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

Influence of the CONCERN Early Warning System on Unanticipated ICU Transfers, In-Hospital Mortality, and Length of Stay: Results from a Multi-site Pragmatic Randomized Controlled Clinical Trial. CONCERN预警系统对意外ICU转院、住院死亡率和住院时间的影响：一项多地点实用随机对照临床试验的结果

AMIA ... Annual Symposium proceedings. AMIA Symposium Pub Date : 2025-05-22 eCollection Date: 2024-01-01

Rachel Y Lee, Kenrick D Cato, Patricia C Dykes, Graham Lowenthal, Jennifer B Withall, Sandy Cho, Haomiao Jia, Sarah C Rossetti

{"title":"Influence of the CONCERN Early Warning System on Unanticipated ICU Transfers, In-Hospital Mortality, and Length of Stay: Results from a Multi-site Pragmatic Randomized Controlled Clinical Trial.","authors":"Rachel Y Lee, Kenrick D Cato, Patricia C Dykes, Graham Lowenthal, Jennifer B Withall, Sandy Cho, Haomiao Jia, Sarah C Rossetti","doi":"","DOIUrl":"","url":null,"abstract":"Communicating Narrative Concerns Entered by RNs Early Warning System (CONCERN EWS) is a machine-learning predictive model that leverages nursing surveillance documentation patterns to predict deterioration risks for hospitalized patients. In a retrospective cohort study of 1,013 hospital encounters with unanticipated ICU transfers from a multi-site pragmatic randomized controlled trial, we assessed the influence of CONCERN EWS on in-hospital mortality and length of stay following unanticipated ICU transfers. Chi-square tests, t-tests, multivariate logistic regression, and generalized linear models were used. Our findings showed that patients who had unanticipated ICU transfers from acute care units with CONCERN EWS had a lower in-hospital mortality rate and a shorter average hospital stay than those transferred from units receiving usual care. These results suggest that CONCERN EWS enhances shared situational awareness for care teams, improves communication, and effectively facilitates timely interventions, thereby streamlining care processes and improving patient outcomes.","PeriodicalId":72180,"journal":{"name":"AMIA ... Annual Symposium proceedings. AMIA Symposium","volume":"2024 ","pages":"655-663"},"PeriodicalIF":0.0,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12099359/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144144674","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

Clinician Perspectives on a Predictive Model for Recommending Opioid Use Disorder Treatment. 推荐阿片类药物使用障碍治疗的预测模型的临床医生观点。

AMIA ... Annual Symposium proceedings. AMIA Symposium Pub Date : 2025-05-22 eCollection Date: 2024-01-01

Leigh Anne Tang, Michelle Gomez, Uday Suresh, Kristopher A Kast, Robert A Becker, Thomas J Reese, Colin G Walsh, Jessica S Ancker

{"title":"Clinician Perspectives on a Predictive Model for Recommending Opioid Use Disorder Treatment.","authors":"Leigh Anne Tang, Michelle Gomez, Uday Suresh, Kristopher A Kast, Robert A Becker, Thomas J Reese, Colin G Walsh, Jessica S Ancker","doi":"","DOIUrl":"","url":null,"abstract":"Background: Predictive models that have been made available as clinical decision support systems have not always been used. Objectives: This qualitative study aimed to identify factors that might impact the uptake of a predictive model recommending either methadone or buprenorphine as medication for opioid use disorder (MOUD) in the inpatient setting. Methods: We conducted semi-structured interviews with clinicians who prescribe MOUD and performed a combined deductive and inductive content analysis using a socio-technical model. Results: Thirteen clinicians were interviewed. Non-specialists trusted their specialist peers to lead MOUD decisions and claimed they would trust a tool endorsed by experts and the institution. Clinicians expected the model to follow clinical reasoning, which involves considering factors that are not well-captured by the electronic health record (e.g., housing status, access to care, facility preferences). Conclusion: Predictive models for MOUD should be designed to foster appropriate trust given the tool's purpose, process, limitation, and performance.","PeriodicalId":72180,"journal":{"name":"AMIA ... Annual Symposium proceedings. AMIA Symposium","volume":"2024 ","pages":"1109-1118"},"PeriodicalIF":0.0,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12099360/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144144426","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

Derivation and Experimental Performance of Standard and Novel Uncertainty Calibration Techniques. 标准和新型不确定度校准技术的推导和实验性能。

AMIA ... Annual Symposium proceedings. AMIA Symposium Pub Date : 2025-05-22 eCollection Date: 2024-01-01

