from current national funding initiatives in Germany.
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Abstract
Despite their young age, the FAIR principles are recognised as important guidelines for research data management. Their generic design, however, leaves much room for interpretation in domain-specific application. Based on practical experience in the operation of a data repository, this article addresses problems in FAIR provisioning of medical data for research purposes in the use case of the Leipzig Health Atlas project and shows necessary future developments.
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Towards Precise Descriptions of Medical Free/Libre and Open Source Software. Stud Health Technol Inform 2020; 270:463-468. [PMID: 32570427 DOI: 10.3233/shti200203] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
The web portal Medfloss.org lists over 360 medical free/libre and open source software (MEDFLOSS) projects. These projects are described with the help of a self-developed nomenclature. Due to inconsistencies, the nomenclature shall be replaced by HITO, the Health IT Ontology. HITO is developed iteratively based on different use cases. This paper aims to describe methods and results of the second HITO use case in which HITO is extended to improve the description, retrieval and comparisons of MEDFLOSS projects on Medfloss.org. We use a mixed-methods approach to add concepts and relationships to describe MEDFLOSS precisely. The resulting HITO version stresses functional descriptions based on features and supported enterprise functions, rather than just describing technical characteristics. However, describing a larger number of MEDFLOSS projects requires the commitment of the community.
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Towards a comprehensive and interoperable representation of consent-based data usage permissions in the German medical informatics initiative. BMC Med Inform Decis Mak 2020; 20:103. [PMID: 32503529 PMCID: PMC7275462 DOI: 10.1186/s12911-020-01138-6] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2019] [Accepted: 05/27/2020] [Indexed: 11/14/2022] Open
Abstract
Background The aim of the German Medical Informatics Initiative is to establish a national infrastructure for integrating and sharing health data. To this, Data Integration Centers are set up at university medical centers, which address data harmonization, information security and data protection. To capture patient consent, a common informed consent template has been developed. It consists of different modules addressing permissions for using data and biosamples. On the technical level, a common digital representation of information from signed consent templates is needed. As the partners in the initiative are free to adopt different solutions for managing consent information (e.g. IHE BPPC or HL7 FHIR Consent Resources), we had to develop an interoperability layer. Methods First, we compiled an overview of data items required to reflect the information from the MII consent template as well as patient preferences and derived permissions. Next, we created entity-relationship diagrams to formally describe the conceptual data model underlying relevant items. We then compared this data model to conceptual models describing representations of consent information using different interoperability standards. We used the result of this comparison to derive an interoperable representation that can be mapped to common standards. Results The digital representation needs to capture the following information: (1) version of the consent, (2) consent status for each module, and (3) period of validity of the status. We found that there is no generally accepted solution to represent status information in a manner interoperable with all relevant standards. Hence, we developed a pragmatic solution, comprising codes which describe combinations of modules with a basic set of status labels. We propose to maintain these codes in a public registry called ART-DECOR. We present concrete technical implementations of our approach using HL7 FHIR and IHE BPPC which are also compatible with the open-source consent management software gICS. Conclusions The proposed digital representation is (1) generic enough to capture relevant information from a wide range of consent documents and data use regulations and (2) interoperable with common technical standards. We plan to extend our model to include more fine-grained status codes and rules for automated access control.
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Abstract
Phenotyping means the determination of clinical relevant phenotypes, e.g. by classification or calculation based on EHR data. Within the German Medical Informatics Initiative, the SMITH consortium is working on the implementation of a phenotyping pipeline. to extract, structure and normalize information from the EHR data of the hospital information systems of the participating sites; to automatically apply complex algorithms and models and to enrich the data within the research data warehouses of the distributed data integration centers with the computed results. Here we present the overall picture and essential building blocks and workflows of this concept.
