A Multimodal Lifestyle Psychosocial Survivorship Program in Young Cancer Survivors: The CARE for CAYA Program-A Randomized Clinical Trial Embedded in a Longitudinal Cohort Study.

Importance: There is a lack of trials examining the effect of counseling interventions for child, adolescent, and younger adult (CAYA) cancer survivors. Objective: To assess lifestyle habits and the psychosocial situation of CAYAs to determine the efficacy of needs-based interventions in the CARE for CAYA program (CFC-P). Design, Setting, and Participants: The CFC-P was conducted as a multicenter program in 14 German outpatient clinics, mainly university cancer centers. Recruitment began January 1, 2018; a randomized clinical trial was conducted until July 15, 2019; and intervention was continued as a longitudinal cohort study until March 31, 2021. Data preparation was conducted from April 1, 2021, and analysis was conducted from August 14, 2021, to May 31, 2022. Herein, predefined confirmatory analyses pertain to the RCT and descriptive results relate to the overall longitudinal study. Data analysis was based on the full analysis set, which is as close as possible to the intention-to-treat principle. Intervention: A comprehensive assessment determined needs in physical activity, nutrition and psychooncology. Those with high needs participated in 1 to 3 modules. In the RCT, the IG received 5 counseling sessions plus newsletters, while the control group CG received 1 counseling session. Main Outcomes and Measures: The primary outcome was the change in the rate of CAYAs with high needs at 52 weeks. Secondary outcomes were feasibility, modular-specific end points, satisfaction, quality of life, and fatigue. Results: Of 1502 approached CAYAs aged 15 to 39 years, 692 declined participation. Another 22 CAYAs were excluded, resulting in 788 participants. In the randomized clinical trial, 359 CAYAs were randomized (intervention group [IG], n = 183; control group [CG], n = 176), and 274 were followed up. In the RCT, the median age was 25.0 (IQR, 19.9-32.2) years; 226 were female (63.0%) and 133 male (37.0%). After 52 weeks, 120 CAYAs (87.0%) in the IG and 115 (86.5%) in the CG still had a high need in at least 1 module (odds ratio, 1.04; 95% CI, 0.51-2.11; P = .91). Both groups reported reduced needs, improved quality of life, reduced fatigue, and high satisfaction with the CFC-P. Conclusions and Relevance: In this randomized clinical trial, the implementation of a lifestyle program in this cohort was deemed necessary, despite not meeting the primary outcome. The interventions did not alter the rate of high needs. The results may provide guidance for the development of multimodal interventions in the follow-up care of CAYAs. Trial Registration: German Clinical Trial Register: DRKS00012504.

Mettertron - Bridging Metadata Repositories and Terminology Servers.

To provide clinical data in distributed research architectures, a fundamental challenge involves defining and distributing suitable metadata within Metadata Repositories. Especially for structured data, data elements need to be bound against suitable terminologies; otherwise, other systems will only be able to interpret the data with complex and error-prone manual involvement. As current Metadata Repository implementations lack support for querying externally defined terminologies in FHIR terminology servers, we propose an intermediate solution that uses appropriate annotations on metadata elements to allow run-time Terminology Services mediated queries of that metadata. This allows a very clear separation of concerns between the two related systems, greatly simplifying terminological maintenance. The system performed well in a prototypical deployment.

Implementation of a clinical long-term follow-up database for adult childhood cancer survivors in Germany: a feasibility study at two specialised late effects clinics.

PURPOSE: Childhood cancer survivors (CCS) are at risk for increased morbidity and reduced quality of life associated with treatment-related late effects. In Germany, however, only a few of the more than 40,000 CCS registered in the German Childhood Cancer Registry (GCCR) currently benefit from adequate clinical long-term follow-up (LTFU) structures. To establish a comprehensive knowledge base on CCS' long-term health in Germany, a database was developed in cooperation with the GCCR. Following a first evaluation phase at two German university centres, this database will be implemented more widely within Germany allowing longitudinal documentation of clinical LTFU data. METHODS: The feasibility study cohort comprised 208 CCS aged 18 or older whose medical, mental and psychosocial health data were collected during routine LTFU or first clinic visits in adult care. CCS were enrolled from 04/2021 to 12/2022, and data entry was completed by 03/2023. Descriptive data analysis was conducted. All CCS were stratified into three risk groups (RG) based on their individual risk for developing late effects resulting from their respective diagnoses and treatments. RESULTS: Chronic health conditions of various organ systems associated with late and long-term effects of cancer therapy affected CCS in all RG supporting the clinical relevance of risk-adapted LTFU. Enrolment into the database was feasible and broadly accepted amongst CCS. CONCLUSION: Implementation of a clinical follow-up care infrastructure and database in Germany will pave the way to collect clinically evaluated and regularly updated health data of potentially over 40,000 German CCS and facilitate future national and international cooperation.