Katherine E Brown, Steve Talbert, Douglas A Talbert

引用次数: 0

"Getting people access to services is also getting them access to a phone": Clarifying digital divide dynamics and their consequences in Community Mental Health Care. “让人们获得服务也让他们获得电话”：澄清社区精神卫生保健中的数字鸿沟动态及其后果。

AMIA ... Annual Symposium proceedings. AMIA Symposium Pub Date : 2025-05-22 eCollection Date: 2024-01-01

Alicia K Williamson, Ella Jiaqi Li, Tiffany C Veinot

{"title":"\"Getting people access to services is also getting them access to a phone\": Clarifying digital divide dynamics and their consequences in Community Mental Health Care.","authors":"Alicia K Williamson, Ella Jiaqi Li, Tiffany C Veinot","doi":"","DOIUrl":"","url":null,"abstract":"Access to mental healthcare is increasingly technologically-mediated. People with low socioeconomic status (SES) and serious mental illness (SMI) face lower rates of tech ownership and may lack technological skills, called \"digital divides.\" Yet, little is known about how digital divides may impact mental healthcare access. Therefore, a qualitative study (ethnographic observations and interviews) was conducted with stakeholders working with low-SES SMI patients using community mental health care (CMH) (N=14). Findings showed that consumers struggled to maintain consistent internet-and thus mental healthcare-access despite owning smartphones. Consumers frequently faced care disruptions due to broken, lost, or uncharged phones. Staff and patients created effortful but ad-hoc workarounds to restore access during technological access disruptions. These solutions frequently occurred after healthcare appointments were missed. Digital divide concepts should accommodate the work necessary to maintain technology access even after ownership and its impact on care access-especially among low-SES SMI patients.","PeriodicalId":72180,"journal":{"name":"AMIA ... Annual Symposium proceedings. AMIA Symposium","volume":"2024 ","pages":"1245-1254"},"PeriodicalIF":0.0,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12099397/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144144677","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

Using a Healthcare Process Modeling Approach to Understand Electronic Health Records-based Pressure Injury Data and to Support Development of a Standardized Pressure Injury Phenotyping Pipeline. 使用医疗保健过程建模方法来理解基于电子健康记录的压力损伤数据，并支持标准化压力损伤表型管道的开发。

AMIA ... Annual Symposium proceedings. AMIA Symposium Pub Date : 2025-05-22 eCollection Date: 2024-01-01

Luwei Liu, Min-Jeoung Kang, Michael Sainlaire, Graham Lowenthal, Tanya Martel, Sandy Cho, Debra Furlong, Wadia Gilles-Fowler, Luciana Schleder Goncalves, Lisa Herlihy, Veysel Karani Baris, Jacqueline Massaro, Beth Melanson, Lori D Morrow, Paula Wolski, Wenyu Song, Patricia C Dykes

{"title":"Using a Healthcare Process Modeling Approach to Understand Electronic Health Records-based Pressure Injury Data and to Support Development of a Standardized Pressure Injury Phenotyping Pipeline.","authors":"Luwei Liu, Min-Jeoung Kang, Michael Sainlaire, Graham Lowenthal, Tanya Martel, Sandy Cho, Debra Furlong, Wadia Gilles-Fowler, Luciana Schleder Goncalves, Lisa Herlihy, Veysel Karani Baris, Jacqueline Massaro, Beth Melanson, Lori D Morrow, Paula Wolski, Wenyu Song, Patricia C Dykes","doi":"","DOIUrl":"","url":null,"abstract":"The complexity of health care processes present significant challenges for using Electronic Health Records (EHR) data to build high fidelity phenotypes. This study leverages a healthcare process modeling (HPM) approach to enable understanding of EHR-based pressure injury (PrI) data patterns needed for building a standardized PrI phenotyping pipeline. The PrI HPM was developed and validated using mixed methods, including exploratory sequential design, through interdisciplinary collaboration among clinical experts, data scientists, database analysts, and informaticians. zThe qualitative analysis identified the dynamics between PrI care and the associated clinical documentation processes. The quantitative analysis identified inherent challenges and limitations of the PrI data. The PrI HPM includes three moderating factors: system configuration, hospital policy, and nurse's individual workflow. We further incorporated the HPM into the PrI phenotype development process to address phenotyping challenges. Moreover, we suggested a set of standardizable recommendations to address PrI phenotyping challenges.","PeriodicalId":72180,"journal":{"name":"AMIA ... Annual Symposium proceedings. AMIA Symposium","volume":"2024 ","pages":"738-747"},"PeriodicalIF":0.0,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12099414/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144144862","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

