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AMIA Summits on Translational Science Proceedings

Mohammadamin Tajgardoon, Michael M Wagner, Shyam Visweswara, Richard K Zimmerman
Computer simulation is the only method available for evaluating vaccination policy for rare diseases or emergency use of new vaccines. The most realistic simulation of vaccination policy is agent-based simulation (ABS) in which agents have similar socio-demographic characteristics to a population of interest. Currently, analysts use published information about vaccine efficacy (VE) as the probability that a vaccinated agent develops immunity; however, VE trials typically report only a single overall VE, or VE conditioned on one covariate (e...
2018: AMIA Summits on Translational Science Proceedings
Steven J Skube, Elizabeth A Lindemann, Elliot G Arsoniadis, Mari Akre, Elizabeth C Wick, Genevieve B Melton
Functional health status is an important factor not only for determining overall health, but also for measuring risks of adverse events. Our hypothesis is that important functional status data is contained in clinical notes. We found that several categories of phrases related to functional status including diagnoses, activity and care assessments, physical exam, functional scores, assistive equipment, symptoms, and surgical history were important factors. Use of functional health status level terms from our chart review compared to National Surgical Quality Improvement Program determination had varying sensitivities for correct functional status category identification, with 96% for independent patients, 60% for partially dependent patients, and 44% for totally dependent patients...
2018: AMIA Summits on Translational Science Proceedings
Nicolas Paris, Michael Mendis, Christel Daniel, Shawn Murphy, Xavier Tannier, Pierre Zweigenbaum
Integrating Biology and the Bedside (i2b2) is the de-facto open-source medical tool for cohort discovery. Fast Healthcare Interoperability Resources (FHIR) is a new standard for exchanging health care information electronically. Substitutable Modular third-party Applications (SMART) defines the SMART-on-FHIR specification on how applications shall interface with Electronic Health Records (EHR) through FHIR. Related work made it possible to produce FHIR from an i2b2 instance or made i2b2 able to store FHIR datasets...
2018: AMIA Summits on Translational Science Proceedings
Thomas Li, Cheng Gao, Chao Yan, Sarah Osmundson, Bradley A Malin, You Chen
Neonatal encephalopathy (NE) is a leading cause of neonatal mortality and lifetime neurological disability. The earlier the risk of NE can be assessed, the more effective interventions can be in preventing adverse outcomes. Existing studies that focus on intrapartum risk factors do not provide the early prognostic forecasting necessary to prepare healthcare professionals to intervene early in a high-risk NE case. This work used maternal data in a supervised machine learning framework to predict NE events. Specifically, we 1) collected the electronic medical records (EMRs) for 104 NE newborns and 31,054 non-NE newborns and their mothers, 2) trained and tested a regularized logistic regression on imbalanced and high-dimensional EMR data, and 3) discerned important features that could be possible risk factors...
2018: AMIA Summits on Translational Science Proceedings
Wesley M Durand, Paul C Stey, Elizabeth S Chen, Indra Neil Sarkar
Public health and clinical practice pattern trends are often analyzed using complex survey data. Use of statistical approaches that do not account for survey design predisposes to error, potentially leading to resource misdirection and inefficiency. This study examined two techniques for analyzing trends in complex survey data: (1) design-corrected logistic regression and (2) jackknife re-weighted linear regression. These approaches were compared toweighted least squares regression, as well as non-design corrected techniques...
2018: AMIA Summits on Translational Science Proceedings
Brian J Douthit, Rachel L Richesson
Clinical practice guidelines (CPGs) often serve as the knowledge base for clinical decision support (CDS). While CPGs are rigorously created by medical professional societies, the concepts in each guideline may not be sufficient for translation into CDS applications. In addition, clinicians' perceptions of these concepts may differ greatly, affecting the implementation and impact of CDS within an organization. Five guidelines developed by the American College of Emergency Physicians were systematically explored, generating fifty-one unique clinical concepts...
2018: AMIA Summits on Translational Science Proceedings
Jacob K Crump, Guilherme Del Fiol, Marc S Williams, Robert R Freimuth
Integration of genetic information is becoming increasingly important in clinical practice. However, genetic information is often ambiguous and difficult to understand, and clinicians have reported low-self-efficacy in integrating genetics into their care routine. The Health Level Seven (HL7) Infobutton standard helps to integrate online knowledge resources within Electronic Health Records (EHRs) and is required for EHR certification in the US. We implemented a prototype of a standards-based genetic reporting application coupled with infobuttons leveraging the Infobutton and Fast Healthcare Interoperability Resources (FHIR) Standards...
