[Data integration centers-from a concept in the Medical Informatics Initiative to its local implementation in the Network of University Medicine]. / Die Datenintegrationszentren ­ Von der Konzeption in der Medizininformatik-Initiative zur lokalen Umsetzung in einem Netzwerk Universitätsmedizin.

As part of the Medical Informatics Initiative (MII), data integration centers (DICs) have been established at 38 university and 3 non-university locations in Germany since 2018. At DICs, research and healthcare data are collected. The DICs represent an important pillar in research and healthcare. They establish the technical, organizational, and (ethical) data protection requirements to enable cross-site research with the available routine clinical data.This article presents the three main pillars of DICs: ethical-legal framework, organization, and technology. The organization of DICs and their organizational embedding and interaction are presented, as well as the technical infrastructure. The services that a DIC provides for its own location and for external researchers are explained, and the role of the DIC as an internal and external interface for strengthening cooperation and collaboration is outlined.Legal conformity, organization, and technology form the basis for the processes and structures of a DIC and are decisive for how it is integrated into the healthcare and research landscape of a location, but also for how it can react to national and European requirements and act and function as an interface to the outside world. In this context and with regard to national developments (e.g., introduction of the electronic patient file-ePA), but also international and European initiatives (e.g., European Health Data Space-EHDS), the DIC will play a central role in the future.

Functional Requirements for Medical Data Integration into Knowledge Management Environments: Requirements Elicitation Approach Based on Systematic Literature Analysis.

BACKGROUND: In patient care, data are historically generated and stored in heterogeneous databases that are domain specific and often noninteroperable or isolated. As the amount of health data increases, the number of isolated data silos is also expected to grow, limiting the accessibility of the collected data. Medical informatics is developing ways to move from siloed data to a more harmonized arrangement in information architectures. This paradigm shift will allow future research to integrate medical data at various levels and from various sources. Currently, comprehensive requirements engineering is working on data integration projects in both patient care- and research-oriented contexts, and it is significantly contributing to the success of such projects. In addition to various stakeholder-based methods, document-based requirement elicitation is a valid method for improving the scope and quality of requirements. OBJECTIVE: Our main objective was to provide a general catalog of functional requirements for integrating medical data into knowledge management environments. We aimed to identify where integration projects intersect to derive consistent and representative functional requirements from the literature. On the basis of these findings, we identified which functional requirements for data integration exist in the literature and thus provide a general catalog of requirements. METHODS: This work began by conducting a literature-based requirement elicitation based on a broad requirement engineering approach. Thus, in the first step, we performed a web-based systematic literature review to identify published articles that dealt with the requirements for medical data integration. We identified and analyzed the available literature by applying the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. In the second step, we screened the results for functional requirements using the requirements engineering method of document analysis and derived the requirements into a uniform requirement syntax. Finally, we classified the elicited requirements into a category scheme that represents the data life cycle. RESULTS: Our 2-step requirements elicitation approach yielded 821 articles, of which 61 (7.4%) were included in the requirement elicitation process. There, we identified 220 requirements, which were covered by 314 references. We assigned the requirements to different data life cycle categories as follows: 25% (55/220) to data acquisition, 35.9% (79/220) to data processing, 12.7% (28/220) to data storage, 9.1% (20/220) to data analysis, 6.4% (14/220) to metadata management, 2.3% (5/220) to data lineage, 3.2% (7/220) to data traceability, and 5.5% (12/220) to data security. CONCLUSIONS: The aim of this study was to present a cross-section of functional data integration-related requirements defined in the literature by other researchers. The aim was achieved with 220 distinct requirements from 61 publications. We concluded that scientific publications are, in principle, a reliable source of information for functional requirements with respect to medical data integration. Finally, we provide a broad catalog to support other scientists in the requirement elicitation phase.

Towards a comprehensive and interoperable representation of consent-based data usage permissions in the German medical informatics initiative.

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.

Barriers and Facilitators to the Implementation of eHealth Services: Systematic Literature Analysis.

