AMIA ... Annual Symposium proceedings. AMIA Symposium最新文献_第10页

Designing Support to help Health Communication Professionals Convey Numbers Clearly to the Public - A Needs Assessment and Formative Usability Evaluation. 设计辅助工具，帮助健康传播专业人员向公众清晰传达数字--需求评估和形成性可用性评价。

AMIA ... Annual Symposium proceedings. AMIA Symposium Pub Date : 2024-01-11 eCollection Date: 2023-01-01

Uday Suresh, Jessica S Ancker, Brian J Zikmund-Fisher, Natalie C Benda

{"title":"Designing Support to help Health Communication Professionals Convey Numbers Clearly to the Public - A Needs Assessment and Formative Usability Evaluation.","authors":"Uday Suresh, Jessica S Ancker, Brian J Zikmund-Fisher, Natalie C Benda","doi":"","DOIUrl":"","url":null,"abstract":"Communicating health-related probabilities to patients and the public presents challenges, although multiple studies have demonstrated that we can promote comprehension and appropriate application of numbers by matching presentation formats (e.g., percentage, bar charts, icon arrays) to communication goal (e.g., improving recall, decreasing worry, taking action). We used this literature to create goal-driven, evidence-based guidance to support health communicators in conveying probabilities. We then conducted semi-structured interviews with 39 health communicators to understand: communicators' goals for expressing probabilities, formats they choose to convey probabilities, and perceptions of prototypes of our \"communicating numbers clearly\" guidance. We found that communicators struggled to articulate granular goals for their communication, impeding their ability to select appropriate guidance. Future work should consider how best to support health communicators in selecting granular, differentiable goals to support broadly comprehensible information design.","PeriodicalId":72180,"journal":{"name":"AMIA ... Annual Symposium proceedings. AMIA Symposium","volume":"2023 ","pages":"1277-1286"},"PeriodicalIF":0.0,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10785911/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139467434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Framework for Research in Equitable Synthetic Control Arms. 公平合成控制武器研究框架》。

AMIA ... Annual Symposium proceedings. AMIA Symposium Pub Date : 2024-01-11 eCollection Date: 2023-01-01

Naffs Neehal, Vibha Anand, Kristin P Bennett

引用次数: 0

Real-world Application of Racial and Ethnic Imputation and Cohort Balancing Techniques to Deliver Equitable Clinical Trial Recruitment. 在现实世界中应用种族和民族推算及队列平衡技术，实现公平的临床试验招募。

AMIA ... Annual Symposium proceedings. AMIA Symposium Pub Date : 2024-01-11 eCollection Date: 2023-01-01

Kelly J Craig, Yanrong Jerry Ji, Yuxin Chloe Zhang, Alexandra Berk, Amanda Zaleski, Omar Abdelsamad, Henriette Coetzer, Dorothea J Verbrugge, Guangying Hua

{"title":"Real-world Application of Racial and Ethnic Imputation and Cohort Balancing Techniques to Deliver Equitable Clinical Trial Recruitment.","authors":"Kelly J Craig, Yanrong Jerry Ji, Yuxin Chloe Zhang, Alexandra Berk, Amanda Zaleski, Omar Abdelsamad, Henriette Coetzer, Dorothea J Verbrugge, Guangying Hua","doi":"","DOIUrl":"","url":null,"abstract":"Enhancing diversity and inclusion in clinical trial recruitment, especially for historically marginalized populations including Black, Indigenous, and People of Color individuals, is essential. This practice ensures that generalizable trial results are achieved to deliver safe, effective, and equitable health and healthcare. However, recruitment is limited by two inextricably linked barriers - the inability to recruit and retain enough trial participants, and the lack of diversity amongst trial populations whereby racial and ethnic groups are underrepresented when compared to national composition. To overcome these barriers, this study describes and evaluates a framework that combines 1) probabilistic and machine learning models to accurately impute missing race and ethnicity fields in real-world data including medical and pharmacy claims for the identification of eligible trial participants, 2) randomized controlled trial experimentation to deliver an optimal patient outreach strategy, and 3) stratified sampling techniques to effectively balance cohorts to continuously improve engagement and recruitment metrics.","PeriodicalId":72180,"journal":{"name":"AMIA ... Annual Symposium proceedings. AMIA Symposium","volume":"2023 ","pages":"319-328"},"PeriodicalIF":0.0,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10785904/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139467598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Use of Health Belief Model-based Deep Learning to Understand Public Health Beliefs in Breast Cancer Screening from Social Media before and during the COVID-19 Pandemic. 利用基于健康信念模型的深度学习，从 COVID-19 大流行之前和期间的社交媒体中了解公众对乳腺癌筛查的健康信念。

