AMIA ... Annual Symposium proceedings. AMIA Symposium最新文献_第3页

Identifying the Optimal Look-back Period for Prior Antimicrobial Resistance Clinical Decision Support. 确定先前抗菌药耐药性临床决策支持的最佳回溯期。

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

John J Hanna, Abdi D Wakene, Lauren N Cooper, Marlon I Diaz, Catherine Chen, Christoph U Lehmann, Richard J Medford

{"title":"Identifying the Optimal Look-back Period for Prior Antimicrobial Resistance Clinical Decision Support.","authors":"John J Hanna, Abdi D Wakene, Lauren N Cooper, Marlon I Diaz, Catherine Chen, Christoph U Lehmann, Richard J Medford","doi":"","DOIUrl":"","url":null,"abstract":"Background: Lack of consensus on the appropriate look-back period for multi-drug resistance (MDR) complicates antimicrobial clinical decision support. We compared the predictive performance of different MDR look-back periods for five common MDR mechanisms (MRSA, VRE, ESBL, AmpC, CRE).Methods: We mapped microbiological cultures to MDR mechanisms and labeled them at different look-back periods. We compared predictive performance for each look-back period-MDR combination using precision, recall, F1 scores, and odds ratios.Results: Longer look-back periods resulted in lower odds ratios, lower precisions, higher recalls, and lower delta changes in precision and recall compared to shorter periods. We observed higher precision with more information available to clinicians.Conclusion: A previously positive MDR culture may have significant enough precision depending on the mechanism of resistance and varying information available. One year is a clinically relevant and statistically sound look-back period for empiric antimicrobial decision-making at varying points of care for the studied population.","PeriodicalId":72180,"journal":{"name":"AMIA ... Annual Symposium proceedings. AMIA Symposium","volume":"2023 ","pages":"969-976"},"PeriodicalIF":0.0,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10785855/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139467455","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

Effects of Porting Essie Tokenization and Normalization to Solr. 将 Essie 标记化和规范化移植到 Solr 的效果。

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

Soumya Gayen, Deepak Gupta, Russell F Loane, Nicholas C Ide, Dina Demner-Fushman

引用次数: 0

Prediction of Transfusion among In-patient Population using Temporal Pattern based Clinical Similarity Graphs. 利用基于时态模式的临床相似性图预测住院病人输血情况

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

Amara Tariq, Leon Su, Bhavik Patel, Imon Banerjee

{"title":"Prediction of Transfusion among In-patient Population using Temporal Pattern based Clinical Similarity Graphs.","authors":"Amara Tariq, Leon Su, Bhavik Patel, Imon Banerjee","doi":"","DOIUrl":"","url":null,"abstract":"Intelligent prediction of risk of blood transfusion among hospitalized patients can identify at-risk patients and provide timely information to the hospital to plan and reserve resources to meet the demand of blood transfusion. While previously proposed solutions focus on sub-populations such as patients admitted to ICU after gastrointestinal bleeding or postpartum patients with hemorrhage, we design a predictive model applicable to complete in-patient population. Our model relies on patients' similarity graph based on temporal patterns among clinical history of the patients. These graphs are processed through graph convolutional neural network (GCNN) to estimate node or patient level risk of blood transfusion. Thus, our model not only learns from the patient's own clinical history but also from other patients with similar clinical history. The model is also capable of fusing diverse data elements from electronic health records (EHR) such as demographic information, billing codes, and recorded vital signs. Our model was validated on both internal and external sets and outperformed all comparative baseline models.","PeriodicalId":72180,"journal":{"name":"AMIA ... Annual Symposium proceedings. AMIA Symposium","volume":"2023 ","pages":"679-688"},"PeriodicalIF":0.0,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10785860/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139467589","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

The SIMPLE Architectural Pattern for Integrating Patient-Facing Apps into Clinical Workflows: Desiderata and Application for Lung Cancer Screening. 将面向患者的应用程序整合到临床工作流程中的 SIMPLE 架构模式：肺癌筛查的需求和应用。

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

Christian A Balbin, Kensaku Kawamoto

引用次数: 0

"In conferences, everyone goes 'health data is the future' ": an interview study on challenges in re-using EHR data for research in Clinical Data Warehouses. "在会议上，每个人都在说'健康数据是未来'：关于在临床数据仓库中重新使用电子病历数据进行研究的挑战的访谈研究。

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

Sonia Priou, Guillaume Lame, Marija Jankovic, Emmanuelle Kempf

引用次数: 0

Large Language Models for Healthcare Data Augmentation: An Example on Patient-Trial Matching. 用于医疗保健数据增强的大型语言模型：以患者-试验匹配为例。