BACKGROUND: The field of eHealth has a history of more than 20 years. During that time, many different eHealth services were developed. However, factors influencing the adoption of such services were seldom the main focus of analyses. For this reason, organizations adopting and implementing eHealth services seem not to be fully aware of the barriers and facilitators influencing the integration of eHealth services into routine care. OBJECTIVE: The objective of this work is to provide (1) a comprehensive list of relevant barriers to be considered and (2) a list of facilitators or success factors to help in planning and implementing successful eHealth services. METHODS: For this study, a twofold approach was applied. First, we gathered experts' current opinions on facilitators and barriers in implementing eHealth services via expert discussions at two health informatics conferences held in Europe. Second, we conducted a systematic literature analysis concerning the barriers and facilitators for the implementation of eHealth services. Finally, we merged the results of the expert discussions with those of the systematic literature analysis. RESULTS: Both expert discussions (23 and 10 experts, respectively) identified 15 barriers and 31 facilitators, whereas 76 barriers and 268 facilitators were found in 38 of the initial 56 articles published from 12 different countries. For the analyzed publications, the count of distinct barriers reported ranged from 0 to 40 (mean 10.24, SD 8.87, median 8). Likewise, between 0 and 48 facilitators were mentioned in the literature (mean 9.18, SD 9.33, median 6). The combination of both sources resulted in 77 barriers and 292 facilitators for the adoption and implementation of eHealth services. CONCLUSIONS: This work contributes a comprehensive list of barriers and facilitators for the implementation and adoption of eHealth services. Addressing barriers early, and leveraging facilitators during the implementation, can help create eHealth services that better meet the needs of users and provide higher benefits for patients and caregivers.

Large-Scale Standardized Image Integration for Secondary Use Research Projects.

Imaging techniques are a cornerstone of today's medicine and can be crucial for a successful therapy. But in addition, the generated imaging series are an important resource for new informatics' methods, especially in the field of artificial intelligence. This paper describes the success of integrating clinical routine imaging data into a standardized format for research purposes. Thus, we designed an integration flow and successfully implemented it in the local data integration center of University Hospital Schleswig-Holstein. The flow integrates imaging series and radiological reports from the primary system into an openEHR repository with enrichment by semantic codes for better findability and retrieval using HL7 FHIR. As a result, 6.6 million radiological studies with 29 million image series are now available for further medical (informatics) research.

An Image Retrieval Pipeline in a Medical Data Integration Center.

Medical images need annotations with high-level semantic descriptors, so that domain experts can search for the desired dataset among an enormous volume of visual media within a Medical Data Integration Center. This article introduces a processing pipeline for storing and annotating DICOM and PNG imaging data by applying Elasticsearch, S3 and Deep Learning technologies. The proposed method processes both DICOM and PNG images to generate annotations. These image annotations are indexed in Elasticsearch with the corresponding raw data paths, where they can be retrieved and analyzed.

Structured Data Retrieval and Analysis of HL7 v2 Messages with Elasticsearch.

The era of the electronic health record (EHR) requires lots of semantic interoperability for data sharing and reusability. We select HL7 v2 messages as the most common structured data type in hospital information systems, to investigate the plausibility of using Elasticsearch (ES) as a healthcare search engine and data analytics tool. Due to the facts, Elasticsearch can be integrated as a powerful searchable database for practical healthcare applications, to analyze structured healthcare data from various locations. It allows easy and efficient searching for complex query tasks.

Evaluation of data completeness in the electronic health record for the purpose of patient recruitment into clinical trials: a retrospective analysis of element presence.

