Profiling lung cancer patients using electronic health records

TL;DR

This paper demonstrates the feasibility of extracting and analyzing relevant clinical data from electronic health records of lung cancer patients using NLP, aiming to enhance clinical decision-making and patient care.

Contribution

It introduces an NLP framework for extracting key patient information from clinical records and shows its application in analyzing lung cancer patient data from a hospital service.

Findings

Successful extraction of patient demographics and health data.

Integration of EHR analysis into clinical service is feasible.

Provides a foundation for further research in EHR-based clinical analysis.

Abstract

If Electronic Health Records contain a large amount of information about the patients 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.