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Design of Metadata Services for Clinical Data Interoperability in Germany. Stud Health Technol Inform 2019; 264:1528-1529. [PMID: 31438215 DOI: 10.3233/shti190518] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Secondary use of electronic health record (EHR) data requires a detailed description of metadata, especially when data collection and data re-use are organizationally and technically far apart. This paper describes the concept of the SMITH consortium that includes conventions, processes, and tools for describing and managing metadata using common standards for semantic interoperability. It deals in particular with the chain of processing steps of data from existing information systems and provides an overview of the planned use of metadata, medical terminologies, and semantic services in the consortium.
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Integrating Heterogeneous Data Sources for Cross-Institutional Data Sharing: Requirements Elicitation and Management in SMITH. Stud Health Technol Inform 2019; 264:1785-1786. [PMID: 31438343 DOI: 10.3233/shti190647] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
The digitization of health records and cross-institutional data sharing is a necessary precondition to improve clinical research and patient care. The SMITH project unites several university hospitals and medical faculties in order to provide medical informatics solutions for health data integration and cross-institutional communication. In this paper, we focus on requirements elicitation and management for extracting clinical data from heterogeneous subsystems and data integration based on eHealth standards such as HL7 FHIR and IHE profiles.
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Towards a Software Tool for Planning IHE-Compliant Information Systems. Stud Health Technol Inform 2019; 258:6-10. [PMID: 30942703] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
As hospital information systems are complex and the requirements for interoperability grow with the increasing networking in healthcare, careful planning becomes more and more necessary. The use of standards as described in IHE profiles, for example, are an important prerequisite for enabling interoperability. Enterprise Architecture Planning (EAP) methods should support this, but none of the currently available EAP methods offers the option of using IHE profiles. The 3LGM2IHE project wants to close this gap and implement the support of IHE profiles in the 3LGM2 tool. This paper describes how requirements for this tool were determined and presents the results.
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Abstract
INTRODUCTION This article is part of the Focus Theme of Methods of Information in Medicine on the German Medical Informatics Initiative. "Smart Medical Information Technology for Healthcare (SMITH)" is one of four consortia funded by the German Medical Informatics Initiative (MI-I) to create an alliance of universities, university hospitals, research institutions and IT companies. SMITH's goals are to establish Data Integration Centers (DICs) at each SMITH partner hospital and to implement use cases which demonstrate the usefulness of the approach. OBJECTIVES To give insight into architectural design issues underlying SMITH data integration and to introduce the use cases to be implemented. GOVERNANCE AND POLICIES SMITH implements a federated approach as well for its governance structure as for its information system architecture. SMITH has designed a generic concept for its data integration centers. They share identical services and functionalities to take best advantage of the interoperability architectures and of the data use and access process planned. The DICs provide access to the local hospitals' Electronic Medical Records (EMR). This is based on data trustee and privacy management services. DIC staff will curate and amend EMR data in the Health Data Storage. METHODOLOGY AND ARCHITECTURAL FRAMEWORK To share medical and research data, SMITH's information system is based on communication and storage standards. We use the Reference Model of the Open Archival Information System and will consistently implement profiles of Integrating the Health Care Enterprise (IHE) and Health Level Seven (HL7) standards. Standard terminologies will be applied. The SMITH Market Place will be used for devising agreements on data access and distribution. 3LGM2 for enterprise architecture modeling supports a consistent development process.The DIC reference architecture determines the services, applications and the standardsbased communication links needed for efficiently supporting the ingesting, data nourishing, trustee, privacy management and data transfer tasks of the SMITH DICs. The reference architecture is adopted at the local sites. Data sharing services and the market place enable interoperability. USE CASES The methodological use case "Phenotype Pipeline" (PheP) constructs algorithms for annotations and analyses of patient-related phenotypes according to classification rules or statistical models based on structured data. Unstructured textual data will be subject to natural language processing to permit integration into the phenotyping algorithms. The clinical use case "Algorithmic Surveillance of ICU Patients" (ASIC) focusses on patients in Intensive Care Units (ICU) with the acute respiratory distress syndrome (ARDS). A model-based decision-support system will give advice for mechanical ventilation. The clinical use case HELP develops a "hospital-wide electronic medical record-based computerized decision support system to improve outcomes of patients with blood-stream infections" (HELP). ASIC and HELP use the PheP. The clinical benefit of the use cases ASIC and HELP will be demonstrated in a change of care clinical trial based on a step wedge design. DISCUSSION SMITH's strength is the modular, reusable IT architecture based on interoperability standards, the integration of the hospitals' information management departments and the public-private partnership. The project aims at sustainability beyond the first 4-year funding period.