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

Jiayi Yuan, Ruixiang Tang, Xiaoqian Jiang, Xia Hu

{"title":"Large Language Models for Healthcare Data Augmentation: An Example on Patient-Trial Matching.","authors":"Jiayi Yuan, Ruixiang Tang, Xiaoqian Jiang, Xia Hu","doi":"","DOIUrl":"","url":null,"abstract":"The process of matching patients with suitable clinical trials is essential for advancing medical research and providing optimal care. However, current approaches face challenges such as data standardization, ethical considerations, and a lack of interoperability between Electronic Health Records (EHRs) and clinical trial criteria. In this paper, we explore the potential of large language models (LLMs) to address these challenges by leveraging their advanced natural language generation capabilities to improve compatibility between EHRs and clinical trial descriptions. We propose an innovative privacy-aware data augmentation approach for LLM-based patient-trial matching (LLM-PTM), which balances the benefits of LLMs while ensuring the security and confidentiality of sensitive patient data. Our experiments demonstrate a 7.32% average improvement in performance using the proposed LLM-PTM method, and the generalizability to new data is improved by 12.12%. Additionally, we present case studies to further illustrate the effectiveness of our approach and provide a deeper understanding of its underlying principles.","PeriodicalId":72180,"journal":{"name":"AMIA ... Annual Symposium proceedings. AMIA Symposium","volume":"2023 ","pages":"1324-1333"},"PeriodicalIF":0.0,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10785941/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139467513","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

Mapping Clinical Documents to the Logical Observation Identifiers, Names and Codes (LOINC) Document Ontology using Electronic Health Record Systems Structured Metadata. 利用电子健康记录系统结构元数据将临床文档映射到逻辑观察标识符、名称和代码（LOINC）文档本体。

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

Huzaifa Khan, Abu Saleh Mohammad Mosa, Vyshnavi Paka, Md Kamruz Zaman Rana, Vasanthi Mandhadi, Soliman Islam, Hua Xu, James C McClay, Sraboni Sarker, Praveen Rao, Lemuel R Waitman

{"title":"Mapping Clinical Documents to the Logical Observation Identifiers, Names and Codes (LOINC) Document Ontology using Electronic Health Record Systems Structured Metadata.","authors":"Huzaifa Khan, Abu Saleh Mohammad Mosa, Vyshnavi Paka, Md Kamruz Zaman Rana, Vasanthi Mandhadi, Soliman Islam, Hua Xu, James C McClay, Sraboni Sarker, Praveen Rao, Lemuel R Waitman","doi":"","DOIUrl":"","url":null,"abstract":"As Electronic Health Record (EHR) systems increase in usage, organizations struggle to maintain and categorize clinical documentation so it can be used for clinical care and research. While prior research has often employed natural language processing techniques to categorize free text documents, there are shortcomings relative to computational scalability and the lack of key metadata within notes' text. This study presents a framework that can allow institutions to map their notes to the LOINC document ontology using a Bag of Words approach. After preliminary manual value- set mapping, an automated pipeline that leverages key dimensions of metadata from structured EHR fields aligns the notes with the dimensions of the document ontology. This framework resulted in 73.4% coverage of EHR documents, while also mapping 132 million notes in less than 2 hours; an order of magnitude more efficient than NLP based methods.","PeriodicalId":72180,"journal":{"name":"AMIA ... Annual Symposium proceedings. AMIA Symposium","volume":"2023 ","pages":"1017-1026"},"PeriodicalIF":0.0,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10785913/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139467532","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

Variability in Nursing Documentation Patterns across Patients' Hospital Stays. 病人住院期间护理记录模式的差异。

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

Rachel Y Lee, Christopher Knaplund, Jennifer Withall, Syed Mohtashim Bokhari, Kenrick D Cato, Sarah C Rossetti

引用次数: 0

A QUEST for Model Assessment: Identifying Difficult Subgroups via Epistemic Uncertainty Quantification. 模型评估的 QUEST：通过认识不确定性量化识别困难子群。

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

Katherine E Brown, Steve Talbert, Douglas A Talbert

引用次数: 0

Analysis of Task Attributes Associated with Crisis Checklist Compliance in Pediatric Trauma Resuscitation. 分析与儿科创伤复苏中危机核对表合规性相关的任务属性。

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

Angela Mastrianni, Leah Hamlin, Emily C Alberto, Travis M Sullivan, Adesh Ranganna, Ivan Marsic, Randall S Burd, Aleksandra Sarcevic

{"title":"Analysis of Task Attributes Associated with Crisis Checklist Compliance in Pediatric Trauma Resuscitation.","authors":"Angela Mastrianni, Leah Hamlin, Emily C Alberto, Travis M Sullivan, Adesh Ranganna, Ivan Marsic, Randall S Burd, Aleksandra Sarcevic","doi":"","DOIUrl":"","url":null,"abstract":"Although checklists can improve overall team performance during medical crises, non-compliant checklist use poses risks to patient safety. We examined how task attributes affected checklist compliance by studying the use of a digital checklist during trauma resuscitation. We first determined task attributes and checklist compliance behaviors for 3,131 resuscitation tasks. Using statistical analyses and qualitative video review, we then identified barriers to accurately tracking task status, finding that certain task attributes were associated with non-compliant checklist behaviors. For example, tasks with multiple steps were more likely to be incorrectly recorded as completed when the task was not performed to completion. We discuss challenges in capturing and tracking the status of tasks with attributes that contribute to non-compliant checklist use. We also contribute a framework for understanding how tasks with certain attributes can be designed on checklists to improve compliance.","PeriodicalId":72180,"journal":{"name":"AMIA ... Annual Symposium proceedings. AMIA Symposium","volume":"2023 ","pages":"504-513"},"PeriodicalIF":0.0,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10785895/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139467143","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