2018: AMIA Summits on Translational Science Proceedings
Alex Butler, Wei Wei, Chi Yuan, Tian Kang, Yuqi Si, Chunhua Weng
Much effort has been devoted to leverage EHR data for matching patients into clinical trials. However, EHRs may not contain all important data elements for clinical research eligibility screening. To better design research-friendly EHRs, an important step is to identify data elements frequently used for eligibility screening but not yet available in EHRs. This study fills this knowledge gap. Using the Alzheimer's disease domain as an example, we performed text mining on the eligibility criteria text in Clinicaltrials...
2018: AMIA Summits on Translational Science Proceedings
Rajsavi S Anand, Paul Stey, Sukrit Jain, Dustin R Biron, Harikrishna Bhatt, Kristina Monteiro, Edward Feller, Megan L Ranney, Indra Neil Sarkar, Elizabeth S Chen
Diabetes constitutes a significant health problem that leads to many long term health issues including renal, cardiovascular, and neuropathic complications. Many of these problems can result in increased health care costs, as well risk of ICU stay and mortality. To date, no published study has used predictive modeling to examine the relative influence of diabetes, diabetic health maintenance, and comorbidities on outcomes in ICU patients. Using the MIMIC-III database, machine learning and binomial logistic regression modeling were applied to predict risk of mortality...
2018: AMIA Summits on Translational Science Proceedings
Raniah N Aldekhyyel, Genevieve B Melton, Gretchen Hultman, Michael B Pitt
To measure the impact of a novel interactive inpatient pediatric pain management solution integrating our hospital's electronic health record system, the nurse communication phones, and the pharmacy dispensing system, we assessed parent and nurse perspectives on the tool's potential value, benefits, and challenges. A mixed-methods approach with survey instruments containing closed-ended and open-ended questions was administered to 30 parents and 59 nurses (66% and 23% response rate respectively). Overall, parents were more satisfied with the interactive technology experience (90%) compared to nurses (50%) with both indicating timely reassessments of pain being the most valuable feature...
2018: AMIA Summits on Translational Science Proceedings
Yiye Zhang, Rema Padman, Paul Epner, Victoria Bauer, Anthony Solomonides, Goutham Rao
The diagnostic process is a complex, uncertain, and highly variable process which is under-studied and lacks evidence from randomized clinical trials. This study used a novel visual analytics method to identify and visualize diagnostic paths for undifferentiated abdominal pain, by leveraging electronic health record (EHR) data of 501 patients in the ambulatory setting of a single institution. A total of 63 patients reached diagnoses in the study sample. We illustrate steps in identifying diagnostic paths of the study patients, both individually and collectively, and visually present the diversity in their diagnostic processes...
2018: AMIA Summits on Translational Science Proceedings
Yaoyun Zhang, Hee-Jin Li, Jingqi Wang, Trevor Cohen, Kirk Roberts, Hua Xu
Mental health is increasingly recognized an important topic in healthcare. Information concerning psychiatric symptoms is critical for the timely diagnosis of mental disorders, as well as for the personalization of interventions. However, the diversity and sparsity of psychiatric symptoms make it challenging for conventional natural language processing techniques to automatically extract such information from clinical text. To address this problem, this study takes the initiative to use and adapt word embeddings from four source domains - intensive care, biomedical literature, Wikipedia and Psychiatric Forum - to recognize symptoms in the target domain of psychiatry...
2018: AMIA Summits on Translational Science Proceedings
Cheng Ye, Joseph Coco, Anna Epishova, Chen Hajaj, Henry Bogardus, Laurie Novak, Joshua Denny, Yevgeniy Vorobeychik, Thomas Lasko, Bradley Malin, Daniel Fabbri
Crowdsourcing services like Amazon Mechanical Turk allow researchers to ask questions to crowds of workers and quickly receive high quality labeled responses. However, crowds drawn from the general public are not suitable for labeling sensitive and complex data sets, such as medical records, due to various concerns. Major challenges in building and deploying a crowdsourcing system for medical data include, but are not limited to: managing access rights to sensitive data and ensuring data privacy controls are enforced; identifying workers with the necessary expertise to analyze complex information; and efficiently retrieving relevant information in massive data sets...