BACKGROUND: Computerized clinical trial recruitment support is one promising field for the application of routine care data for clinical research. The primary task here is to compare the eligibility criteria defined in trial protocols with patient data contained in the electronic health record (EHR). To avoid the implementation of different patient definitions in multi-site trials, all participating research sites should use similar patient data from the EHR. Knowledge of the EHR data elements which are commonly available from most EHRs is required to be able to define a common set of criteria. The objective of this research is to determine for five tertiary care providers the extent of available data compared with the eligibility criteria of randomly selected clinical trials. METHODS: Each participating study site selected three clinical trials at random. All eligibility criteria sentences were broken up into independent patient characteristics, which were then assigned to one of the 27 semantic categories for eligibility criteria developed by Luo et al. We report on the fraction of patient characteristics with corresponding structured data elements in the EHR and on the fraction of patients with available data for these elements. The completeness of EHR data for the purpose of patient recruitment is calculated for each semantic group. RESULTS: 351 eligibility criteria from 15 clinical trials contained 706 patient characteristics. In average, 55% of these characteristics could be documented in the EHR. Clinical data was available for 64% of all patients, if corresponding data elements were available. The total completeness of EHR data for recruitment purposes is 35%. The best performing semantic groups were 'age' (89%), 'gender' (89%), 'addictive behaviour' (74%), 'disease, symptom and sign' (64%) and 'organ or tissue status' (61%). No data was available for 6 semantic groups. CONCLUSIONS: There exists a significant gap in structure and content between data documented during patient care and data required for patient eligibility assessment. Nevertheless, EHR data on age and gender of the patient, as well as selected information on his disease can be complete enough to allow for an effective support of the manual screening process with an intelligent preselection of patients and patient data.

Interdisciplinary Teams in Health Informatics: Using FHIR Standards to Share Computable Knowledge.

The use and shareability of Clinical Quality Language (CQL) artefacts is an important aspect in enabling the exchange and interoperability of clinical data to support both clinical decisions and research in the medical informatics field. This paper, while basing on use cases and synthetic data, developed purposeful CQL reusable libraries to showcase the possibilities of multidisciplinary teams and how CQLs could be best used to support clinical decision making.

First experiences in implementing a software-based support for patient recruitment at Heidelberg university hospital.

Clinical trials have often got problems in achieving their recruitment target. Making the recruitment process more efficient and timely is tried to achieve in Heidelberg by implementing a software-based system to support patient recruitment. The architecture implemented in Heidelberg was developed in a multi-center research project named 'EHR-based support for patient recruitment'. The architecture is generic as five distinct university hospitals developed it and found it implementable. The same architecture is also implemented at four other university hospitals in Germany. The system was implemented into the existing system architecture and can thus be implemented by the vendor of the system. This makes the system available to all customers of named systems.

ETL Processes for Integrating Healthcare Data - Tools and Architecture Patterns.

Improving the interoperability of healthcare information systems is a crucial clinical care issue involving disparate but coexisting information systems. However, healthcare organizations are also facing the dilemma of choosing the right ETL tool and architecture pattern as data warehouse enterprises. This article gives an overview of current ETL tools for healthcare data integration. In addition, we demonstrate three ETL processes for clinical data integration using different ETL tools and architecture patterns, which map data from various data sources (e.g. MEONA and ORBIS) to diverse standards (e.g. FHIR and openEHR). Depending on the project's technical requirements, we choose our ETL tool and software architecture pattern to boost team efficiency.

Strategies and Recommendation for Data Loading of FHIR-Based Data Marts with Focus on GDPR Compliance.

Interoperability and portability of healthcare data to enable research in the healthcare sector is an important factor towards precision medicine and a learning health system. With many safety-nets put in place like the European General Data Protection Regulation, and local standards like the broad consent set up by the German Medical Informatics Initiative, management and compliance to these standards across all systems and clinical data repositories becomes a daunting task. An appropriate process needs to be established especially when patient data is transferred to and from different systems and standards. On extraction and transforming, an appropriate method of loading the modified data to a destination where it can be read and accessed needs to be established besides functional compliance by the repository systems. This paper makes recommendations in relation to data load strategies while working with FHIR server-based data marts.

One Conference, Three Proceedings - Which Papers Should I Submit and How? A Publication Strategy for Young Scientists Regarding the GMDS Annual Conference and Beyond (Editorial).

The primary intention of any scientific work is to share the gained knowledge and to contribute to the knowledge and progress in the scientific domain. The wide range of journals and conferences, each with specific submission requirements, can be difficult to navigate, especially for young scientists without extensive experience. But a suitable publication strategy can be helpful, especially at the beginning of a scientific career. Using the annual conference of the German Association for Medical Informatics, Biometry and Epidemiology (GMDS) e.V. as an example, this editorial highlights fundamental differences, advantages and disadvantages, as well as assistance in selecting the right form of submission.

