Terminologia de Interface: processamento de linguagem natural de dados clínicos em narrativas do Prontuário Eletrônico do Paciente

Amanda Damasceno de Souza; Frederico Giffoni de Carvalho Dutra; Fábio Corrêa; Helton Júnio da Silva; Jurema Suely de Araújo Nery Ribeiro; Eduardo Ribeiro Felipe

doi:10.5007/1518-2924.2024.e94983

Authors

Amanda Damasceno de Souza Federal University of Minas Gerais https://orcid.org/0000-0001-6859-4333
Frederico Giffoni de Carvalho Dutra FUMEC University https://orcid.org/0000-0002-8666-0354
Fábio Corrêa FUMEC University https://orcid.org/0000-0002-2346-0187
Helton Júnio da Silva FUMEC University https://orcid.org/0000-0003-4200-298X
Jurema Suely de Araújo Nery Ribeiro FUMEC University https://orcid.org/0000-0002-6465-6020
Eduardo Ribeiro Felipe Technological Sciences Institute https://orcid.org/0000-0003-1690-2044

DOI:

https://doi.org/10.5007/1518-2924.2024.e94983

Keywords:

Registros Eletrônicos de Saúde, Dados de Saúde Gerados pelo Paciente, Recuperação da informação, Ginecologia, Processamento de linguagem Natural

Abstract

Objective: To present the retrieval and analysis of clinical data from anamneses in the. Electronic Health Record (EHR), referred to in this research as Interface Terminology.

Methods:The clinical data collection process in this research was carried out on electronic patient records from a private hospital. The data sample consisted of 18,256 anamneses from the field of gynecology in 2018. The clinical data was retrieved through Natural Language Processing using the Python language. The most frequent terms related to clinical data were analysed, such as abbreviations and acronyms, stop words, procedures, and n-grams.

Results: Clinical data has the potential to be reused for scientific production, epidemiological profiling and the creation of dictionaries and enrichment of controlled vocabularies for EHR and other health information systems. They are also important in defining algorithms for information retrieval. As a result, a repository was created in OSF containing spreadsheets and tables with clinical data for reuse in algorithm delimitation, word cloud creation and to identify the most frequent terms in electronic patient records in the field of Gynecology, while the algorithms used in information retrieval were made available in GitHub. The data has been published in the OSF: https://osf.io/de43a/.

Conclusions: Clinical data is information about the patient that is used for care purposes, hospital administrative issues, research related to the patient's health and illness. The Interface Terminology, exemplified in the research hospital's EHR, presented a diversity of clinical data in the anamneses.

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Author Biographies

Amanda Damasceno de Souza, Federal University of Minas Gerais

Professor of the Postgraduate Program in Information Systems and Knowledge Management (PPGSIGC) at FUMEC University. PhD in Knowledge Management and Organization from PPG-GOC of the Federal University of Minas Gerais (UFMG) (2021). Master in Information Science from the School of Information Science at the Federal University of Minas Gerais (ECI/UFMG) (2016). Specialist in Strategic Information Management from ECI/UFMG (2013). Graduated in Library Science from the Federal University of Minas Gerais (ECI/UFMG) (2005). She is a member of the Research Group Center for Studies and Research on Information Resources, Services and Praxis (NERSI). Member of the Knowledge Representation, Ontologies and Language (ReCOL) research group. Member of the ABNT CE 021:002.032 Committee. Member of the Research Ethics Committee of Hospital Felício Rocho (Since 2016). Deputy Coordinator of the Research Ethics Committee at Felício Rocho Hospital (since 2020). Participates as a Professor in the Specialization Course in Care Strategy in Nursing-CEECE/UFMG, in the areas of Nursing in Cardiology and Hemodynamics and Quality Management in Health and Nursing.

