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AMIA ... Annual Symposium Proceedings

Fei Wang, Chuanren Liu, Yajuan Wang, Jianying Hu, Guoqiang Yu
[This retracts the article on p. 1269 in vol. 2015, PMID: 26958267.].
2015: AMIA ... Annual Symposium Proceedings
Yan Wang, Elizabeth S Chen, Serguei Pakhomov, Elliot Arsoniadis, Elizabeth W Carter, Elizabeth Lindemann, Indra Neil Sarkar, Genevieve B Melton
Within clinical discourse, social history (SH) includes important information about substance use (alcohol, drug, and nicotine use) as key risk factors for disease, disability, and mortality. In this study, we developed and evaluated a natural language processing (NLP) system for automated detection of substance use statements and extraction of substance use attributes (e.g., temporal and status) based on Stanford Typed Dependencies. The developed NLP system leveraged linguistic resources and domain knowledge from a multi-site social history study, Propbank and the MiPACQ corpus...
2015: AMIA ... Annual Symposium Proceedings
Lucy L Wang, Eli Grunblatt, Hyunggu Jung, Ira J Kalet, Mark E Whipple
Constructing a biological model using an established ontology provides a unique opportunity to perform content auditing on the ontology. We built a Markov chain model to study tumor metastasis in the regional lymphatics of patients with head and neck squamous cell carcinoma (HNSCC). The model attempts to determine regions with high likelihood for metastasis, which guides surgeons and radiation oncologists in selecting the boundaries of treatment. To achieve consistent anatomical relationships, the nodes in our model are populated using lymphatic objects extracted from the Foundational Model of Anatomy (FMA) ontology...
2015: AMIA ... Annual Symposium Proceedings
Mariƫtte M van Engen-Verheul, Wouter T Gude, Sabine N van der Veer, Hareld M C Kemps, Monique M W Jaspers, Nicolette F de Keizer, Niels Peek
Despite their widespread use, audit and feedback (A&F) interventions show variable effectiveness on improving professional performance. Based on known facilitators of successful A&F interventions, we developed a web-based A&F intervention with indicator-based performance feedback, benchmark information, action planning and outreach visits. The goal of the intervention was to engage with multidisciplinary teams to overcome barriers to guideline concordance and to improve overall team performance in the field of cardiac rehabilitation (CR)...
2015: AMIA ... Annual Symposium Proceedings
Mengmeng Sun, Wei Zhu, Shiqiang Tao, Licong Cui, Guo-Qiang Zhang
Ontology search interfaces can benefit from the latest information retrieval advances. This paper introduces a Conjunctive Ontology Browser and Explorer (COBE) for searching and exploring SNOMED CT concepts and visualizing SNOMED CT fragments. COBE combines navigational exploration (NE) with direct lookup (DL) as two complementary modes for finding specific SNOMED CT concepts. The NE mode allows a user to interactively and incrementally narrow down (hence conjunctive) the search space by adding word stems, one at a time...
2015: AMIA ... Annual Symposium Proceedings
Maxwell T Spadafore, Zeeshan Syed, Ilan S Rubinfeld
To enable automated maintenance of patient sedation in an intensive care unit (ICU) setting, more robust, quantitative metrics of sedation depth must be developed. In this study, we demonstrated the feasibility of a fully computational system that leverages low-quality electrocardiography (ECG) from a single lead to detect the presence of benzodiazepine sedatives in a subject's system. Starting with features commonly examined manually by cardiologists searching for evidence of poisonings, we generalized the extraction of these features to a fully automated process...
2015: AMIA ... Annual Symposium Proceedings
Vanessa Sochat, Maude David, Dennis P Wall
The task of mapping neurological disorders in the human brain must be informed by multiple measurements of an individual's phenotype - neuroimaging, genomics, and behavior. We developed a novel meta-analytical approach to integrate disparate resources and generated transcriptional maps of neurological disorders in the human brain yielding a purely computational procedure to pinpoint the brain location of transcribed genes likely to be involved in either onset or maintenance of the neurological condition.