AMIA ... Annual Symposium proceedings. AMIA Symposium Pub Date : 2024-01-11 eCollection Date: 2023-01-01

Michelle Bak, Chieh-Li Chin, Jessie Chin

引用次数: 0

Creating Conversion Factors from EHR Event Log Data: A Comparison of Investigator-Derived and Vendor-Derived Metrics for Primary Care Physicians. 从电子病历事件日志数据中创建换算系数：初级保健医生的研究人员得出的指标与供应商得出的指标之比较》（A Comparison of Investigator-Derived Metrics and Vendor-Derived Metrics for Primary Care Physicians）。

AMIA ... Annual Symposium proceedings. AMIA Symposium Pub Date : 2024-01-11 eCollection Date: 2023-01-01

Honor S Magon, Daniel Helkey, Tait Shanafelt, Daniel Tawfik

{"title":"Creating Conversion Factors from EHR Event Log Data: A Comparison of Investigator-Derived and Vendor-Derived Metrics for Primary Care Physicians.","authors":"Honor S Magon, Daniel Helkey, Tait Shanafelt, Daniel Tawfik","doi":"","DOIUrl":"","url":null,"abstract":"Physicians spend a large amount of time with the electronic health record (EHR), which the majority believe contributes to their burnout. However, there are limitedstandardized measures of physician EHR time. Vendor-derived metrics are standardized but may underestimate real-world EHR experience. Investigator-derived metrics may be more reliable but not standardized, particularly with regard to timeout thresholds defining inactivity. This study aimed to enable standardized investigator-derived metrics using conversion factors between raw event log-derived metrics and Signal (Epic System's standardized metric) for primary care physicians. This was an observational, retrospective longitudinal study of EHR raw event logs and Signal data from a quaternary academic medical center and its community affiliates in California, over a 6-month period. The study evaluated 242 physicians over 1370 physician-months, comparing 53.7 million event logs to 6850 Signal metrics, in five different time based metrics. Results show that inactivity thresholds for event log metric derivation that most closely approximate Signal metrics ranged from 90 seconds (Visit Navigator) to 360 seconds (\"Pajama time\") depending on the metric. Based on this data, conversion factors for investigator-derived metrics across a wide range of inactivity thresholds, via comparison with Signal metrics, are provided which may allow researchers to consistently quantify EHR experience.","PeriodicalId":72180,"journal":{"name":"AMIA ... Annual Symposium proceedings. AMIA Symposium","volume":"2023 ","pages":"1115-1124"},"PeriodicalIF":0.0,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10785859/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139467424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Exercise Exertion Level Prediction Using Data from Wearable Physiologic Monitors. 利用可穿戴生理监测器的数据预测运动消耗水平

AMIA ... Annual Symposium proceedings. AMIA Symposium Pub Date : 2024-01-11 eCollection Date: 2023-01-01

Aref Smiley, Te-Yi Tsai, Aileen Gabriel, Ihor Havrylchuk, Elena Zakashansky, Taulant Xhakli, Xingyue Huo, Wanting Cui, Fatemeh Shah-Mohammadi, Joseph Finkelstein

