An Archetype Query Language interpreter into MongoDB: Managing NoSQL standardized Electronic Health Record extracts systems

Ramos, Miguel; Sánchez-de-Madariaga, Ricardo; Barros, Jesús; Carrajo, Lino; Vázquez, Guillermo; Pérez, Santiago; Pascual, Mario; Martín-Sánchez, Fernando; Carrero, Adolfo Muñoz

doi:10.1016/j.jbi.2019.103339

Cited by 10 publications

(6 citation statements)

References 6 publications

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“…In this process, other technologies were analyzed, such as the Archetype Query Language (AQL) 42 for the extraction and selection of data based on the defined archetypes. 43 This technology was discarded at this point due to the complexity of its implementation in the current health care environment, being considered for deployment in future steps of this line of work. With this, the operations were developed according to a design agnostic to specific use cases, so that, they could be instantiated automatically, as a final part of the application of the methodology.…”

Section: Methodsmentioning

confidence: 99%

TransformEHRs: a flexible methodology for building transparent ETL processes for EHR reuse

et al. 2022

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Background During the COVID-19 pandemic, several methodologies were designed for obtaining electronic health record (EHR)-derived datasets for research. These processes are often based on black boxes, on which clinical researchers are unaware of how the data were recorded, extracted, and transformed. In order to solve this, it is essential that extract, transform, and load (ETL) processes are based on transparent, homogeneous, and formal methodologies, making them understandable, reproducible, and auditable. Objectives This study aims to design and implement a methodology, according with FAIR Principles, for building ETL processes (focused on data extraction, selection, and transformation) for EHR reuse in a transparent and flexible manner, applicable to any clinical condition and health care organization. Methods The proposed methodology comprises four stages: (1) analysis of secondary use models and identification of data operations, based on internationally used clinical repositories, case report forms, and aggregated datasets; (2) modeling and formalization of data operations, through the paradigm of the Detailed Clinical Models; (3) agnostic development of data operations, selecting SQL and R as programming languages; and (4) automation of the ETL instantiation, building a formal configuration file with XML. Results First, four international projects were analyzed to identify 17 operations, necessary to obtain datasets according to the specifications of these projects from the EHR. With this, each of the data operations was formalized, using the ISO 13606 reference model, specifying the valid data types as arguments, inputs and outputs, and their cardinality. Then, an agnostic catalog of data was developed through data-oriented programming languages previously selected. Finally, an automated ETL instantiation process was built from an ETL configuration file formally defined. Conclusions This study has provided a transparent and flexible solution to the difficulty of making the processes for obtaining EHR-derived data for secondary use understandable, auditable, and reproducible. Moreover, the abstraction carried out in this study means that any previous EHR reuse methodology can incorporate these results into them.

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Section: Methodsmentioning

confidence: 99%

TransformEHRs: a flexible methodology for building transparent ETL processes for EHR reuse

et al. 2022

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“…Finally, in terms of implemented resources, both OpenEHR [22,29,36,37] and HL7 FHIR [14,30,38,39] have solutions complete or in a limited way due to the above explained, for information model catalog, clinical decision support, query API and data messaging. In contrast, ISO 13606 does not offer implemented components beyond theoretical formalizations of information models and communication interfaces [40,41], although this has been compensated for by externally developed solutions [8,[42][43][44].…”

Section: Openehrmentioning

confidence: 99%

“…This is evident in the numerous implementations of EHR architectures that have incorporated this standard around the world [37]. Despite this, there are proposals for clinical repositories and exploitation mechanism based on ISO 13606 and FHIR that have proven useful [42,43,45], but one must be aware that this is a use for which these standards were not designed, assuming the limitations presented for such a purpose, and the additional external developments necessary for their suitability. On the other hand, the exchange of health data can be achieved through different proposals such as ISO 13606 and the HL7 FHIR standard, depending on the complexity, as well as the capacity of agreement between parties.…”