2015: AMIA ... Annual Symposium Proceedings
Nathaniel Roysden, Adam Wright
Mental health problems are an independent predictor of increased healthcare utilization. We created random forest classifiers for predicting two outcomes following a patient's first behavioral health encounter: decreased utilization by any amount (AUROC 0.74) and ultra-high absolute utilization (AUROC 0.88). These models may be used for clinical decision support by referring providers, to automatically detect patients who may benefit from referral, for cost management, or for risk/protection factor analysis...
2015: AMIA ... Annual Symposium Proceedings
Travis K Redd, Julie W Doberne, Daniel Lattin, Thomas R Yackel, Carl O Eriksson, Vishnu Mohan, Jeffrey A Gold, Joan S Ash, Michael F Chiang
Despite federal incentives for adoption of electronic health records (EHRs), surveys have shown that EHR use is less common among specialty physicians than generalists. Concerns have been raised that current-generation EHR systems are inadequate to meet the unique information gathering needs of specialists. This study sought to identify whether information gathering needs and EHR usage patterns are different between specialists and generalists, and if so, to characterize their precise nature. We found that specialists and generalists have significantly different perceptions of which elements of the EHR are most important and how well these systems are suited to displaying clinical information...
2015: AMIA ... Annual Symposium Proceedings
Bisakha Ray, Alexander Statnikov, Constantin Aliferis
Brain science is a frontier research area with great promise for understanding, preventing, and treating multiple diseases affecting millions of patients. Its key task of reconstructing neuronal brain connectivity poses unique Big Data Analysis challenges distinct from those in clinical or "-omics" domains. Our goal is to understand the strengths and limitations of reconstruction algorithms, measure performance and its determinants, and ultimately enhance performance and applicability. We devised a set of experiments in a well-controlled setting using an established gold-standard based on calcium fluorescence time series recordings of thousands of neurons sampled from a previously validated neuronal model of complex time-varying causal neuronal connections...
2015: AMIA ... Annual Symposium Proceedings
Fernanda Polubriaginof, Nicholas P Tatonetti, David K Vawdrey
Family history is considered a core element of clinical care. In this study we assessed the quality of family history data captured in an established commercial electronic health record (EHR) at a large academic medical center. Because the EHR had no centralized location to store family history information, it was collected as part of clinical notes in structured or free-text format. We analyzed differences between 10,000 free-text and 9,121 structured family history observations. Each observation was classified according to disease presence/absence and family member affected (e...
2015: AMIA ... Annual Symposium Proceedings
Matthew L Paulson, Chunhua Weng
Use of major eligibility criteria is a popular but unstudied folk practice for improving patient screening efficiency for clinical studies. This mixed-methods research study derived the desiderata for major eligibility criteria in breast cancer clinical trials. We randomly selected thirty interventional breast cancer clinical trials conducted at The New York-Presbyterian Hospital on the Columbia University Medical Center campus to create training (N=20) and testing (N=10) datasets. We utilized the Think-aloud protocol to gauge how clinical researchers identify and use major eligibility criteria to prescreen patients for clinical trials during an audio-recorded interview...
2015: AMIA ... Annual Symposium Proceedings
Mohammad Amin Morid, Siddhartha Jonnalagadda, Marcelo Fiszman, Kalpana Raja, Guilherme Del Fiol
OBJECTIVE: In a previous study, we investigated a sentence classification model that uses semantic features to extract clinically useful sentences from UpToDate, a synthesized clinical evidence resource. In the present study, we assess the generalizability of the sentence classifier to Medline abstracts. METHODS: We applied the classification model to an independent gold standard of high quality clinical studies from Medline. Then, the classifier trained on UpToDate sentences was optimized by re-retraining the classifier with Medline abstracts and adding a sentence location feature...