Frederico Giffoni de Carvalho Dutra, FUMEC University

Professor, researcher, PhD in Information and Knowledge Management from the Federal University of Minas Gerais (2020), Master in Information and Knowledge Management from the Federal University of Minas Gerais (2014), Specialist in Strategic Marketing Management (2007) and Graduated in Administration (2005). He works in the area of Communication, Marketing and Intelligence at Companhia Energética de Minas Gerais-CEMIG, focusing on intelligence and monitoring of customers and brands on social networks and teaches undergraduate and postgraduate courses.

Fábio Corrêa, FUMEC University

Post-Doctorate from the Information Science Program at the Federal University of Minas Gerais (UFMG). Doctor and Master in Information Systems and Knowledge Management. He has an MBA in Software Engineering and Information Technology Governance and a degree in Information Systems. Acting as Professor of the Computer Science Course and the Postgraduate Program in Information Systems and Knowledge Management at FUMEC University. Professional experience in consultancy and Research and Development Projects, as well as working for 15 years in the Information Technology market. He is currently a professor in the Undergraduate and Postgraduate Program in Information Systems and Knowledge Management at FUMEC University. He works in the area of Computer Science, with an emphasis on Information Systems, and Information Science, with an emphasis on Knowledge Management.

Helton Júnio da Silva, FUMEC University

Lawyer, Asset Manager, University Professor in the Postgraduate courses in Real Estate Law and Notarial and Registration Law at the Pontifical Catholic University of Minas Gerais, PhD student in Information System and Knowledge Management, Master in Private Law at the FUMEC University - Fundação Mineira de Education and Culture (2018), Postgraduate in Notarial and Registration Law from Faculdade Milton Campos (2016), Postgraduate in Business Legal Consulting from Centro Universitário UNISEB (2011), Postgraduate in Public Law from Universidade Cândido Mendes (2009), Graduated in Law from the Pontifical Catholic University of Minas Gerais (2008), Graduated in Pedagogy from the State University of Minas Gerais (2003). He worked as a Pedagogue and School Manager in Public Administration and in the private education sector. He is currently Asset Manager at ArcelorMittal Brasil working in the Real Estate processes of companies in the ArcelorMittal group in Brazil.

Jurema Suely de Araújo Nery Ribeiro, FUMEC University

PhD in Information Systems and Knowledge Management - FUMEC (2019). Master in Administration - Research area: Strategy and Competitiveness - from the Faculty of Administrative Studies of Minas Gerias - FEAD (2008); MBA in Logistics from the University Center for Management Sciences - UNA (2004); MBA in Finance from the University Center for Management Sciences - UNA (2004); MBA in Institutional Management from the Pitágoras Postgraduate Center (2011), Specialization in Production Administration from the Institute of Technological Education - IETEC (1997); Bachelor in Administration from Centro Universitário Newton Paiva (1991).

Eduardo Ribeiro Felipe, Technological Sciences Institute

Adjunct Professor at the Federal University of Itajubá, he has a PhD in Knowledge Management and Organization, Master in Information Science from UFMG. He holds a degree as a Data Processing Technologist from Centro Universitário Newton Paiva and a postgraduate degree in Software Engineering from PUC-Minas. He works in the areas of Programming Languages, Web Development, Information Retrieval and Ontologies.

References

BAUD, R.H.; et al. Reconciliation of ontology and terminology to cope with linguistics. Studies in Health Technology and Informatics, Amsterdam, v.129, Pt 1, p.796-801, 2007.

BIRD, S.; KLEIN, E.; LOPER, E. Natural Language Processing with Python: Analyzing Text with the Natural Language Toolkit. Sebastopol: O'Reilly Media, 2019. Disponível em: http://www.nltk.org/book/. Acesso em 15 fev 2021.

BLOBEL, B. Interoperable EHR Systems – Challenges, Standards and Solutions. European Journal for Biomedical Informatics, Praga, v.14, n,2, p.10-19, 2018.