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Grants
- German Federal Ministry of Education and Research Grant No's. 01ZZ1609A, 01ZZ1609B, 01ZZ1609C, 01ZZ1803A, 01ZZ1803B, 01ZZ1803C, 01ZZ1803D, 01ZZ1803E, 01ZZ1803F, 01ZZ1803G, 01ZZ1803H, 01ZZ1803I, 01ZZ1803J, 01ZZ1803K, 01ZZ1803L, 01ZZ1803M, 01ZZ1803N
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Integrated Data Repository Toolkit (IDRT). Methods Inf Med 2018; 55:125-35. [DOI: 10.3414/me15-01-0082] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2015] [Accepted: 09/15/2015] [Indexed: 12/17/2022]
Abstract
SummaryBackground: In recent years, research data warehouses moved increasingly into the focus of interest of medical research. Nevertheless, there are only a few center-independent infrastructure solutions available. They aim to provide a consolidated view on medical data from various sources such as clinical trials, electronic health records, epidemiological registries or longitudinal cohorts. The i2b2 framework is a well-established solution for such repositories, but it lacks support for importing and integrating clinical data and metadata.Objectives: The goal of this project was to develop a platform for easy integration and administration of data from heterogeneous sources, to provide capabilities for linking them to medical terminologies and to allow for transforming and mapping of data streams for user-specific views.Methods: A suite of three tools has been developed: the i2b2 Wizard for simplifying administration of i2b2, the IDRT Import and Mapping Tool for loading clinical data from various formats like CSV, SQL, CDISC ODM or biobanks and the IDRT i2b2 Web Client Plugin for advanced export options. The Import and Mapping Tool also includes an ontology editor for rearranging and mapping patient data and structures as well as annotating clinical data with medical terminologies, primarily those used in Germany (ICD-10-GM, OPS, ICD-O, etc.).Results: With the three tools functional, new i2b2-based research projects can be created, populated and customized to researcher’s needs in a few hours. Amalgamating data and metadata from different databases can be managed easily. With regards to data privacy a pseudonymization service can be plugged in. Using common ontologies and reference terminologies rather than project-specific ones leads to a consistent understanding of the data semantics.Conclusions: i2b2’s promise is to enable clinical researchers to devise and test new hypothesis even without a deep knowledge in statistical programing. The approach pre -sented here has been tested in a number of scenarios with millions of observations and tens of thousands of patients. Initially mostly observant, trained researchers were able to construct new analyses on their own. Early feedback indicates that timely and extensive access to their “own” data is appreciated most, but it is also lowering the barrier for other tasks, for instance checking data quality and completeness (missing data, wrong coding).
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Introducing Technical Aspects of Research Data Management in the Leipzig Health Atlas. Stud Health Technol Inform 2018; 247:426-430. [PMID: 29677996] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
Medical research is an active field in which a wide range of information is collected, collated, combined and analyzed. Essential results are reported in publications, but it is often problematic to have the data (raw and processed), algorithms and tools associated with the publication available. The Leipzig Health Atlas (LHA) project has therefore set itself the goal of providing a repository for this purpose and enabling controlled access to it via a web-based portal. A data sharing concept in accordance to FAIR and OAIS is the basis for the processing and provision of data in the LHA. An IT architecture has been designed for this purpose. The paper presents essential aspects of the data sharing concept, the IT architecture and the methods used.
