Applying Large Language Models to Assess Quality of Care: Monitoring ADHD Medication Side Effects.

IF 6.2 2区 医学 Q1 PEDIATRICS
Yair Bannett, Fatma Gunturkun, Malvika Pillai, Jessica E Herrmann, Ingrid Luo, Lynne C Huffman, Heidi M Feldman
{"title":"Applying Large Language Models to Assess Quality of Care: Monitoring ADHD Medication Side Effects.","authors":"Yair Bannett, Fatma Gunturkun, Malvika Pillai, Jessica E Herrmann, Ingrid Luo, Lynne C Huffman, Heidi M Feldman","doi":"10.1542/peds.2024-067223","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>To assess the accuracy of a large language model (LLM) in measuring clinician adherence to practice guidelines for monitoring side effects after prescribing medications for children with attention-deficit/hyperactivity disorder (ADHD).</p><p><strong>Methods: </strong>Retrospective population-based cohort study of electronic health records. Cohort included children aged 6 to 11 years with ADHD diagnosis and 2 or more ADHD medication encounters (stimulants or nonstimulants prescribed) between 2015 and 2022 in a community-based primary health care network (n = 1201). To identify documentation of side effects inquiry, we trained, tested, and deployed an open-source LLM (LLaMA) on all clinical notes from ADHD-related encounters (ADHD diagnosis or ADHD medication prescription), including in-clinic/telehealth and telephone encounters (n = 15 628 notes). Model performance was assessed using holdout and deployment test sets, compared with manual medical record review.</p><p><strong>Results: </strong>The LLaMA model accurately classified notes that contained side effects inquiry (sensitivity = 87.2, specificity = 86.3, area under curve = 0.93 on holdout test set). Analyses revealed no model bias in relation to patient sex or insurance. Mean age (SD) at first prescription was 8.8 (1.6) years; characteristics were mostly similar across patients with and without documented side effects inquiry. Rates of documented side effects inquiry were lower for telephone encounters than for in-clinic/telehealth encounters (51.9% vs 73.0%, P < .001). Side effects inquiry was documented in 61.4% of encounters after stimulant prescriptions and 48.5% of encounters after nonstimulant prescriptions (P = .041).</p><p><strong>Conclusions: </strong>Deploying an LLM on a variable set of clinical notes, including telephone notes, offered scalable measurement of quality of care and uncovered opportunities to improve psychopharmacological medication management in primary care.</p>","PeriodicalId":20028,"journal":{"name":"Pediatrics","volume":"155 1","pages":""},"PeriodicalIF":6.2000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Pediatrics","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1542/peds.2024-067223","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PEDIATRICS","Score":null,"Total":0}
引用次数: 0

Abstract

Objective: To assess the accuracy of a large language model (LLM) in measuring clinician adherence to practice guidelines for monitoring side effects after prescribing medications for children with attention-deficit/hyperactivity disorder (ADHD).

Methods: Retrospective population-based cohort study of electronic health records. Cohort included children aged 6 to 11 years with ADHD diagnosis and 2 or more ADHD medication encounters (stimulants or nonstimulants prescribed) between 2015 and 2022 in a community-based primary health care network (n = 1201). To identify documentation of side effects inquiry, we trained, tested, and deployed an open-source LLM (LLaMA) on all clinical notes from ADHD-related encounters (ADHD diagnosis or ADHD medication prescription), including in-clinic/telehealth and telephone encounters (n = 15 628 notes). Model performance was assessed using holdout and deployment test sets, compared with manual medical record review.

Results: The LLaMA model accurately classified notes that contained side effects inquiry (sensitivity = 87.2, specificity = 86.3, area under curve = 0.93 on holdout test set). Analyses revealed no model bias in relation to patient sex or insurance. Mean age (SD) at first prescription was 8.8 (1.6) years; characteristics were mostly similar across patients with and without documented side effects inquiry. Rates of documented side effects inquiry were lower for telephone encounters than for in-clinic/telehealth encounters (51.9% vs 73.0%, P < .001). Side effects inquiry was documented in 61.4% of encounters after stimulant prescriptions and 48.5% of encounters after nonstimulant prescriptions (P = .041).

Conclusions: Deploying an LLM on a variable set of clinical notes, including telephone notes, offered scalable measurement of quality of care and uncovered opportunities to improve psychopharmacological medication management in primary care.

应用大型语言模型评估护理质量:监测多动症药物副作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Pediatrics
Pediatrics 医学-小儿科
CiteScore
12.80
自引率
5.00%
发文量
791
审稿时长
2-3 weeks
期刊介绍: The Pediatrics® journal is the official flagship journal of the American Academy of Pediatrics (AAP). It is widely cited in the field of pediatric medicine and is recognized as the leading journal in the field. The journal publishes original research and evidence-based articles, which provide authoritative information to help readers stay up-to-date with the latest developments in pediatric medicine. The content is peer-reviewed and undergoes rigorous evaluation to ensure its quality and reliability. Pediatrics also serves as a valuable resource for conducting new research studies and supporting education and training activities in the field of pediatrics. It aims to enhance the quality of pediatric outpatient and inpatient care by disseminating valuable knowledge and insights. As of 2023, Pediatrics has an impressive Journal Impact Factor (IF) Score of 8.0. The IF is a measure of a journal's influence and importance in the scientific community, with higher scores indicating a greater impact. This score reflects the significance and reach of the research published in Pediatrics, further establishing its prominence in the field of pediatric medicine.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信