BRASIL. Resolução CFM nº 2056 de 20 de setembro de 2013. Disciplina os departamentos de Fiscalização nos Conselhos Regionais de Medicina, estabelece critérios para a autorização de funcionamento dos serviços médicos de quaisquer naturezas, bem como estabelece critérios mínimos para seu funcionamento, vedando o funcionamento daqueles que não estejam de acordo com os mesmos. Trata também dos roteiros de anamnese a serem adotados em todo o Brasil, inclusive nos estabelecimentos de ensino médico, bem como os roteiros para perícias médicas e a organização do prontuário de pacientes assistidos em ambientes de trabalho dos médicos.Brasília, DF: Presidência da República, 2013. Disponível em : https://www.legisweb.com.br/legislacao/?id=261676. Acesso em 07 jan.2020.

CONSELHO FEDERAL DE MEDICINA. Código de Ética Médica. Resolução CFM nº 1.931, de 17 de setembro de 2009.Brasília: CFM, 2010. (versão de bolso). Disponível em : https://portal.cfm.org.br/images/stories/biblioteca/codigo%20de%20etica%20medica.pdf. Acesso 07 jan. 2020.

CONSELHO REGIONAL DE MEDICINA DO DISTRITO FEDERAL. Prontuário médico do paciente: guia para uso prático. Brasília: Conselho Regional de Medicina, 2006. Disponível em : http://www.crmdf.org.br/sistemas/biblioteca/files/7.pdf. Acesso 09 ago 2012.

DALIANIS, H. Characteristics of Patient Records and Clinical Corpora. In: DALIANIS, H. Clinical Text Mining: Secondary Use of Electronic Patient Records. [s.n.],2018. cap. 4 Disponível em:http://link.springer.com/10.1007/978-3-319-78503-5. Acesso em: 2 jan. 2019.

FARLEX PARTNER MEDICAL DICTIONARY. Anamnesis. 2012. Disponível em: https://medical-dictionary.thefreedictionary.com/anamnesis. Acesso em: 7 jan 2020.

GRÜNE, S. Anamnese und körperliche Untersuchung. Deutsche Medicinische Wochenschrift, Stuttgart, v.141, n.1, p.24-7. Jan. 2016.

LÓPEZ, M. Anamnese. In: LÓPEZ, M.; MEDEIROS, J.L. Semiologia Médica: as bases do diagnóstico clínico. 3.ed. Atheneu: Rio de Janeiro, 1990. Cap. 2, p. 20-34.

MANNING, C. D.; SCHÜTZE, H. Foundations of statistical natural language processing. Cambridge Massachusetts: MIT press, 1999. 620 p.

MOSLEY, M. (ed.). et al. The DAMA Guide to the Data Management Body of knowledge (DAMA- DMBOK Book). Bradley Beach, NJ: Technics Publications, 2009. 406p.

SCHULZ, S.; et al. Interface Terminologies, Reference Terminologies and Aggregation Terminologies: A Strategy for Better Integration. Studies in Health Technology and Informatics, Amsterdam, v. 245, p. 940-944. 2017.

SHORTLIFFE, E.H.; BARNETT, G.O. Biomedical Data: Their Acquisition, Storage, and Use. In: SHORTLIFFE, E.H.; CIMINO, J.J. (Editors). Biomedical Informatics: Computer Applications in Health Care and Biomedicine. 4th Ed. London: Springer-Verlag, 2014. Cap.2, p.46-79.

SOUZA, A. D. INTERFACE TERMINOLOGY: INTERFACE TERMINOLOGY: Natural language processing of clinical data in Electronic Health Record narratives. OSF [dataset], 2023. Disponível em: https://osf.io/de43a/.Acesso em 06 jun 2023.

SOUZA, A.D. O discurso na prática clínica e as terminologias de padronização: investigando a conexão. 2021. Tese (Doutorado em Gestão e Organização do Conhecimento). Pós-Graduação em Gestão e Organização do Conhecimento, Escola de Ciência da Informação, Universidade Federal de Minas Gerais, Belo Horizonte, 2021.Disponível em: http://hdl.handle.net/1843/38044. Acesso em 06 jun. 2023.

WANG Z, et al. Extracting diagnoses and investigation results from unstructured text in electronic health records by semi-supervised machine learning. PLoS One, San Francisco, v.7, n.1, p.e30412, 2012.