TermiCron - Bridging the Gap Between FHIR Terminology Servers and Metadata Repositories.

The large variability of data models, specifications, and interpretations of data elements is particular to the healthcare domain. Achieving semantic interoperability is the first step to enable reuse of healthcare data. To ensure interoperability, metadata repositories (MDR) are increasingly used to manage data elements on a structural level, while terminology servers (TS) manage the ontologies, terminologies, coding systems and value sets on a semantic level. In practice, however, this strict separation is not always followed; instead, semantical information is stored and maintained directly in the MDR, as a link between both systems is missing. This may be reasonable up to a certain level of complexity, but it quickly reaches its limitations with increasing complexity. The goal of this approach is to combine both components in a compatible manner. We present TermiCron, a synchronization engine that provides synchronized value sets from TS in MDRs, including versioning and annotations. Prototypical results were shown for the terminology server Ontoserver and two established MDR systems. Bridging the semantic and structural gap between the two infrastructure components, this approach enables shared use of metadata and reuse of corresponding health information by establishing a clear separation of the two systems and thus serves to strengthen reuse as well as to increase quality.

TerminoDiff - Detecting Semantic Differences in HL7 FHIR CodeSystems.

While HL7 FHIR and its terminology package have seen a rapid uptake by the research community, in no small part due to the wide availability of tooling and resources, there are some areas where tool availability is still lacking. In particular, the comparison of terminological resources, which supports the work of terminologists and implementers alike, has not yet been sufficiently addressed. Hence, we present TerminoDiff, an application to semantically compare FHIR R4 CodeSystem resources. Our tool considers differences across all levels required, i.e. metadata and concept differences, as well as differences in the edge graph, and surfaces them in a visually digestible fashion.

Understanding the Nature of Metadata: Systematic Review.

BACKGROUND: Metadata are created to describe the corresponding data in a detailed and unambiguous way and is used for various applications in different research areas, for example, data identification and classification. However, a clear definition of metadata is crucial for further use. Unfortunately, extensive experience with the processing and management of metadata has shown that the term "metadata" and its use is not always unambiguous. OBJECTIVE: This study aimed to understand the definition of metadata and the challenges resulting from metadata reuse. METHODS: A systematic literature search was performed in this study following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines for reporting on systematic reviews. Five research questions were identified to streamline the review process, addressing metadata characteristics, metadata standards, use cases, and problems encountered. This review was preceded by a harmonization process to achieve a general understanding of the terms used. RESULTS: The harmonization process resulted in a clear set of definitions for metadata processing focusing on data integration. The following literature review was conducted by 10 reviewers with different backgrounds and using the harmonized definitions. This study included 81 peer-reviewed papers from the last decade after applying various filtering steps to identify the most relevant papers. The 5 research questions could be answered, resulting in a broad overview of the standards, use cases, problems, and corresponding solutions for the application of metadata in different research areas. CONCLUSIONS: Metadata can be a powerful tool for identifying, describing, and processing information, but its meaningful creation is costly and challenging. This review process uncovered many standards, use cases, problems, and solutions for dealing with metadata. The presented harmonized definitions and the new schema have the potential to improve the classification and generation of metadata by creating a shared understanding of metadata and its context.

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.

Hands on the Medical Informatics Initiative Core Data Set - Lessons Learned from Converting the MIMIC-IV.

With the steady increase in the connectivity of the healthcare system, new requirements and challenges are emerging. In addition to the seamless exchange of data between service providers on a national level, the local legacy data must also meet the new requirements. For this purpose, the applications used must be tested securely and sufficiently. However, the availability of suitable and realistic test data is not always given. Therefore, this study deals with the creation of test data based on real electronic health record data provided by the Medical Information Mart for Intensive Care (MIMIC-IV) database. In addition to converting the data to the current FHIR R4, conversion to the core data sets of the German Medical Informatics Initiative was also presented and made available. The test data was generated to simulate a legacy data transfer. Moreover, four different FHIR servers were tested for performance. This study is the first step toward comparable test scenarios around shared datasets and promotes comparability among providers on a national level.

Providing ART-DECOR ValueSets via FHIR Terminology Servers - A Technical Report.