Applicability of Different Electronic Record Types for Use in Patient Recruitment Support Systems: Comparative Analysis.

BACKGROUND: Clinical trials constitute an important pillar in medical research. It is beneficial to support recruitment for clinical trials using software tools, so-called patient recruitment support systems; however, such information technology systems have not been frequently used to date. Because medical information systems' underlying data collection methods strongly influence the benefits of implementing patient recruitment support systems, we investigated patient recruitment support system requirements and corresponding electronic record types such as electronic medical record, electronic health record, electronic medical case record, personal health record, and personal cross-enterprise health record. OBJECTIVE: The aim of this study was to (1) define requirements for successful patient recruitment support system deployment and (2) differentiate and compare patient recruitment support system-relevant properties of different electronic record types. METHODS: In a previous study, we gathered requirements for patient recruitment support systems from literature and unstructured interviews with stakeholders (15 patients, 3 physicians, 5 data privacy experts, 4 researchers, and 5 staff members of hospital administration). For this investigation, the requirements were amended and categorized based on input from scientific sessions. Based on literature with a focus on patient recruitment support system-relevant properties, different electronic record types (electronic medical record, electronic health record, electronic medical case record, personal health record and personal cross-enterprise health record) were described in detail. We also evaluated which patient recruitment support system requirements can be achieved for each electronic record type. RESULTS: Patient recruitment support system requirements (n=16) were grouped into 4 categories (consent management, patient recruitment management, trial management, and general requirements). All 16 requirements could be partially met by at least 1 type of electronic record. Only 1 requirement was fully met by all 5 types. According to our analysis, personal cross-enterprise health records fulfill most requirements for patient recruitment support systems. They demonstrate advantages especially in 2 domains (1) supporting patient empowerment and (2) granting access to the complete medical history of patients. CONCLUSIONS: In combination with patient recruitment support systems, personal cross-enterprise health records prove superior to other electronic record types, and therefore, this integration approach should be further investigated.

Telemonitoring of Real-World Health Data in Cardiology: A Systematic Review.

BACKGROUND: New sensor technologies in wearables and other consumer health devices open up promising opportunities to collect real-world data. As cardiovascular diseases remain the number one reason for disease and mortality worldwide, cardiology offers potent monitoring use cases with patients in their out-of-hospital daily routines. Therefore, the aim of this systematic review is to investigate the status quo of studies monitoring patients with cardiovascular risks and patients suffering from cardiovascular diseases in a telemedical setting using not only a smartphone-based app, but also consumer health devices such as wearables and other sensor-based devices. METHODS: A literature search was conducted across five databases, and the results were examined according to the study protocols, technical approaches, and qualitative and quantitative parameters measured. RESULTS: Out of 166 articles, 8 studies were included in this systematic review; these cover interventional and observational monitoring approaches in the area of cardiovascular diseases, heart failure, and atrial fibrillation using various app, wearable, and health device combinations. CONCLUSIONS: Depending on the researcher's motivation, a fusion of apps, patient-reported outcome measures, and non-invasive sensors can be orchestrated in a meaningful way, adding major contributions to monitoring concepts for both individual patients and larger cohorts.

Mapping Medication Metadata from the ABDA Data Model to an OpenEHR Medication Archetype: A Qualitative Analysis.

Integrating data from various source systems to gain knowledge and meaningful data about patients for care and research is challenging. This work demonstrates how medication knowledge data from the database of the Federal Union of German Associations of Pharmacists (ABDA) can be used for storing and annotating medicinal products in an openEHR medication archetype.

Provenance Solutions for Medical Research in Heterogeneous IT-Infrastructure: An Implementation Roadmap.

