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Design and Implementation of a Collaborative Clinical Practice and Research Documentation System Using SNOMED-CT and HL7-CDA in the Context of a Pediatric Neurodevelopmental Unit

2023Journal article Open access
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dc.contributor.authorDireito, B
dc.contributor.authorSantos, A
dc.contributor.authorMouga, S
dc.contributor.authorLima, J
dc.contributor.authorBrás, P
dc.contributor.authorOliveira, G
dc.contributor.authorCastelo-Branco, M
dc.date.accessioned2023-04-04T10:17:12Z
dc.date.available2023-04-04T10:17:12Z
dc.date.issued2023
dc.description.abstractThis paper introduces a prototype for clinical research documentation using the structured information model HL7 CDA and clinical terminology (SNOMED CT). The proposed solution was integrated with the current electronic health record system (EHR-S) and aimed to implement interoperability and structure information, and to create a collaborative platform between clinical and research teams. The framework also aims to overcome the limitations imposed by classical documentation strategies in real-time healthcare encounters that may require fast access to complex information. The solution was developed in the pediatric hospital (HP) of the University Hospital Center of Coimbra (CHUC), a national reference for neurodevelopmental disorders, particularly for autism spectrum disorder (ASD), which is very demanding in terms of longitudinal and cross-sectional data throughput. The platform uses a three-layer approach to reduce components’ dependencies and facilitate maintenance, scalability, and security. The system was validated in a real-life context of the neurodevelopmental and autism unit (UNDA) in the HP and assessed based on the functionalities model of EHR-S (EHR-S FM) regarding their successful implementation and comparison with state-of-the-art alternative platforms. A global approach to the clinical history of neurodevelopmental disorders was worked out, providing transparent healthcare data coding and structuring while preserving information quality. Thus, the platform enabled the development of user-defined structured templates and the creation of structured documents with standardized clinical terminology that can be used in many healthcare contexts. Moreover, storing structured data associated with healthcare encounters supports a longitudinal view of the patient’s healthcare data and health status over time, which is critical in routine and pediatric research contexts. Additionally, it enables queries on population statistics that are key to supporting the definition of local and global policies, whose importance was recently emphasized by the COVID pandemic.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationHealthcare. 2023;11: 973pt_PT
dc.identifier.doi10.3390/healthcare11070973pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.4/2338
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.subjectRegistos Electrónicos de Saúdept_PT
dc.subjectPerturbações do Espectro Autismopt_PT
dc.subjectNotificação de Doençaspt_PT
dc.subjectNomenclatura Médica Sistematizadapt_PT
dc.titleDesign and Implementation of a Collaborative Clinical Practice and Research Documentation System Using SNOMED-CT and HL7-CDA in the Context of a Pediatric Neurodevelopmental Unitpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.issue7pt_PT
oaire.citation.startPage973pt_PT
oaire.citation.titleHealthcarept_PT
oaire.citation.volume11pt_PT
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT

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