{"title":"Exercise Exertion Level Prediction Using Data from Wearable Physiologic Monitors.","authors":"Aref Smiley, Te-Yi Tsai, Aileen Gabriel, Ihor Havrylchuk, Elena Zakashansky, Taulant Xhakli, Xingyue Huo, Wanting Cui, Fatemeh Shah-Mohammadi, Joseph Finkelstein","doi":"","DOIUrl":"","url":null,"abstract":"This study aims to develop machine learning (ML) algorithms to predict exercise exertion levels using physiological parameters collected from wearable devices. Real-time ECG, oxygen saturation, pulse rate, and revolutions per minute (RPM) data were collected at three intensity levels during a 16-minute cycling exercise. Parallel to this, throughout each exercise session, the study subjects' ratings of perceived exertion (RPE) were gathered once per minute. Each 16-minute exercise session was divided into a total of eight 2-minute windows. Each exercise window was labeled as \"high exertion,\" or \"low exertion\" classes based on the self-reported RPEs. For each window, the gathered ECG data were used to derive the heart rate variability (HRV) features in the temporal and frequency domains. Additionally, each window's averaged RPMs, heart rate, and oxygen saturation levels were calculated to form all the predictive features. The minimum redundancy maximum relevance algorithm was used to choose the best predictive features. Top selected features were then used to assess the accuracy of ten ML classifiers to predict the next window's exertion level. The k-nearest neighbors (KNN) model showed the highest accuracy of 85.7% and the highest F1 score of 83%. An ensemble model showed the highest area under the curve (AUC) of 0.92. The suggested method can be used to automatically track perceived exercise exertion in real-time.","PeriodicalId":72180,"journal":{"name":"AMIA ... Annual Symposium proceedings. AMIA Symposium","volume":"2023 ","pages":"653-662"},"PeriodicalIF":0.0,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10785938/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139467471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Annotation and Information Extraction of Consumer-Friendly Health Articles for Enhancing Laboratory Test Reporting. 对方便消费者的健康文章进行注释和信息提取，以改进实验室检验报告。

AMIA ... Annual Symposium proceedings. AMIA Symposium Pub Date : 2024-01-11 eCollection Date: 2023-01-01

Zhe He, Shubo Tian, Arslan Erdengasileng, Karim Hanna, Yang Gong, Zhan Zhang, Xiao Luo, Mia Liza A Lustria

{"title":"Annotation and Information Extraction of Consumer-Friendly Health Articles for Enhancing Laboratory Test Reporting.","authors":"Zhe He, Shubo Tian, Arslan Erdengasileng, Karim Hanna, Yang Gong, Zhan Zhang, Xiao Luo, Mia Liza A Lustria","doi":"","DOIUrl":"","url":null,"abstract":"Viewing laboratory test results is patients' most frequent activity when accessing patient portals, but lab results can be very confusing for patients. Previous research has explored various ways to present lab results, but few have attempted to provide tailored information support based on individual patient's medical context. In this study, we collected and annotated interpretations of textual lab result in 251 health articles about laboratory tests from AHealthyMe.com. Then we evaluated transformer-based language models including BioBERT, ClinicalBERT, RoBERTa, and PubMedBERT for recognizing key terms and their types. Using BioPortal's term search API, we mapped the annotated terms to concepts in major controlled terminologies. Results showed that PubMedBERT achieved the best F1 on both strict and lenient matching criteria. SNOMED CT had the best coverage of the terms, followed by LOINC and ICD-10-CM. This work lays the foundation for enhancing the presentation of lab results in patient portals by providing patients with contextualized interpretations of their lab results and individualized question prompts that they can, in turn, refer to during physician consults.","PeriodicalId":72180,"journal":{"name":"AMIA ... Annual Symposium proceedings. AMIA Symposium","volume":"2023 ","pages":"407-416"},"PeriodicalIF":0.0,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10785897/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139467307","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Auditing Learned Associations in Deep Learning Approaches to Extract Race and Ethnicity from Clinical Text. 审核深度学习方法中的学习关联，从临床文本中提取种族和民族。

AMIA ... Annual Symposium proceedings. AMIA Symposium Pub Date : 2024-01-11 eCollection Date: 2023-01-01

