What can millions of laboratory test results tell us about the temporal aspect of data quality? Study of data spanning 17 years in a clinical data warehouse

Looten, Vincent; Chang, Liliane Kong Win; Neuraz, Antoine; Landau-Loriot, Marie-Anne; Védie, Benoît; Paul, Jean–Louis; Mauge, Laëtitia; Rivet, Nadia; Bonifati, Angela; Châtellier, Gilles; Burgun, Anita; Rance, Bastien

doi:10.1016/j.cmpb.2018.12.030

Cited by 13 publications

(7 citation statements)

References 30 publications

(32 reference statements)

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“…However, it is the backbone of all research done within a CDW. In order to improve the quality of the data with respect to research uses, it is necessary to conduct continuous studies dedicated to this topic [52,[54][55][56]. These studies should contribute to a reflection on methodologies and standard tools for data quality, such as those developed by the OHDSI research network [41].…”

Section: Data Quality and Documentationmentioning

confidence: 99%

Good practices for clinical data warehouse implementation: A case study in France

et al. 2023

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Real-world data (RWD) bears great promises to improve the quality of care. However, specific infrastructures and methodologies are required to derive robust knowledge and brings innovations to the patient. Drawing upon the national case study of the 32 French regional and university hospitals governance, we highlight key aspects of modern clinical data warehouses (CDWs): governance, transparency, types of data, data reuse, technical tools, documentation, and data quality control processes. Semi-structured interviews as well as a review of reported studies on French CDWs were conducted in a semi-structured manner from March to November 2022. Out of 32 regional and university hospitals in France, 14 have a CDW in production, 5 are experimenting, 5 have a prospective CDW project, 8 did not have any CDW project at the time of writing. The implementation of CDW in France dates from 2011 and accelerated in the late 2020. From this case study, we draw some general guidelines for CDWs. The actual orientation of CDWs towards research requires efforts in governance stabilization, standardization of data schema, and development in data quality and data documentation. Particular attention must be paid to the sustainability of the warehouse teams and to the multilevel governance. The transparency of the studies and the tools of transformation of the data must improve to allow successful multicentric data reuses as well as innovations in routine care.

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Section: Data Quality and Documentationmentioning

confidence: 99%

Good practices for clinical data warehouse implementation: A case study in France

et al. 2023

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“…In conclusion, conducting health studies using electronic health records requires careful attention to ensure accurate results owing to a lack of a systematic quality process. The data quality control procedure is a long and necessary process [ 17 38 39 ]. The future challenge will be the setting up of standardized and shared quality control pipelines to ensure quality results, not only at the local level but also in a regional and national context of future data sharing.…”

Section: Discussionmentioning

confidence: 99%

Implementing a Biomedical Data Warehouse From Blueprint to Bedside in a Regional French University Hospital Setting: Unveiling Processes, Overcoming Challenges, and Extracting Clinical Insight

Karakachoff,

Goronflot,

Coudol

et al. 2024

JMIR Med Inform

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Background Biomedical data warehouses (BDWs) have become an essential tool to facilitate the reuse of health data for both research and decisional applications. Beyond technical issues, the implementation of BDWs requires strong institutional data governance and operational knowledge of the European and national legal framework for the management of research data access and use. Objective In this paper, we describe the compound process of implementation and the contents of a regional university hospital BDW. Methods We present the actions and challenges regarding organizational changes, technical architecture, and shared governance that took place to develop the Nantes BDW. We describe the process to access clinical contents, give details about patient data protection, and use examples to illustrate merging clinical insights. Implementation (Results) More than 68 million textual documents and 543 million pieces of coded information concerning approximately 1.5 million patients admitted to CHUN between 2002 and 2022 can be queried and transformed to be made available to investigators. Since its creation in 2018, 269 projects have benefited from the Nantes BDW. Access to data is organized according to data use and regulatory requirements. Conclusions Data use is entirely determined by the scientific question posed. It is the vector of legitimacy of data access for secondary use. Enabling access to a BDW is a game changer for research and all operational situations in need of data. Finally, data governance must prevail over technical issues in institution data strategy vis-à-vis care professionals and patients alike.

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“…Looten et al , 10 leveraged the European Hospital Georges Pompidou CDW and tracked the evolution of 192 biological parameters over 17 years (445,000+ patients, 131 million laboratory test results). The authors developed computational and statistical methods to identify different evolution profiles and formulated recommendations to enable safe use and sharing of biological data collection to limit the impact of data evolution in retrospective and federated studies.…”

Section: Discussionmentioning

confidence: 99%

Clinical Research Informatics: Contributions from 2018

Daniel

2019

Yearb Med Inform

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Objectives: To summarize key contributions to current research in the field of Clinical Research Informatics (CRI) and to select best papers published in 2018. Method: A bibliographic search using a combination of MeSH descriptors and free-text terms on CRI was performed using PubMed, followed by a double-blind review in order to select a list of candidate best papers to be then peer-reviewed by external reviewers. After peer-review ranking, a consensus meeting of the editorial team was organized to conclude on the selection of best papers. Results: Among the 1,469 retrieved papers published in 2018 in the various areas of CRI, the full review process selected four best papers. The first best paper describes a simple algorithm detecting co-morbidities in Electronic Healthcare Records (EHRs) using a clinical data warehouse and a knowledge base. The authors of the second best paper present a federated algorithm for predicting heart failure hospital admissions based on patients' medical history described in their distributed EHRs. The third best paper reports the evaluation of an open source, interoperable, and scalable data quality assessment tool measuring completeness of data items, which can be run on different architectures (EHRs and Clinical Data Warehouses (CDWs) based on PCORnet or OMOP data models). The fourth best paper reports a data quality program conducted across 37 hospitals addressing data quality Issues through the whole data life cycle from patient to researcher. Conclusions: Research efforts in the CRI field currently focus on consolidating promises of early Distributed Research Networks aimed at maximizing the potential of large-scale, harmonized data from diverse, quickly developing digital sources. Data quality assessment methods and tools as well as privacy-enhancing techniques are major concerns. It is also notable that, following examples in the US and Asia, ambitious regional or national plans in Europe are launched that aim at developing big data and new artificial intelligence technologies to contribute to the understanding of health and diseases in whole populations and whole health systems, and returning actionable feedback loops to improve existing models of research and care. The use of “real-world" data is continuously increasing but the ultimate role of this data in clinical research remains to be determined.

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What can millions of laboratory test results tell us about the temporal aspect of data quality? Study of data spanning 17 years in a clinical data warehouse

Cited by 13 publications

References 30 publications

Good practices for clinical data warehouse implementation: A case study in France

Good practices for clinical data warehouse implementation: A case study in France

Implementing a Biomedical Data Warehouse From Blueprint to Bedside in a Regional French University Hospital Setting: Unveiling Processes, Overcoming Challenges, and Extracting Clinical Insight

Clinical Research Informatics: Contributions from 2018

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