Section: Openehrmentioning

confidence: 99%

Can OpenEHR, ISO 13606 and HL7 FHIR work together? An agnostic perspective for the selection and application of EHR standards from Spain

Pedrera-Jiménez¹,

standards²,

Kalra³

et al. 2022

Preprint

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<p>Due to the heterogeneity of Electronic Health Record (EHR) standards, the decision-making teams, who are not experts in health information, express confusion for selecting and applying these resources in their data platforms. For this reason, a group of experts has analyzed strengths and weaknesses about design, modeling capabilities, flexibility and resources implemented of three relevant standards based on Detailed Clinical Models: OpenEHR, ISO 13606 and HL7 FHIR. Thus, it was concluded that: (1) they are useful for the purposes for which they have been designed and show shortcomings in those for which they have not; (2) they are functionally compatible in health data platforms and methodologies developed in a standards-agnostic perspective; and (3) they are conceptually and technically compatible with each other, so the choice of one or the other does not have a high impact as long as one starts from the one richer in modeling capabilities and flexibility.</p>

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“…Precision medicine knowledge is typically made of a large number of different categories of information, where the pieces of information in each category are not as abundant as compared to other domains of database applications. The structural complexity of the precision medicine knowledgebase built by RDBMS adds to the complexity when the relational structure of the database needs to be changed to reflect the addition of a new type of knowledge ( 12 , 13 ). An example is shown in a later section to illustrate this deficiency.…”

Section: Introductionmentioning

confidence: 99%

“…More recently, researchers have also tried non-RDBMS technologies for building precision medicine knowledgebases. Examples include semantic networks ( 12 ), distributed file systems ( 13 ) and graph databases ( 14 , 15 ). Semantic networks describe knowledge in the form of triplets, which have a limited expression power ( 16 ) and are difficult to use when modelling natural language-based precision medicine knowledge.…”

Section: Introductionmentioning

confidence: 99%

MMKP: A mind mapping knowledgebase prototyping tool for precision medicine

Liang

Li²,

Dong³

et al. 2022

Front. Immunol.

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BackgroundWith significant advancements in the area of precision medicine, the breadth and complexity of the relevant knowledge in the field has increased significantly. However, the difficulty associated with dynamic modelling and the disorganization of such knowledge hinders its rapid development potential.ResultsTo overcome the difficulty in using the relational database model for dynamic modelling, and to aid in the organization of precision medicine knowledge, we developed the Mind Mapping Knowledgebase Prototyping (MMKP) tool. The MMKP implements a novel design that we call a “polymorphic foreign key”, which allows the establishment of a logical linkage between a single table field and a record from any table. This design has advantages in supporting dynamic changes to the structural relationships in precision medicine knowledge. Knowledge stored in MMKP is presented as a mind map to facilitate human interaction. When using this tool, medical experts may curate the structure and content of the precision knowledge in a flow that is similar to the human thinking process.ConclusionsThe design of polymorphic foreign keys natively supports knowledge modelling in the form of mind mapping, which avoids the hard-coding of medical logic into a rigid database schema and significantly reduces the workload that is required for adapting a relational data model to future changes to the medical logic. The MMKP tool provides a graphical user interface for both data management and knowledgebase prototyping. It supports the flexible customization of the data field constraints and annotations. MMKP is available as open-source code on GitHub: https://github.com/ZjuLiangsl/mmkp.

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An Archetype Query Language interpreter into MongoDB: Managing NoSQL standardized Electronic Health Record extracts systems

Cited by 10 publications

References 6 publications

TransformEHRs: a flexible methodology for building transparent ETL processes for EHR reuse

TransformEHRs: a flexible methodology for building transparent ETL processes for EHR reuse

Can OpenEHR, ISO 13606 and HL7 FHIR work together? An agnostic perspective for the selection and application of EHR standards from Spain

MMKP: A mind mapping knowledgebase prototyping tool for precision medicine

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