Exploring the use of Artificial Genomes for Genome-wide Association Studies through the lens of Utility and Privacy. 通过效用和隐私的视角探索人工基因组在全基因组关联研究中的应用。

AMIA ... Annual Symposium proceedings. AMIA Symposium Pub Date : 2025-05-22 eCollection Date: 2024-01-01

Xinyue Wang, Sitao Min, Jaideep Vaidya

{"title":"Exploring the use of Artificial Genomes for Genome-wide Association Studies through the lens of Utility and Privacy.","authors":"Xinyue Wang, Sitao Min, Jaideep Vaidya","doi":"","DOIUrl":"","url":null,"abstract":"Collaborative Genome-wide association studies (GWAS) have the potential to uncover rare genetic variant-trait associations by leveraging larger datasets and diverse population samples. Despite this potential, privacy concerns and cumbersome review processes for data validation and collaborator selection hinder their broader implementation. Advances in generative models present a possible solution by generating synthetic datasets that closely resemble real genomic data, thus enhancing privacy and expediting the review process. This study assesses the capability of deep generative models to produce artificial genomic data for GWAS applications. We evaluate two state-of-the-art models on real-world datasets, identifying significant limitations in their ability to generate high-quality artificial genomes. Furthermore, we demonstrate that prevailing privacy measures, mainly based on membership inference attacks, are inadequate for providing insightful privacy evaluations. Our findings highlight the critical challenges and suggest future directions for the effective use of artificial genomes in GWAS.","PeriodicalId":72180,"journal":{"name":"AMIA ... Annual Symposium proceedings. AMIA Symposium","volume":"2024 ","pages":"1196-1205"},"PeriodicalIF":0.0,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12099349/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144144612","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

Adaptive Recruitment Resource Allocation to Improve Cohort Representativeness in Participatory Biomedical Datasets. 自适应招募资源分配提高参与性生物医学数据集的队列代表性。

AMIA ... Annual Symposium proceedings. AMIA Symposium Pub Date : 2025-05-22 eCollection Date: 2024-01-01

Victor A Borza, Andrew Estornell, Ellen Wright Clayton, Chien-Ju Ho, Russell L Rothman, Yevgeniy Vorobeychik, Bradley A Malin

{"title":"Adaptive Recruitment Resource Allocation to Improve Cohort Representativeness in Participatory Biomedical Datasets.","authors":"Victor A Borza, Andrew Estornell, Ellen Wright Clayton, Chien-Ju Ho, Russell L Rothman, Yevgeniy Vorobeychik, Bradley A Malin","doi":"","DOIUrl":"","url":null,"abstract":"Large participatory biomedical studies - studies that recruit individuals to join a dataset - are gaining popularity and investment, especially for analysis by modern AI methods. Because they purposively recruit participants, these studies are uniquely able to address a lack of historical representation, an issue that has affected many biomedical datasets. In this work, we define representativeness as the similarity to a target population distribution of a set of attributes and our goal is to mirror the U.S. population across distributions of age, gender, race, and ethnicity. Many participatory studies recruit at several institutions, so we introduce a computational approach to adaptively allocate recruitment resources among sites to improve representativeness. In simulated recruitment of 10,000-participant cohorts from medical centers in the STAR Clinical Research Network, we show that our approach yields a more representative cohort than existing baselines. Thus, we highlight the value of computational modeling in guiding recruitment efforts.","PeriodicalId":72180,"journal":{"name":"AMIA ... Annual Symposium proceedings. AMIA Symposium","volume":"2024 ","pages":"192-201"},"PeriodicalIF":0.0,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12099364/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144144693","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

Time Matters: Examine Temporal Effects on Biomedical Language Models. 时间问题：检验生物医学语言模型的时间效应。

AMIA ... Annual Symposium proceedings. AMIA Symposium Pub Date : 2025-05-22 eCollection Date: 2024-01-01

Weisi Liu, Zhe He, Xiaolei Huang

引用次数: 0

Where do doctors disagree? Characterizing Decision Points for Safe Reinforcement Learning in Choosing Vasopressor Treatment. 医生们在哪些方面存在分歧？选择血管加压药物治疗的安全强化学习决策点特征。

AMIA ... Annual Symposium proceedings. AMIA Symposium Pub Date : 2025-05-22 eCollection Date: 2024-01-01

