Profiling Lung Cancer Patients Using Electronic Health Records

J Med Syst. 2018 May 31;42(7):126. doi: 10.1007/s10916-018-0975-9.

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.

Keywords: Electronic health records; Lung cancer; Natural language processing; Telemedicine.

MeSH terms

  • Data Mining
  • Electronic Health Records*
  • Female
  • Humans
  • Lung Neoplasms / diagnosis*
  • Lung Neoplasms / therapy
  • Male
  • Natural Language Processing*
  • Reproducibility of Results