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Towards Phenotyping of Clinical Trial Eligibility Criteria. Stud Health Technol Inform 2018; 248:293-299. [PMID: 29726450] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
BACKGROUND Medical plaintext documents contain important facts about patients, but they are rarely available for structured queries. The provision of structured information from natural language texts in addition to the existing structured data can significantly speed up the search for fulfilled inclusion criteria and thus improve the recruitment rate. OBJECTIVES This work is aimed at supporting clinical trial recruitment with text mining techniques to identify suitable subjects in hospitals. METHOD Based on the inclusion/exclusion criteria of 5 sample studies and a text corpus consisting of 212 doctor's letters and medical follow-up documentation from a university cancer center, a prototype was developed and technically evaluated using NLP procedures (UIMA) for the extraction of facts from medical free texts. RESULTS It was found that although the extracted entities are not always correct (precision between 23% and 96%), they provide a decisive indication as to which patient file should be read preferentially. CONCLUSION The prototype presented here demonstrates the technical feasibility. In order to find available, lucrative phenotypes, an in-depth evaluation is required.
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Technical Environment for Developing the SNIK Ontology of Information Management in Hospitals. Stud Health Technol Inform 2017; 243:122-126. [PMID: 28883184] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
The SNIK project converts textbooks about information management in hospitals to a domain ontology that provides a shared vocabulary for institutions to model and integrate processes, data and infrastructure. To accommodate user groups with different requirements and technical backgrounds, and to support incremental and cooperative development, we create a system architecture to publish, visualize, browse and query the ontology, as well as to evaluate and improve the data quality.
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Modeling Requirements for Cohort and Register IT. Stud Health Technol Inform 2016; 228:277-281. [PMID: 27577387] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
BACKGROUND The project KoRegIT (funded by TMF e.V.) aimed to develop a generic catalog of requirements for research networks like cohort studies and registers (KoReg). The catalog supports such kind of research networks to build up and to manage their organizational and IT infrastructure. OBJECTIVES To make transparent the complex relationships between requirements, which are described in use cases from a given text catalog. By analyzing and modeling the requirements a better understanding and optimizations of the catalog are intended. There are two subgoals: a) to investigate one cohort study and two registers and to model the current state of their IT infrastructure; b) to analyze the current state models and to find simplifications within the generic catalog. METHODS Processing the generic catalog was performed by means of text extraction, conceptualization and concept mapping. Then methods of enterprise architecture planning (EAP) are used to model the extracted information. To work on objective a) questionnaires are developed by utilizing the model. They are used for semi-structured interviews, whose results are evaluated via qualitative content analysis. Afterwards the current state was modeled. Objective b) was done by model analysis. RESULTS A given generic text catalog of requirements was transferred into a model. As result of objective a) current state models of one existing cohort study and two registers are created and analyzed. An optimized model called KoReg-reference-model is the result of objective b). CONCLUSION It is possible to use methods of EAP to model requirements. This enables a better overview of the partly connected requirements by means of visualization. The model based approach also enables the analysis and comparison of the empirical data from the current state models. Information managers could reduce the effort of planning the IT infrastructure utilizing the KoReg-reference-model. Modeling the current state and the generation of reports from the model, which could be used as requirements specification for bids, is supported, too.
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Requirements on Clinical Trial Management Systems for Academic Site Management Organizations. Stud Health Technol Inform 2016; 228:292-296. [PMID: 27577390] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
As a part of the introduction of a Clinical Trial Management System (CTMS) for an Academic Site Management Organization (SMO) we had to determine the requirements such a system has to meet. By performing extensive Requirements Engineering, we aimed at raising the success of the future system and the user satisfaction. Investigations revealed the existence of TORE (Task and Object-oriented Requirements Engineering), a task-driven approach for determining requirements on user interface- and information-intensive systems. In this paper, we present an adoption of this method for our purposes, resulting in a reasonable list of requirements for CTMS acquisition.