To ensure semantic interoperability within healthcare systems, using common, curated terminological systems to identify relevant concepts is of fundamental importance. The HL7 FHIR standard specifies means of modelling terminological systems and appropriate ways of accessing and querying these artefacts within a terminology server. Hence, initiatives towards healthcare interoperability like IHE specify not only software interfaces, but also common codes in the form of value sets and code systems. The way in which these coding tables are provided is not necessarily compatible to the current version of the HL7 FHIR specification and therefore cannot be used with current HL7 FHIR-based terminology servers. This work demonstrates a conversion of terminological resources specified by the Integrating the Healthcare Initiative in the ART-DECOR platform, partly available in HL7 FHIR, to ensure that they can be used within a HL7 FHIR-based terminological server. The approach itself can be used for other terminological resources specified within ART-DECOR but can also be used as the basis for other code-driven conversions of proprietary coding schemes.

APERITIF - Automatic Patient Recruiting for Clinical Trials Based on HL7 FHIR.

Clinical trials are carried out to prove the safety and effectiveness of new interventions and therapies. As diseases and their causes continue to become more specific, so do inclusion and exclusion criteria for trials. Patient recruitment has always been a challenge, but with medical progress, it becomes increasingly difficult to achieve the necessary number of cases. In Germany, the Medical Informatics Initiative is planning to use the central application and registration office to conduct feasibility analyses at an early stage and thus to identify suitable project partners. This approach aims to technically adapt/integrate the envisioned infrastructure in such a way that it can be used for trial case number estimation for the planning of multicenter clinical trials. We have developed a fully automated solution called APERITIF that can identify the number of eligible patients based on free-text eligibility criteria, taking into account the MII core data set and based on the FHIR standard. The evaluation showed a precision of 62.64 % for inclusion criteria and a precision of 66.45 % for exclusion criteria.

Desiderata for a Synthetic Clinical Data Generator.

The current movement in Medical Informatics towards comprehensive Electronic Health Records (EHRs) has enabled a wide range of secondary use cases for this data. However, due to a number of well-justified concerns and barriers, especially with regards to information privacy, access to real medical records by researchers is often not possible, and indeed not always required. An appealing alternative to the use of real patient data is the employment of a generator for realistic, yet synthetic, EHRs. However, we have identified a number of shortcomings in prior works, especially with regards to the adaptability of the projects to the requirements of the German healthcare system. Based on three case studies, we define a non-exhaustive list of requirements for an ideal generator project that can be used in a wide range of localities and settings, to address and enable future work in this regard.

openEHR Mapper - A Tool to Fuse Clinical and Genomic Data Using the openEHR Standard.

Precision medicine is an emerging and important field for health care. Molecular tumor boards use a combination of clinical and molecular data, such as somatic tumor mutations to decide on personalized therapies for patients who have run out of standard treatment options. Personalized treatment decisions require clinical data from the hospital information system and mutation data to be accessible in a structured way. Here we introduce an open data platform to meet these requirements. We use the openEHR standard to create an expert-curated data model that is stored in a vendor-neutral format. Clinical and molecular patient data is integrated into cBioPortal, a warehousing solution for cancer genomic studies that is extended for use in clinical routine for molecular tumor boards. For data integration, we developed openEHR Mapper, a tool that allows to (i) process input data, (ii) communicate with the openEHR repository, and (iii) export the data to cBioPortal. We benchmarked the mapper performance using XML and JSON as serialization format and added caching capabilities as well as multi-threading to the openEHR Mapper.

Analysis of ISO/TS 21526 Towards the Extension of a Standardized Query API.

Metadata is often used for different tasks in the field of medical informatics: semantic description of data, quality validation, data integration, or information retrieval. Metadata definitions are captured and curated in time-consuming tasks and stored in metadata repositories that manage and preserve the metadata. Due to technical and legal restrictions, metadata is rarely as easily accessible and interoperable as it is necessary for modern information systems. In a previous study, a uniform interface based on the widely used ISO/IEC 11179 and the Facebook data retrieval language GraphQL was introduced as a solution to these technical obstacles. In the meantime, the ISO standard 21526 has been published, a recent version designed with a strong focus on health informatics. While it is conceptually oriented on the metamodel in ISO 11179, a number of extensions but also restructurings have been introduced. In this study, the authors investigated the difference between ISO 11179 and ISO 21526 and extended the unified metadata query interface to be future-proof and in particular, to support the semantic extensions of ISO 21526.

A Smart Mapping Editor for Standardised Data Transformation.

The integration of heterogeneous healthcare data sources is a necessary process to enable the secondary use valuable information in clinical research. Data integration is time-consuming for data stewards. The transformation using predefined rules for data harmonization can reduce the time-consuming and error-prone work and ease the data integration at various sites. In our study, we examined various script(ing) languages to find the most suitable candidate for definition of transformation rules and implement a smart editor which supports the data stewards in selecting rules reusing them. Thereby, it also provides an automatic and seamless documentation to strengthen the reliability of the defined transformation rules.

