Application of Natural Language Processing in Electronic Health Record Data Extraction for Navigating Prostate Cancer Care: A Narrative Review

被引:4
作者
Bhatia, Ansh [1 ,2 ]
Titus, Renil [2 ]
Porto, Joao G. [1 ]
Katz, Jonathan [3 ]
Lopategui, Diana M. [1 ]
Marcovich, Robert [1 ]
Parekh, Dipen J. [1 ]
Shah, Hemendra N. [1 ]
机构
[1] Univ Miami, Desai Sethi Urol Inst, Miller Sch Med, Miami, FL USA
[2] Seth GS Med Coll & King Edward Mem Hosp, Mumbai, Maharashtra, India
[3] Univ Calif, Dept Urol, San Diego, CA USA
关键词
artificial intelligence; natural language processing; prostate cancer; cancer staging;
D O I
10.1089/end.2023.0690
中图分类号
R5 [内科学]; R69 [泌尿科学(泌尿生殖系疾病)];
学科分类号
1002 ; 100201 ;
摘要
Introduction: Natural language processing (NLP)-based data extraction from electronic health records (EHRs) holds significant potential to simplify clinical management and aid research. This review aims to evaluate the current landscape of NLP-based data extraction in prostate cancer (PCa) management. Materials and Methods: We conducted a literature search of PubMed and Google Scholar databases using the keywords: "Natural Language Processing," "Prostate Cancer," "data extraction," and "EHR" with variations of each. No language or time limits were imposed. All results were collected in a standardized manner, including country of origin, sample size, algorithm, objective of outcome, and model performance. The precision, recall, and the F1 score of studies were collected as a metric of model performance. Results: Of the 14 studies included in the review, 2 articles focused on documenting digital rectal examinations, 1 on identifying and quantifying pain secondary to PCa, 8 on extracting staging/grading information from clinical reports, with an emphasis on TNM-classification, risk stratification, and identifying metastasis, 2 articles focused on patient-centered post-treatment outcomes such as incontinence, erectile, and bowel dysfunction, and 1 on loneliness/social isolation following PCa diagnosis. All models showed moderate to high data annotation/extraction accuracy compared with the gold standard method of manual data extraction by chart review. Despite their potential, NLPs face challenges in handling ambiguous, institution-specific language and context nuances, leading to occasional inaccuracies in clinical data interpretation. Conclusion: NLP-based data extraction has effectively extracted various outcomes from PCa patients' EHRs. It holds the potential for automating outcome monitoring and data collection, resulting in time and labor savings.
引用
收藏
页码:852 / 864
页数:13
相关论文
共 44 条
[21]  
hipaajournal.com, HIPAA Journal
[22]   Five sources of bias in natural language processing [J].
Hovy, Dirk ;
Prabhumoye, Shrimai .
LANGUAGE AND LINGUISTICS COMPASS, 2021, 15 (08)
[23]   Natural language processing in urology: Automated extraction of clinical information from histopathology reports of uro-oncology procedures [J].
Huang, Honghong ;
Lim, Fiona Xin Yi ;
Gu, Gary Tianyu ;
Han, Matthew Jiangchou ;
Fang, Andrew Hao Sen ;
Chia, Elian Hui San ;
Bei, Eileen Yen Tze ;
Tham, Sarah Zhuling ;
Ho, Henry Sun Sien ;
Yuen, John Shyi Peng ;
Sun, Aixin ;
Lim, Jay Kheng Sit .
HELIYON, 2023, 9 (04)
[24]   Natural Language Processing-Enabled and Conventional Data Capture Methods for Input to Electronic Health Records: A Comparative Usability Study [J].
Kaufman, David R. ;
Sheehan, Barbara ;
Stetson, Peter ;
Bhatt, Ashish R. ;
Field, Adele I. ;
Patel, Chirag ;
Maisel, James Mark .
JMIR MEDICAL INFORMATICS, 2016, 4 (04) :21-37
[25]  
Khattak WA., 2023, Int J Appl Health Care Anal, V8, P17
[26]   Second Prize: A Natural Language Processing Program Effectively Extracts Key Pathologic Findings from Radical Prostatectomy Reports [J].
Kim, Brian J. ;
Merchant, Madhur ;
Zheng, Chengyi ;
Thomas, Anil A. ;
Contreras, Richard ;
Jacobsen, Steven J. ;
Chien, Gary W. .
JOURNAL OF ENDOUROLOGY, 2014, 28 (12) :1474-1478
[27]   Inconsistencies in Quality of Life Data Collection in Clinical Trials: A Potential Source of Bias? Interviews with Research Nurses and Trialists [J].
Kyte, Derek ;
Ives, Jonathan ;
Draper, Heather ;
Keeley, Thomas ;
Calvert, Melanie .
PLOS ONE, 2013, 8 (10)
[28]   Machine Learning Approaches for Extracting Stage from Pathology Reports in Prostate Cancer [J].
Lenain, Raphael ;
Seneviratne, Martin G. ;
Bozkurt, Selen ;
Blayney, Douglas W. ;
Brooks, James D. ;
Hernandez-Boussard, Tina .
MEDINFO 2019: HEALTH AND WELLBEING E-NETWORKS FOR ALL, 2019, 264 :1522-1523
[29]   The Impact of Chat Generative Pre-trained Transformer (ChatGPT) on Oncology: Application, Expectations, and Future Prospects [J].
Li, Yanxing ;
Gao, Wentao ;
Luan, Zhenhua ;
Zhou, Zhi ;
Li, Jianjun .
CUREUS JOURNAL OF MEDICAL SCIENCE, 2023, 15 (11)
[30]   Social isolation in adults with cancer: An evolutionary concept analysis [J].
Liang, Yanjing ;
Hao, Guihua ;
Wu, Mei ;
Hou, Lili .
FRONTIERS IN PSYCHOLOGY, 2022, 13