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Automated Import of Clinical Data from HL7 Messages into OpenClinica and tranSMART Using Mirth Connect. Stud Health Technol Inform 2016; 228:317-321. [PMID: 27577395] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
Electronic data capture (EDC) tools are designed to simplify data acquisition, improving data quality and managing clinical data electronically. Some data are collected from the laboratory information management system (LIMS), which is an important data source for a study. OpenClinica is an open source clinical data management system (CDMS) for web-based electronic data capture (EDC), which is used widely in academic clinical research. TranSMART is also an open source web-based platform used for the management and analysis of different data types common in clinical and translational research. Many LIMS use the Health Level 7 standard - Version 2.x (HL7) as a message exchange protocol. In this paper, we implement Mirth Connect as a Communication Server (CS) to convert these HL7 messages either to Operational Data Model (ODM) data for the automatic import in OpenClinica or tabular-delimited text format files, whose data is uploaded in tranSMART using the tMDataLoader tool.
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Simplified Deployment of Health Informatics Applications by Providing Docker Images. Stud Health Technol Inform 2016; 228:643-647. [PMID: 27577463] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
Due to the specific needs of biomedical researchers, in-house development of software is widespread. A common problem is to maintain and enhance software after the funded project has ended. Even if many tools are made open source, only a couple of projects manage to attract a user basis large enough to ensure sustainability. Reasons for this include complex installation and configuration of biomedical software as well as an ambiguous terminology of the features provided; all of which make evaluation of software laborious. Docker is a para-virtualization technology based on Linux containers that eases deployment of applications and facilitates evaluation. We investigated a suite of software developments funded by a large umbrella organization for networked medical research within the last 10 years and created Docker containers for a number of applications to support utilization and dissemination.
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MI-Lab - A Laboratory Environment for Medical Informatics Students. Stud Health Technol Inform 2016; 228:48-52. [PMID: 27577339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
Medical research and health care highly depend on the use of information technology. There is a wide range of application systems (patient administration system, laboratory information system, communication server etc.) and heterogeneous data types (administrative data, clinical data, laboratory data, image data, genomic data etc.). Students and researchers do not often have the possibility to use productive application systems of e.g. hospitals or medical practices to gain practical experiences or examine new components and technologies. Therefore, the aim of this project is to develop a dedicated laboratory environment for patient health care and clinical research. Essential application systems were identified and a suitable architecture was designed for this purpose. It is accompanied by a teaching plan that considers learning modules for bachelor and master degrees in medical informatics. We implemented the laboratory environment called MI-Lab with multiple free and open source software components. All components are installed on virtual machines and/or Docker containers. This modular architecture creates a flexible system which can be deployed in various scenarios. The preliminary evaluation results suggests that laboratory environments like MI-Lab work well in teaching practical aspects of medical informatics and are widely accepted by students.
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Modeling Interoperable Information Systems with 3LGM² and IHE. Methods Inf Med 2015; 54:398-405. [PMID: 26394817 DOI: 10.3414/me14-02-0027] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2015] [Accepted: 09/04/2015] [Indexed: 11/09/2022]
Abstract
BACKGROUND Strategic planning of information systems (IS) in healthcare requires descriptions of the current and the future IS state. Enterprise architecture planning (EAP) tools like the 3LGM² tool help to build up and to analyze IS models. A model of the planned architecture can be derived from an analysis of current state IS models. Building an interoperable IS, i. e. an IS consisting of interoperable components, can be considered a relevant strategic information management goal for many IS in healthcare. Integrating the healthcare enterprise (IHE) is an initiative which targets interoperability by using established standards. OBJECTIVES To link IHE concepts to 3LGM² concepts within the 3LGM² tool. To describe how an information manager can be supported in handling the complex IHE world and planning interoperable IS using 3LGM² models. To describe how developers or maintainers of IHE profiles can be supported by the representation of IHE concepts in 3LGM². METHODS Conceptualization and concept mapping methods are used to assign IHE concepts such as domains, integration profiles actors and transactions to the concepts of the three-layer graph-based meta-model (3LGM²). RESULTS IHE concepts were successfully linked to 3LGM² concepts. An IHE-master-model, i. e. an abstract model for IHE concepts, was modeled with the help of 3LGM² tool. Two IHE domains were modeled in detail (ITI, QRPH). We describe two use cases for the representation of IHE concepts and IHE domains as 3LGM² models. Information managers can use the IHE-master-model as reference model for modeling interoperable IS based on IHE profiles during EAP activities. IHE developers are supported in analyzing consistency of IHE concepts with the help of the IHE-master-model and functions of the 3LGM² tool CONCLUSION The complex relations between IHE concepts can be modeled by using the EAP method 3LGM². 3LGM² tool offers visualization and analysis features which are now available for the IHE-master-model. Thus information managers and IHE developers can use or develop IHE profiles systematically. In order to improve the usability and handling of the IHE-master-model and its usage as a reference model, some further refinements have to be done. Evaluating the use of the IHE-master-model by information managers and IHE developers is subject to further research.
