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Data structuring of electronic health records: a systematic review

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Abstract

The medical field has experienced a series of transformations with the adoption of new technologies. One of the aspects that experienced significant changes is how a patient’s information is stored. Electronic health records have brought a series of advantages but still present many issues. One of them is the degree of structuring for contained information. More structuring brings a greater richness of information. On the other hand, it contains more challenging and complex content when most of the information is stored in free text (unstructured information). In this sense, many studies focused on structuring the information contained in free text have emerged. This work aims to review the studies focused on the structuring of unstructured health record information, seeking to answer key questions to propose new studies in the field on topics such as the form in which information is structured, the main techniques used, and how data acquisition for development and evaluation is done. To answer these questions, a wide systematic review of the field was conducted since the emergence of BERT networks. In addition to answering those questions, this systematic review identified the main challenges, such as difficulty in data acquisition, problems with natural language processing, and the specific challenges of the studies that process non-English languages, finalizing with a general view of the state of the art in the field and its future opportunities.

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Acknowledgements

The authors would like to thank the Coordination for the Improvement of Higher Education Personnel - CAPES (Financial Code 001), the National Council for Scientific and Technological Development - CNPq (Grant number 309537 / 2020-7) and the Instituto Federal de Educação, Ciência e Tecnologia do Rio Grande do Sul (IFRS) for their support in this work.

Funding

The article was partially funded by the Coordination for the Improvement of Higher Education Personnel - CAPES (Financial Code 001), the National Council for Scientific and Technological Development - CNPq (Grant number 309537 / 2020-7), and the Instituto Federal de Educação, Ciência e Tecnologia do Rio Grande do Sul (IFRS).

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  1. Instituto Federal de Educação, Ciência e Tecnologia do Rio Grande do Sul (IFRS), Rua Alberto Hoffmann, 285, RS 91791-508, Porto Alegre, Brazil

    Jezer Machado de Oliveira

  2. SOFTWARELAB, Applied Computing Graduate Program, Universidade do Vale do Rio dos Sinos - Unisinos, Av Unisinos 950, São Leopoldo, 93022-750, Brazil

    Jezer Machado de Oliveira, Cristiano André da Costa & Rodolfo Stoffel Antunes

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de Oliveira, J.M., da Costa, C.A. & Antunes, R.S. Data structuring of electronic health records: a systematic review. Health Technol. 11, 1219–1235 (2021). https://doi.org/10.1007/s12553-021-00607-w

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