Research data generated in large projects raise challenges about not only data analytics but also data quality assessments and data governance. The provenance of a data set - that is the history of data sets - holds information relevant to technicians and non-technicians and is able to answer questions regarding data quality, transparency, and more. We propose an implementation roadmap to extract, store, and utilize provenance records in order to make provenance available to data analysts, research subjects, privacy officers, and machines (machine readability). Each aspect is tackled separately, resulting in the implementation of a provenance toolbox. We aim to do so within the context of HiGHmed, a research consortium established within the medical informatics initiative in Germany. In this testbed of federated IT-infrastructures, the toolbox shall assist each stakeholder in answering domain-specific and domain-agnostic questions regarding the provenance of data sets. This way, we will improve data re-use, transparency, and reproducibility.

HiGHmed - An Open Platform Approach to Enhance Care and Research across Institutional Boundaries.

INTRODUCTION: This article is part of the Focus Theme of Methods of Information in Medicine on the German Medical Informatics Initiative. HiGHmed brings together 24 partners from academia and industry, aiming at improvements in care provision, biomedical research and epidemiology. By establishing a shared information governance framework, data integration centers and an open platform architecture in cooperation with independent healthcare providers, the meaningful reuse of data will be facilitated. Complementary, HiGHmed integrates a total of seven Medical Informatics curricula to develop collaborative structures and processes to train medical informatics professionals, physicians and researchers in new forms of data analytics. GOVERNANCE AND POLICIES: We describe governance structures and policies that have proven effective during the conceptual phase. These were further adapted to take into account the specific needs of the development and networking phase, such as roll-out, carerelated aspects and our focus on curricula development in Medical Inform atics. ARCHITECTURAL FRAMEWORK AND METHODOLOGY: To address the challenges of organizational, technical and semantic interoperability, a concept for a scalable platform architecture, the HiGHmed Platform, was developed. We outline the basic principles and design goals of the open platform approach as well as the roles of standards and specifications such as IHE XDS, openEHR, SNOMED CT and HL7 FHIR. A shared governance framework provides the semantic artifacts which are needed to establish semantic interoperability. USE CASES: Three use cases in the fields of oncology, cardiology and infection control will demonstrate the capabilities of the HiGHmed approach. Each of the use cases entails diverse challenges in terms of data protection, privacy and security, including clinical use of genome sequencing data (oncology), continuous longitudinal monitoring of physical activity (cardiology) and cross-site analysis of patient movement data (infection control). DISCUSSION: Besides the need for a shared governance framework and a technical infrastructure, backing from clinical leaders is a crucial factor. Moreover, firm and sustainable commitment by participating organizations to collaborate in further development of their information system architectures is needed. Other challenges including topics such as data quality, privacy regulations, and patient consent will be addressed throughout the project.

Towards a Holistic Biomedical Information Platform for Primary and Secondary Use Settings.

BACKGROUND: Clinical information is often used for biomedical research. Data warehouses can help providing researchers with data and the opportunity to find eligible participants for clinical trials. OBJECTIVES: To define an information platform for healthcare and biomedical research based on requirements by clinicians and researchers. METHODS: Interviews with clinicians, researchers, data privacy officers, IT and hospital administration combined with a questionnaire sent to 60 medical departments at our hospital were conducted. RESULTS: Resulting requirements were grouped and a platform architecture was designed based on the requirements. CONCLUSION: Requirements lead to a single platform supporting both, patient care and biomedical research.

Implementing the Patient Portal of the PEHR in the Metropolitan Region Rhine-Neckar - Experiences with Liferay.

A patient portal with access to a personal cross-enterprise electronic health record (PEHR) had to be developed for the project "INFormation technology for PATient-oriented healthcare in the Rhine-Neckar metropolitan region" (INFOPAT). Liferay was chosen as the platform technology in previous researches. Multiple portlets for patients, study members, security officers and administrators had been developed in Java. In this paper all portlets are presented. For three portlets the communication between them, Liferay and the PEHR are described in detail. To communicate with the PEHR a façade called IHE Connector had been implemented too. Despite the broad functionality of the Liferay Core some workarounds had to be implemented. The lack of information in the provided documentation of Liferay lead to delays in development. The Liferay IDE and Liferay itself showed an unstable state.