2015: AMIA ... Annual Symposium Proceedings
Mollie McKillop, Fernanda Polubriaginof, Chunhua Weng
Electronic Health Records (EHRs) hold great promise for secondary data reuse but have been reported to contain severe biases. The temporal characteristics of coding biases remain unclear. This study used a survival analysis approach to reveal temporal bias trends for coding acute diabetic conditions among 268 diabetes patients. For glucose-controlled ketoacidosis patients we found it took an average of 7.5 months for the incorrect code to be removed, while for glucose-controlled hypoglycemic patients it took an average of 9 months...
2015: AMIA ... Annual Symposium Proceedings
Daniel Magee, Rachel Beard, Matthew Scotch
The annual influenza vaccine is one of the most common public health interventions and is universally recommended for all individuals older than six months. Vaccine composition depends on viruses circulating over the past flu season and are estimated to be the most prevalent and representative strains in the current season. Here, we use clinical data outfitted with viral genetics to characterize confirmed influenza cases from the past two flu seasons and genetically compare them to the strains that they were vaccinated against that year...
2015: AMIA ... Annual Symposium Proceedings
Margaret K Linan, Davide Sottara, Robert R Freimuth
Pharmacogenomics (PGx) guidelines contain drug-gene relationships, therapeutic and clinical recommendations from which clinical decision support (CDS) rules can be extracted, rendered and then delivered through clinical decision support systems (CDSS) to provide clinicians with just-in-time information at the point of care. Several tools exist that can be used to generate CDS rules that are based on computer interpretable guidelines (CIG), but none have been previously applied to the PGx domain. We utilized the Unified Modeling Language (UML), the Health Level 7 virtual medical record (HL7 vMR) model, and standard terminologies to represent the semantics and decision logic derived from a PGx guideline, which were then mapped to the Health eDecisions (HeD) schema...
2015: AMIA ... Annual Symposium Proceedings
Kislaya Kunjan, Tammy Toscos, Ayten Turkcan, Brad N Doebbeling
Community health centers (CHCs) play a pivotal role in healthcare delivery to vulnerable populations, but have not yet benefited from a data warehouse that can support improvements in clinical and financial outcomes across the practice. We have developed a multidimensional clinic data warehouse (CDW) by working with 7 CHCs across the state of Indiana and integrating their operational, financial and electronic patient records to support ongoing delivery of care. We describe in detail the rationale for the project, the data architecture employed, the content of the data warehouse, along with a description of the challenges experienced and strategies used in the development of this repository that may help other researchers, managers and leaders in health informatics...
2015: AMIA ... Annual Symposium Proceedings
Andrew J King, Gregory F Cooper, Harry Hochheiser, Gilles Clermont, Shyam Visweswaran
Electronic medical records (EMRs) are capturing increasing amounts of data per patient. For clinicians to efficiently and accurately understand a patient's clinical state, better ways are needed to determine when and how to display EMR data. We built a prototype system that records how physicians view EMR data, which we used to train models that predict which EMR data will be relevant in a given patient. We call this approach a Learning EMR (LEMR). A physician used the prototype to review 59 intensive care unit (ICU) patient cases...
2015: AMIA ... Annual Symposium Proceedings
Logan Kendall, Sonali R Mishra, Ari Pollack, Barry Aaronson, Wanda Pratt
Despite growing use of patient-facing technologies such as patient portals to address information needs for outpatients, we understand little about how patients manage information and use information technologies in an inpatient context. Based on hospital observations and responses to an online questionnaire from previously hospitalized patients and caregivers, we describe information workspace that patients have available to them in the hospital and the information items that patients and caregivers rate as important and difficult to access or manage while hospitalized...
2015: AMIA ... Annual Symposium Proceedings
Yi-Chin Kato-Lin, Rema Padman, Julie Downs, Vibhanshu Abhishek
Mobile apps have great potential to deliver promising interventions to engage consumers and change their health-related behaviors, such as healthy eating. Currently, the interventions for promoting healthy eating are either too onerous to keep consumers engaged or too restrictive to keep consumers connected with healthcare professionals. In addition, while social media allows individuals to receive information from many sources, it is unclear how peer support interacts with professional support in the context of such interventions...
2015: AMIA ... Annual Symposium Proceedings
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