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The Integrated Data Repository Toolkit (IDRT): accelerating translational research infrastructures. J Clin Bioinforma 2015. [PMCID: PMC4460588 DOI: 10.1186/2043-9113-5-s1-s6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
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A comprehensive clinical research database based on CDISC ODM and i2b2. Stud Health Technol Inform 2014; 205:1115-1119. [PMID: 25160362] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
We present a working approach for a clinical research database as part of an archival information system. The CDISC ODM standard is target for clinical study and research relevant routine data, thus decoupling the data ingest process from the access layer. The presented research database is comprehensive as it covers annotating, mapping and curation of poorly annotated source data. Besides a conventional relational database the medical data warehouse i2b2 serves as main frontend for end-users. The system we developed is suitable to support patient recruitment, cohort identification and quality assurance in daily routine.
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Requirements and tasks of cohorts and registers, the German KoRegIT project. Stud Health Technol Inform 2014; 205:1085-1089. [PMID: 25160356] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
Epidemiological cohorts and registers (KoReg) are long lasting and complex research projects, which need systematic and extensive planning and steering. The aim of the KoRegIT project was to develop a generic catalogue of requirements to support the organisational- and IT-structure of KoReg. The catalogue of requirements comprises the top level (TL) tasks of the core processes. All TL were classified into the following project phases: 1. Development, 2. Operation, 3. Completion. According to the defined TL tasks, the appropriate use cases (UC) were identified. The catalogue currently specifies 45 TL tasks and 207 UC. The UC were elaborated by a short and standardized description of the task, the involved actors (human or external systems), the preconditions, which have to be fulfilled in order to realize this task, the normal flow of the task and the post conditions. The developed catalogue was reviewed by representatives of different KoReg in Germany. The draft catalogue of requirements was revised according to the reviewer's feedback and discussion. The revised and complete catalogue with all elaborated UC was reviewed again by further experts. The developed KoRegIT catalogue of requirements offers a supporting tool to set-up the organisational structures and processes of KoReg as well as the definition of the needed IT-infrastructure. In addition it can be used to optimize or to expand these structures.
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Designing a concept for an IT-infrastructure for an integrated research and treatment center. Stud Health Technol Inform 2010; 160:1319-23. [PMID: 20841898] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/29/2023]
Abstract
Healthcare and medical research in Germany are heading to more interconnected systems. New initiatives are funded by the German government to encourage the development of Integrated Research and Treatment Centers (IFB). Within an IFB new organizational structures and infrastructures for interdisciplinary, translational and trans-sectoral working relationship between existing rigid separated sectors are intended and needed. This paper describes how an IT-infrastructure of an IFB could look like, what major challenges have to be solved and what methods can be used to plan such a complex IT-infrastructure in the field of healthcare. By means of project management, system analyses, process models, 3LGM2-models and resource plans an appropriate concept with different views is created. This concept supports the information management in its enterprise architecture planning activities and implies a first step of implementing a connected healthcare and medical research platform.
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