Use of Natural Language Processing to Identify Sexual and Reproductive Health Information in Clinical Text.

OBJECTIVES: This study aimed to enable clinical researchers without expertise in natural language processing (NLP) to extract and analyze information about sexual and reproductive health (SRH), or other sensitive health topics, from large sets of clinical notes. METHODS: (1) We retrieved text from the electronic health record as individual notes. (2) We segmented notes into sentences using one of scispaCy's NLP toolkits. (3) We exported sentences to the labeling application Watchful and annotated subsets of these as relevant or irrelevant to various SRH categories by applying a combination of regular expressions and manual annotation. (4) The labeled sentences served as training data to create machine learning models for classifying text; specifically, we used spaCy's default text classification ensemble, comprising a bag-of-words model and a neural network with attention. (5) We applied each model to unlabeled sentences to identify additional references to SRH with novel relevant vocabulary. We used this information and repeated steps 3 to 5 iteratively until the models identified no new relevant sentences for each topic. Finally, we aggregated the labeled data for analysis. RESULTS: This methodology was applied to 3,663 Child Neurology notes for 971 female patients. Our search focused on six SRH categories. We validated the approach using two subject matter experts, who independently labeled a sample of 400 sentences. Cohen's kappa values were calculated for each category between the reviewers (menstruation: 1, sexual activity: 0.9499, contraception: 0.9887, folic acid: 1, teratogens: 0.8864, pregnancy: 0.9499). After removing the sentences on which reviewers did not agree, we compared the reviewers' labels to those produced via our methodology, again using Cohen's kappa (menstruation: 1, sexual activity: 1, contraception: 0.9885, folic acid: 1, teratogens: 0.9841, pregnancy: 0.9871). CONCLUSION: Our methodology is reproducible, enables analysis of large amounts of text, and has produced results that are highly comparable to subject matter expert manual review.

A retrospective textual analysis of sexual and reproductive health counseling for adolescent and young adult people with epilepsy of gestational capacity.

Rationale The American Academy of Neurology (AAN) recommends annual sexual and reproductive health (SRH) counseling for all people with epilepsy of gestational capacity (PWEGC). Child neurologists report discussing SRH concerns infrequently with adolescents. Limited research exists regarding documentation of such counseling. METHODS: We retrospectively studied clinical notes using natural language processing to investigate child neurologists' documentation of SRH counseling for adolescent and young adult PWEGC. We segmented notes into sentences and evaluated for references to menstruation, sexual activity, contraception, folic acid, teratogens, and pregnancy. We developed training sets in a labeling application and used machine learning to identify additional counseling instances. We repeated this iteratively until we identified no new relevant sentences. We validated results using external reviewers; after removing sentences reviewers disagreed on (n = 13/400), we calculated Cohen's kappa values between the model and reviewers (>0.98 for all categories). We evaluated labeled texts for each patient per calendar year with descriptive statistics and logistic regression, adjusting for race/ethnicity, age, and teratogen use. RESULTS: Data comprised 971 PWEGC age 13-21 years with 2277 patient-years and 3663 outpatient child neurology notes. Nearly half of patient-years lacked SRH counseling documentation (49.1%). Among all patients, 38.0% never had SRH counseling documented. Documentation was present regarding menstruation in 26.7% of patient-years, folic acid in 25.0%, contraception in 21.9%, pregnancy in 3.5%, teratogens in 3.0%, and sexual activity in 1.8%. Documentation regarding menstruation and contraception was associated with prescription of antiseizure medications that have a higher risk of teratogenic effects (OR = 1.27, p = 0.020, 95% CI = [1.04,1.54]; OR = 1.27, p = 0.027, 95% CI = [1.03,1.58]). Documentation regarding contraception, folic acid, and sexual activity was increased among older patients (OR = 1.28, p < 0.001, 95% CI = [1.21,1.35]; OR = 1.26, p < 0.001, 95% CI = [1.19,1.32]; OR = 1.26, p = 0.004, 95% CI = [1.08,1.47]). Documentation regarding sexual activity was decreased among patients identifying as White/Non-Hispanic (OR = 0.39, p = 0.007, 95% CI = [0.20,0.78]). CONCLUSION: Child neurologists counsel PWEGC on SRH less frequently than recommended by the AAN based on documentation.