Abstract
If Electronic Health Records contain a large amount of information about the patient’s condition and response to treatment, which can potentially revolutionize the clinical practice, such information is seldom considered due to the complexity of its extraction and analysis. We here report on a first integration of an NLP framework for the analysis of clinical records of lung cancer patients making use of a telephone assistance service of a major Spanish hospital. We specifically show how some relevant data, about patient demographics and health condition, can be extracted; and how some relevant analyses can be performed, aimed at improving the usefulness of the service. We thus demonstrate that the use of EHR texts, and their integration inside a data analysis framework, is technically feasible and worth of further study.
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This paper is supported by European Union’s Horizon 2020 research and innovation programme under grant agreement No. 727658, project IASIS (Integration and analysis of heterogeneous big data for precision medicine and suggested treatments for different types of patients).
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This article is part of the Topical Collection on Patient Facing Systems
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Menasalvas Ruiz, E., Tuñas, J.M., Bermejo, G. et al. Profiling Lung Cancer Patients Using Electronic Health Records. J Med Syst 42, 126 (2018). https://doi.org/10.1007/s10916-018-0975-9
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DOI: https://doi.org/10.1007/s10916-018-0975-9