Esther Brown, Shivam Raval, Alex Rojas, Jiayu Yao, Sonali Parbhoo, Leo A Celi, Siddharth Swaroop, Weiwei Pan, Finale Doshi-Velez

{"title":"Where do doctors disagree? Characterizing Decision Points for Safe Reinforcement Learning in Choosing Vasopressor Treatment.","authors":"Esther Brown, Shivam Raval, Alex Rojas, Jiayu Yao, Sonali Parbhoo, Leo A Celi, Siddharth Swaroop, Weiwei Pan, Finale Doshi-Velez","doi":"","DOIUrl":"","url":null,"abstract":"In clinical settings, domain experts sometimes disagree on optimal treatment actions. These \"decision points\" must be comprehensively characterized, as they offer opportunities for Artificial Intelligence (AI) to provide statistically informed recommendations. To address this, we introduce a pipeline to investigate \"decision regions\", clusters of decision points, by training classifiers for prediction and applying clustering techniques to the classifier's embedding space. Our methodology includes: a robustness analysis confirming the topological stability of decision regions across diverse design parameters; an empirical study using the MIMIC-III database, focusing on the binary decision to administer vasopressors to hypotensive patients in the ICU; and an expert-validated summary of the decision regions' statistical attributes with novel clinical interpretations. We demonstrate that the topology of these decision regions remains stable across various design choices, reinforcing the reliability of our findings and generalizability of our approach. We encourage future work to extend this approach to other medical datasets.","PeriodicalId":72180,"journal":{"name":"AMIA ... Annual Symposium proceedings. AMIA Symposium","volume":"2024 ","pages":"222-231"},"PeriodicalIF":0.0,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12099420/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144144360","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

Ontology-based modeling, integration, and analysis of heterogeneous clinical, pathological, and molecular kidney data for precision medicine. 基于本体的建模、整合和分析异构临床、病理和分子肾数据，用于精准医学。

AMIA ... Annual Symposium proceedings. AMIA Symposium Pub Date : 2025-05-22 eCollection Date: 2024-01-01

Yongqun Oliver He, Laura Barisoni, Avi Z Rosenberg, Peter Robinson, Alexander D Diehl, Yichao Chen, Jim Phuong, Jens Hansen, Bruce W Herr Ii, Katy Börner, Jennifer Schaub, Nikki Bonevich, Ghida Arnous, Saketh Boddapati, Jie Zheng, Fadhl Alakwaa, Pinaki Sardar, William D Duncan, Chen Liang, M Todd Valerius, Sanjay Jain, Ravi Iyengar, Jonathan Himmelfarb, Matthias Kretzler

{"title":"Ontology-based modeling, integration, and analysis of heterogeneous clinical, pathological, and molecular kidney data for precision medicine.","authors":"Yongqun Oliver He, Laura Barisoni, Avi Z Rosenberg, Peter Robinson, Alexander D Diehl, Yichao Chen, Jim Phuong, Jens Hansen, Bruce W Herr Ii, Katy Börner, Jennifer Schaub, Nikki Bonevich, Ghida Arnous, Saketh Boddapati, Jie Zheng, Fadhl Alakwaa, Pinaki Sardar, William D Duncan, Chen Liang, M Todd Valerius, Sanjay Jain, Ravi Iyengar, Jonathan Himmelfarb, Matthias Kretzler","doi":"","DOIUrl":"","url":null,"abstract":"Many data resources generate, process, store, or provide kidney related molecular, pathological, and clinical data. Reference ontologies offer an opportunity to support knowledge and data integration. The Kidney Precision Medicine Project (KPMP) team contributed to the representation and addition of 329 kidney phenotype terms to the Human Phenotype Ontology (HPO), and identified many subcategories of acute kidney injury (AKI) or chronic kidney disease (CKD). The Kidney Tissue Atlas Ontology (KTAO) imports and integrates kidney-related terms from existing ontologies (e.g., HPO, CL, and Uberon) and represents 259 kidney-related biomarkers. We have also developed a precision medicine metadata ontology (PMMO) to integrate 50 variables from KPMP and CZ CellxGene data resources and applied PMMO for integrative kidney data analysis. The gene expression profiles of kidney gene biomarkers were specifically analyzed under healthy control or AKI/CKD disease states. This work demonstrates how ontology-based approaches support multi-domain data and knowledge integration in precision medicine.","PeriodicalId":72180,"journal":{"name":"AMIA ... Annual Symposium proceedings. AMIA Symposium","volume":"2024 ","pages":"523-532"},"PeriodicalIF":0.0,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12099421/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144144641","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