Exploring the full potential of the electronic health record: the application of natural language processing for clinical practice

Van Bulck, Liesbet; Reading Turchioe, Meghan; Topaz, Maxim; Song, Jiyoun

doi:10.1093/eurjcn/zvae091

European Journal of Cardiovascular Nursing

2024

DOI: 10.1093/eurjcn/zvae091

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Exploring the full potential of the electronic health record: the application of natural language processing for clinical practice

Liesbet Van Bulck,

Meghan Reading Turchioe,

Maxim Topaz

et al.

Abstract: The electronic health record (EHR) contains valuable patient data and offers opportunities to administer and analyse patients’ individual needs longitudinally. However, most information in the EHR is currently stored in unstructured text notations. Natural language processing (NLP), a branch of artificial intelligence that enables computers to understand, interpret, and generate human language, can be used to delve into unstructured text data to uncover valuable insights and knowledge. This article discusses d… Show more

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2024

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Cited by 2 publications

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Understanding Daily Care Experience Preferences Across the Lifespan of Older Adults: Application of Natural Language Processing

Min,

Woo,

Song

et al. 2024

West J Nurs Res

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Introduction: Older adults are a heterogeneous group, and their care experience preferences are likely to be diverse and individualized. Thus, the aim of this study was to identify categories of older adults’ care experience preferences and to examine similarities and differences across different age groups. Methods: The initial categories of older adults’ care experience preferences were identified through a qualitative review of narrative text (n = 3134) in the ADVault data set. A natural language processing (NLP) algorithm was used to automatically and accurately define older adults’ care experience preference categories. Descriptive statistics were used to examine similarities and differences in care experience preference categories across different age groups. Results: The overall average performance of NLP algorithms was relatively high (average F-score = 0.88; range: 0.77-0.96). Through a qualitative review of 350 randomly selected texts, a total of 11 categories were identified. The most frequent category was music, followed by photographs, entertainment, family/friends, religion-related, atmosphere, flower/plants, pet, bed/bedding, hobby, and other. After applying the best performing NLP algorithm to each category, older adults’ care experience preference categories were music (41.32%), followed by photographs (28.47%), entertainment (13.46%), religion-related (n = 12.69%), pet (12.22%), flower/plants (11.51%), family/friends (8.45%), atmosphere (7.75%), bed/bedding (6.12%), and hobby (5.45%). Young-old and old-old adults had similar care experience preferences with music being the most frequent category while old-old adults had photographs as the most frequent category for their care experience preference. Conclusion: Clinicians must understand the distinct categories of care experience preferences and incorporate them into personalized care planning.

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Understanding Daily Care Experience Preferences Across the Lifespan of Older Adults: Application of Natural Language Processing

Min,

Woo,

Song

et al. 2024

West J Nurs Res

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Exploring Natural Language Processing through an Exemplar Using YouTube

Chung,

Song,

Son

2024

IJERPH

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There has been a growing emphasis on data across various health-related fields, not just in nursing research, due to the increasing volume of unstructured data in electronic health records (EHRs). Natural Language Processing (NLP) provides a solution by transforming this unstructured data into structured formats, thereby facilitating valuable insights. This methodology paper explores the application of NLP in nursing, using an exemplar case study that analyzes YouTube data to investigate social phenomena among adults living alone. The methodology involves five steps: accessing data through YouTube’s API, data cleaning, preprocessing (tokenization, sentence segmentation, linguistic normalization), sentiment analysis using Python, and topic modeling. This study serves as a comprehensive guide for integrating NLP into nursing research, supplemented with digital content demonstrating each step. For successful implementation, nursing researchers must grasp the fundamental concepts and processes of NLP. The potential of NLP in nursing is significant, particularly in utilizing unstructured textual data from nursing documentation and social media. Its benefits include streamlining nursing documentation, enhancing patient communication, and improving data analysis.

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Exploring the full potential of the electronic health record: the application of natural language processing for clinical practice

Cited by 2 publications

References 19 publications

Understanding Daily Care Experience Preferences Across the Lifespan of Older Adults: Application of Natural Language Processing

Understanding Daily Care Experience Preferences Across the Lifespan of Older Adults: Application of Natural Language Processing

Exploring Natural Language Processing through an Exemplar Using YouTube

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