The Registry Data Warehouse in the European Reference Network for Rare Respiratory Diseases – Background, Conception and Implementation

Schaaf, Jannik; Chalmers, James D.; Omran, Heymut; Pennekamp, Petra; Sitbon, Olivier; Wagner, Thomas; Reis, Abílio; Kadioglu, Dennis; Storf, Holger

doi:10.3233/shti210049

Cited by 4 publications

(4 citation statements)

References 6 publications

(8 reference statements)

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“…Only one article included all four data items ( 24 ) and only one discussed three FAIR challenges, but not including the findable item ( 34 ). Eight articles combined two out of four FAIR data items in different combinations: five studies concentrated on interoperability with reusability ( 35 , 47 ); with accessibility ( 12 , 57 ) and with findability ( 58 ); three articles focused on findable – with accessible ( 32 , 47 ) and with reusability ( 42 ). All five other publications explored only one FAIR data item, with interoperability ( 38 , 45 , 59 , 60 ) outweighing accessibility ( 23 ).…”

Section: Resultsmentioning

confidence: 99%

“…The less frequently found data item is findability. However, articles identified with this data item share a common recommendation emphasizing the use of standardized terminology to enhance the findability of its data ( 24 , 42 , 47 , 58 , 60 ). Despite these recommendations, there are still challenges to achieve full FAIR compliance for rare disease databases.…”

Section: Discussionmentioning

confidence: 99%

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Challenges in mapping European rare disease databases, relevant for ML-based screening technologies in terms of organizational, FAIR and legal principles: scoping review

Raycheva,

Kostadinov,

Mitova

et al. 2023

Front. Public Health

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BackgroundGiven the increased availability of data sources such as hospital information systems, electronic health records, and health-related registries, a novel approach is required to develop artificial intelligence-based decision support that can assist clinicians in their diagnostic decision-making and shorten rare disease patients’ diagnostic odyssey. The aim is to identify key challenges in the process of mapping European rare disease databases, relevant to ML-based screening technologies in terms of organizational, FAIR and legal principles.MethodsA scoping review was conducted based on the PRISMA-ScR checklist. The primary article search was conducted in three electronic databases (MEDLINE/Pubmed, Scopus, and Web of Science) and a secondary search was performed in Google scholar and on the organizations’ websites. Each step of this review was carried out independently by two researchers. A charting form for relevant study analysis was developed and used to categorize data and identify data items in three domains – organizational, FAIR and legal.ResultsAt the end of the screening process, 73 studies were eligible for review based on inclusion and exclusion criteria with more than 60% (n = 46) of the research published in the last 5 years and originated only from EU/EEA countries. Over the ten-year period (2013–2022), there is a clear cycling trend in the publications, with a peak of challenges reporting every four years. Within this trend, the following dynamic was identified: except for 2016, organizational challenges dominated the articles published up to 2018; legal challenges were the most frequently discussed topic from 2018 to 2022. The following distribution of the data items by domains was observed – (1) organizational (n = 36): data accessibility and sharing (20.2%); long-term sustainability (18.2%); governance, planning and design (17.2%); lack of harmonization and standardization (17.2%); quality of data collection (16.2%); and privacy risks and small sample size (11.1%); (2) FAIR (n = 15): findable (17.9%); accessible sustainability (25.0%); interoperable (39.3%); and reusable (17.9%); and (3) legal (n = 33): data protection by all means (34.4%); data management and ownership (22.9%); research under GDPR and member state law (20.8%); trust and transparency (13.5%); and digitalization of health (8.3%). We observed a specific pattern repeated in all domains during the process of data charting and data item identification – in addition to the outlined challenges, good practices, guidelines, and recommendations were also discussed. The proportion of publications addressing only good practices, guidelines, and recommendations for overcoming challenges when mapping RD databases in at least one domain was calculated to be 47.9% (n = 35).ConclusionDespite the opportunities provided by innovation – automation, electronic health records, hospital-based information systems, biobanks, rare disease registries and European Reference Networks – the results of the current scoping review demonstrate a diversity of the challenges that must still be addressed, with immediate actions on ensuring better governance of rare disease registries, implementing FAIR principles, and enhancing the EU legal framework.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Challenges in mapping European rare disease databases, relevant for ML-based screening technologies in terms of organizational, FAIR and legal principles: scoping review