2018: AMIA Summits on Translational Science Proceedings
Shen Xu, Toby Rogers, Elliot Fairweather, Anthony Glenn, James Curran, Vasa Curcin
Data provenance is a technique that describes the history of digital objects. In health data settings, it can be used to deliver auditability and transparency, and to achieve trust in a software system. However, implementing data provenance in analytics software at an enterprise level presents a different set of challenges from the research environments where data provenance was originally devised. In this paper, the challenges of reporting provenance information to the user is presented. Provenance captured from analytics software can be large and complex and visualizing a series of tasks over a long period can be overwhelming even for a domain expert, requiring visual aggregation mechanisms that fit with complex human cognitive activities involved in the process...
2018: AMIA Summits on Translational Science Proceedings
Ran Xiao, Yuan Xu, Michele M Pelter, David W Mortara, Xiao Hu
Patients with suspected acute coronary syndrome (ACS) are at risk of transient myocardial ischemia (TMI), which could lead to serious morbidity or even mortality. Early detection of myocardial ischemia can reduce damage to heart tissues and improve patient condition. Significant ST change in the electrocardiogram (ECG) is an important marker for detecting myocardial ischemia during the rule-out phase of potential ACS. However, current ECG monitoring software is vastly underused due to excessive false alarms...
2018: AMIA Summits on Translational Science Proceedings
Patrick M Zhang, Indra Neil Sarkar
Recent technological advancements in genetic testing and the growing accessibility of public genomic data provide researchers with a unique avenue to approach personalized medicine. This feasibility study examined the potential of direct-to-consumer (DTC) genomic tests (focusing on 23andMe) in research and clinical applications. In particular, we combined population genetics information from the Personal Genome Project with adverse event reports from AEOLUS and pharmacogenetic information from PharmGKB. Primarily, associations between drugs based on co-occurring genetic variations and associations between variants and adverse events were used to assess the potential for leveraging single nucleotide polymorphism information from 23andMe...
2018: AMIA Summits on Translational Science Proceedings
Danny T Y Wu, Kai Zheng, David J Bradley
All academic medical centers have a strong desire to maximize the value of their clinical data for secondary use purposes such as quality improvement (QI) and research. However, this need has not been adequately fulfilled due in part to the fact that the data capture functions in current electronic health record systems predominantly focus on clinical documentation and billing, lacking the flexibility to allow the collection of additional data elements critical to QI or research. To address this gap, we designed and developed a dynamic data platform to support clinicians' varied needs for recording additional data about their patients outside of direct patient care (e...
2018: AMIA Summits on Translational Science Proceedings
Wen Yin, Cheng Gao, Yaomin Xu, Bingshan Li, Douglas M Ruderfer, You Chen
Drug repositioning for available medications can be preferred over traditional drug development, which requires substantially more effort to uncover new insights into medications and diseases. Genome-Wide Association Studies (GWAS) and Phenome-Wide Association Studies (PheWAS) are two complimentary methods for finding novel associations between genes and diseases. We hypothesize that discoveries from these studies could be leveraged to find new targets for existing drugs. Thus, we propose a framework to learn opportunities for inferring such relationships via overlapped genes between disease-associated genes (e...
2018: AMIA Summits on Translational Science Proceedings
Tamara J Winden, Elizabeth S Chen, Karen A Monsen, Yan Wang, Genevieve B Melton
Social determinants of health (SDOH) are important considerations in diagnosis, prevention, and health outcomes. However, they are often not well documented in the EHR and found primarily in unstructured or semi-structured text. Building upon previous work, we analyzed all flowsheet data in 2013 for information related to the SDOH topic areas of Residence, Living Situation, and Living Conditions. Overall, 91 rows were identified as being related to the topics areas resulting in 604,616 unique observations. Individual rows contained SDOH data often covered multiple concepts especially free-text entries...
2018: AMIA Summits on Translational Science Proceedings
Si Wen, Tahsin M Kurc, Le Hou, Joel H Saltz, Rajarsi R Gupta, Rebecca Batiste, Tianhao Zhao, Vu Nguyen, Dimitris Samaras, Wei Zhu
Segmentation of nuclei in whole slide tissue images is a common methodology in pathology image analysis. Most segmentation algorithms are sensitive to input algorithm parameters and the characteristics of input images (tissue morphology, staining, etc.). Because there can be large variability in the color, texture, and morphology of tissues within and across cancer types (heterogeneity can exist even within a tissue specimen), it is likely that a set of input parameters will not perform well across multiple images...
2018: AMIA Summits on Translational Science Proceedings
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