One Step Away from Technology but One Step Towards Domain Experts-MDRBridge: A Template-Based ISO 11179-Compliant Metadata Processing Pipeline.

BACKGROUND: Secondary use of routine medical data relies on a shared understanding of given information. This understanding is achieved through metadata and their interconnections, which can be stored in metadata repositories (MDRs). The necessity of an MDR is well understood, but the local work on metadata is a time-consuming and challenging process for domain experts. OBJECTIVE: To support the identification, collection, and provision of metadata in a predefined structured manner to foster consolidation. A particular focus is placed on user acceptance. METHODS: We propose a software pipeline MDRBridge as a practical intermediary for metadata capture and processing, based on MDRSheet, an ISO 11179-3 compliant template using popular spreadsheet software. It serves as a practical mediator for metadata acquisition and processing in a broader pipeline. Due to the different origins of the metadata, both manual entry and automatic extractions from application systems are supported. To enable the export of collected metadata into external MDRs, a mapping of ISO 11179 to Clinical Data Interchange Standards Consortium (CDISC) Operational Data Model (ODM) was developed. RESULTS: MDRSheet is embedded in the processing pipeline MDRBridge and delivers metadata in the CDISC ODM format for further use in MDRs. This approach is used to interactively unify core datasets, import existing standard datasets, and automatically extract all defined data elements from source systems. The involvement of clinical domain experts improved significantly due to minimal changes within their usual work routine. CONCLUSION: A high degree of acceptance was achieved by adapting the working methods of clinical domain experts. The designed process is capable of transforming all relevant data elements according to the ISO 11179-3 format. MDRSheet is used as an intermediate format to present the information at a glance and to allow editing or supplementing by domain experts.

Towards a Federation of Metadata Repositories: Addressing Technical Interoperability.

The utilisation of metadata repositories increasingly promotes secondary use of routinely collected data. However, this has not yet solved the problem of data exchange across organisational boundaries. The local description of a metadata set must also be exchangeable for flawless data exchange. In previous work, a metadata exchange language QL4MDR was developed. This work aimed to examine the applicability of this exchange language. For this purpose, existing MDR implementations were identified and systematically inspected and roughly divided into two categories to distinguish between data integration and query integration. It has been shown that all the implementations can be adapted to QL4MDR. The integration of metadata is an important first step; it enables the exchange of information, which is so urgently needed for the further processing of instance data, from the metadata mappings to the transformation rules.

Scientific Challenge in eHealth: MAPPATHON, a Metadata Mapping Challenge.

Scientific challenges based on benchmark data enable the comparison and evaluation of different algorithms and take place regularly in scientific disciplines like medical image processing, text mining or genetics. The idea of a challenge is rarely applied within the eHealth community. Mappathon is a metadata mapping challenge that asks for methods to find corresponding data elements within similar datasets and to correlate data elements among each other.

Practical Extension of Provenance to Healthcare Data Based on the W3C PROV Standard.

Secondary use of healthcare data is dependent on the availability of provenance data for assessing its quality, reliability or trustworthiness. Usually, instance-level data that might be communicated by HL7 interfaces entail limited metadata about involved software systems, persons or organizations bearing responsibility for those systems. This paper proposes a strategy for capturing interoperable provenance data needed by data stewards for assessing healthcare data that are reused in a research context. Aimed at a realistic level of granularity even system-level metadata will support a data steward trying to trace the origins or provenance of healthcare data that have been transferred to the research context. Those metadata are extracted from the 3LGM2-system, used for modelling hospital information systems. Based on the W3C provenance specification interrelated activities, entities and agents can be integrated and stored in RDF triple stores and therefore queried and visualized.

Using Graph Tools on Metadata Repositories.

To exchange data across several sites or to interpret it at a later point in time, it is necessary to create a general understanding of the data. As a standard practice, this understanding is achieved through metadata. These metadata are usually stored in relational databases, so-called metadata repositories (MDR). Typical functions of such an MDR include pure storage, administration and other specific metadata functionalities such as finding relations among data elements. This results in a multitude of connections between the data elements, which can be described as highly interconnected graphs. To use alternative databases such as graph databases for modelling and visualisation it has already been proven to be beneficial in previous studies. The objective of this work is to evaluate how on-board techniques rely on matching and mapping using a graph database. Different datasets relating to cancer were entered, and algorithms for metadata management were applied.