Raycheva,

Kostadinov,

Mitova

et al. 2023

Front. Public Health

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“…Currently 24 networks for different rare and complex diseases or disease groups exist. One of these networks is the European Reference Network for Respiratory diseases (ERN-LUNG), which focuses on a number of rare lung diseases (RLD) affecting the lungs and airways [3,4].…”

Section: Introductionmentioning

confidence: 99%

“…One goal of the ERNs is to develop and provide registries and databases. Registries are core elements for epidemiologic, public health or clinical studies and collect information on individual patients [4]. Due to the small number of patients in RDs, it is even more necessary than in common diseases to collect and share patient data across the national level [5].…”

Section: Introductionmentioning

confidence: 99%

The ERN-LUNG Population Registry: Aims, Software-Implementation and First Results

Schaaf

Zieschank

Goebel

et al. 2022

Studies in Health Technology and Informatics

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The ERN-LUNG Population Registry is a new European-wide collection of patients with rare lung diseases, allowing patients to register online in the registry. Medical experts can recruit patients in the registry for disease-specific registries and care options. The Population Registry was implemented on the basis of the open source software OSSE and extended by functions for the self-registration of patients. Patients were invited through patient organizations between May and November 2022. 115 patients registered online in the registry, whereas 60 of them provided full data in the registry form. After first months of usage, further dissemination of the registry is necessary to reach more patients, e.g. by recruiting them via medical centres directly. Improvements of the registry should be conducted to achieve a higher number of fully completed forms.

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Methods Used in the Development of Common Data Models for Health Data: Scoping Review

Ahmadi¹,

Zoch²,

Kelbert³

et al. 2023

JMIR Med Inform

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Background Common data models (CDMs) are essential tools for data harmonization, which can lead to significant improvements in the health domain. CDMs unite data from disparate sources and ease collaborations across institutions, resulting in the generation of large standardized data repositories across different entities. An overview of existing CDMs and methods used to develop these data sets may assist in the development process of future models for the health domain, such as for decision support systems. Objective This scoping review investigates methods used in the development of CDMs for health data. We aim to provide a broad overview of approaches and guidelines that are used in the development of CDMs (ie, common data elements or common data sets) for different health domains on an international level. Methods This scoping review followed the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist. We conducted the literature search in prominent databases, namely, PubMed, Web of Science, Science Direct, and Scopus, starting from January 2000 until March 2022. We identified and screened 1309 articles. The included articles were evaluated based on the type of adopted method, which was used in the conception, users’ needs collection, implementation, and evaluation phases of CDMs, and whether stakeholders (such as medical experts, patients’ representatives, and IT staff) were involved during the process. Moreover, the models were grouped into iterative or linear types based on the imperativeness of the stages during development. Results We finally identified 59 articles that fit our eligibility criteria. Of these articles, 45 specifically focused on common medical conditions, 10 focused on rare medical conditions, and the remaining 4 focused on both conditions. The development process usually involved stakeholders but in different ways (eg, working group meetings, Delphi approaches, interviews, and questionnaires). Twenty-two models followed an iterative process. Conclusions The included articles showed the diversity of methods used to develop a CDM in different domains of health. We highlight the need for more specialized CDM development methods in the health domain and propose a suggestive development process that might ease the development of CDMs in the health domain in the future.

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The Registry Data Warehouse in the European Reference Network for Rare Respiratory Diseases – Background, Conception and Implementation

Cited by 4 publications

References 6 publications

Challenges in mapping European rare disease databases, relevant for ML-based screening technologies in terms of organizational, FAIR and legal principles: scoping review

Challenges in mapping European rare disease databases, relevant for ML-based screening technologies in terms of organizational, FAIR and legal principles: scoping review

The ERN-LUNG Population Registry: Aims, Software-Implementation and First Results

Methods Used in the Development of Common Data Models for Health Data: Scoping Review

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