Oliver J Bear Don't Walk Iv, Adrienne Pichon, Harry Reyes Nieva, Tony Sun, Jaan Altosaar, Karthik Natarajan, Adler Perotte, Peter Tarczy-Hornoch, Dina Demner-Fushman, Noémie Elhadad

{"title":"Auditing Learned Associations in Deep Learning Approaches to Extract Race and Ethnicity from Clinical Text.","authors":"Oliver J Bear Don't Walk Iv, Adrienne Pichon, Harry Reyes Nieva, Tony Sun, Jaan Altosaar, Karthik Natarajan, Adler Perotte, Peter Tarczy-Hornoch, Dina Demner-Fushman, Noémie Elhadad","doi":"","DOIUrl":"","url":null,"abstract":"Complete and accurate race and ethnicity (RE) patient information is important for many areas of biomedical informatics research, such as defining and characterizing cohorts, performing quality assessments, and identifying health inequities. Patient-level RE data is often inaccurate or missing in structured sources, but can be supplemented through clinical notes and natural language processing (NLP). While NLP has made many improvements in recent years with large language models, bias remains an often-unaddressed concern, with research showing that harmful and negative language is more often used for certain racial/ethnic groups than others. We present an approach to audit the learned associations of models trained to identify RE information in clinical text by measuring the concordance between model-derived salient features and manually identified RE-related spans of text. We show that while models perform well on the surface, there exist concerning learned associations and potential for future harms from RE-identification models if left unaddressed.","PeriodicalId":72180,"journal":{"name":"AMIA ... Annual Symposium proceedings. AMIA Symposium","volume":"2023 ","pages":"289-298"},"PeriodicalIF":0.0,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10785932/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139467352","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Challenges and Opportunities for Professional Medical Publications Writers to Contribute to Plain Language Summaries (PLS) in an AI/ML Environment - A Consumer Health Informatics Systematic Review. 专业医学出版物撰稿人在 AI/ML 环境中为通俗语言摘要 (PLS) 撰稿的挑战与机遇--消费者健康信息学系统综述。

AMIA ... Annual Symposium proceedings. AMIA Symposium Pub Date : 2024-01-11 eCollection Date: 2023-01-01

Holly R Tomlin, Michel Wissing, Sai Tanikella, Preetinder Kaur, Linda Tabas

{"title":"Challenges and Opportunities for Professional Medical Publications Writers to Contribute to Plain Language Summaries (PLS) in an AI/ML Environment - A Consumer Health Informatics Systematic Review.","authors":"Holly R Tomlin, Michel Wissing, Sai Tanikella, Preetinder Kaur, Linda Tabas","doi":"","DOIUrl":"","url":null,"abstract":"Professional medical publications writers (PMWs) cover a wide range of biomedical writing activities that recently includes translation of biomedical publications to plain language summaries (PLS). The consumer health informatics literature (CHI) consistently describes the importance of incorporating health literacy principles in any natural language processing (NLP) app designed to communicate medical information to lay audiences, particularly patients. In this stepwise systematic review, we searched PubMed indexed literature for CHI NLP-based apps that have the potential to assist PMWs in developing text based PLS. Results showed that available apps are limited to patient portals and other technologies used to communicate medical text and reports from electronic health records. PMWs can apply the lessons learned from CHI NLP-based apps to supervise development of tools specific to text simplification and summarization for PLS from biomedical publications.","PeriodicalId":72180,"journal":{"name":"AMIA ... Annual Symposium proceedings. AMIA Symposium","volume":"2023 ","pages":"709-717"},"PeriodicalIF":0.0,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10785924/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139467371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Comparative Merits of Available Mortality Data Sources for Clinical Research. 现有死亡率数据源在临床研究中的优势比较。

AMIA ... Annual Symposium proceedings. AMIA Symposium Pub Date : 2024-01-11 eCollection Date: 2023-01-01

Evan T Sholle, Marcos A Davila, Kristin Kostka, Sajjad Abedian, Marika Cusick, Spencer Krichevsky, Jyotishman Pathak, Thomas R Campion

引用次数: 0