4,029 results match your criteria AMIA ... Annual Symposium proceedings. AMIA Symposium[Journal]


Analyzing Medication Error Reports in Clinical Settings: An Automated Pipeline Approach.

AMIA Annu Symp Proc 2018 5;2018:1611-1620. Epub 2018 Dec 5.

University of Texas Health Science Center at Houston, Houston, TX, USA.

Medication error is a severe patient safety event in the United States. Medication error reports collected by Patient Safety Organizations provide an opportunity to analyze and learn from previous errors. However, the current workflow of analyzing the error reports is labor-intensive and time-consuming. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371341PMC
December 2018

Computable Eligibility Criteria through Ontology-driven Data Access: A Case Study of Hepatitis C Virus Trials.

AMIA Annu Symp Proc 2018 5;2018:1601-1610. Epub 2018 Dec 5.

University of Florida, Gainesville, FL, USA.

The increasing adoption of electronic health record (EHR) systems and proliferation of clinical data offer unprecedented opportunities for cohort identification to accelerate patient recruitment. However, the effort required to translate trial eligibility criteria to the correct cohort identification queries for clinical investigators is substantial, at least in part due to the lack of clear definitions in both the free-text eligibility criteria and the data models used to structure the available data elements in target patient databases. We propose to adopt an ontology-driven data access approach that generates formal representations of the connections between the entities in eligibility criteria and the available data elements to (1) narrow the semantic gap between researchers' cohort identification needs and the underlying database nuances, and (2) render the eligibility criteria computable. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371316PMC
December 2018

Learning When Communications Between Healthcare Providers Indicate Hormonal Therapy Medication Discontinuation.

AMIA Annu Symp Proc 2018 5;2018:1591-1600. Epub 2018 Dec 5.

Vanderbilt University Medical Center, Nashville, Tennessee, USA.

Hormonal therapy is an effective yet challenging long-term treatment for patients with hormone receptor positive breast cancer. Understanding what factors indicate discontinuation of a recommended hormonal therapy medication can help improve treatment experience. To date, studies on medication discontinuation have focused on patient information gathered through questionnaires, structured electronic medical records and online discussion boards. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371302PMC
December 2018
1 Read

Toward Reporting Support and Quality Assessment for Learning from Reporting: A Necessary Data Elements Model for Narrative Medication Error Reports.

AMIA Annu Symp Proc 2018 5;2018:1581-1590. Epub 2018 Dec 5.

School of Biomedical Informatics, University of Texas Health Science Center at Houston, Texas, USA.

To understand and prevent medication errors, spontaneous reporting systems are developed and implemented to aggregate medication error reports for root cause analysis (RCA). Despite of the rich relational information in medication error reports, low quality, especially incompleteness, impedes effective utilization of the reports for analyzing and learning. The lack of a completeness evaluation tool for narrative medication error reports is a barrier to improving the quality of reports. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371327PMC
December 2018
6 Reads

Visual Explanations From Deep 3D Convolutional Neural Networks for Alzheimer's Disease Classification.

AMIA Annu Symp Proc 2018 5;2018:1571-1580. Epub 2018 Dec 5.

Dept. of Computer & Information Science & Engineering, University of Florida, Gainesville, FL 32611, USA,

We develop three efficient approaches for generating visual explanations from 3D convolutional neural networks (3D-CNNs) for Alzheimer's disease classification. One approach conducts sensitivity analysis on hierarchical 3D image segmentation, and the other two visualize network activations on a spatial map. Visual checks and a quantitative localization benchmark indicate that all approaches identify important brain parts for Alzheimer's disease diagnosis. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371279PMC
December 2018

Approaches to Link Geospatially Varying Social, Economic, and Environmental Factors with Electronic Health Record Data to Better Understand Asthma Exacerbations.

AMIA Annu Symp Proc 2018 5;2018:1561-1570. Epub 2018 Dec 5.

Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA, USA.

Electronic health record (EHR)-derived data has become an invaluable resource for biomedical research, but is seldom used for the study of the health impacts of social and environmental factors due in part to the unavailability of relevant variables. We describe how EHR-derived data can be enhanced via linking of external sources of social, economic and environmental data when patient-related geospatial information is available, and we illustrate an approach to better understand the geospatial patterns of asthma exacerbation rates in Philadelphia. Specifically, we relate the spatial distribution of asthma exacerbations observed in EHR-derived data to that of known and potential risk factors (i. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371292PMC
December 2018
5 Reads

Clinical text annotation - what factors are associated with the cost of time?

AMIA Annu Symp Proc 2018 5;2018:1552-1560. Epub 2018 Dec 5.

School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA.

Building high-quality annotated clinical corpora is necessary for developing statistical Natural Language Processing (NLP) models to unlock information embedded in clinical text, but it is also time consuming and expensive. Consequently, it important to identify factors that may affect annotation time, such as syntactic complexity of the text- to-be-annotated and the vagaries of individual user behavior. However, limited work has been done to understand annotation of clinical text. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371268PMC
December 2018

Identification of Rare Adverse Events with Year-varying Reporting Rates for FLU4 Vaccine in VAERS.

AMIA Annu Symp Proc 2018 5;2018:1544-1551. Epub 2018 Dec 5.

Perelman School of Medicine, The University of Pennsylvania, Philadelphia, PA, USA.

In 2012, a new influenza vaccine - FLU4 was first licensed in the US. FLU4 is a quadrivalent flu vaccine, which can protect against four flu viruses. Compared to FLU and FLU3, FLU4 gives broader protection against the flu viruses. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371315PMC
December 2018
7 Reads

FABLE: A Semi-Supervised Prescription Information Extraction System.

AMIA Annu Symp Proc 2018 5;2018:1534-1543. Epub 2018 Dec 5.

George Mason University, Fairfax, Virginia, USA.

Prescription information is an important component of electronic health records (EHRs). This information contains detailed medication instructions that are crucial for patients' well-being and is often detailed in the narrative portions of EHRs. As a result, narratives of EHRs need to be processed with natural language processing (NLP) methods that can extract medication and prescription information from free text. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371278PMC
December 2018

A Frame-Based NLP System for Cancer-Related Information Extraction.

AMIA Annu Symp Proc 2018 5;2018:1524-1533. Epub 2018 Dec 5.

School of Biomedical Informatics The University of Texas Health Science Center at Houston Houston, TX, USA.

We propose a frame-based natural language processing (NLP) method that extracts cancer-related information from clinical narratives. We focus on three frames: cancer diagnosis, cancer therapeutic procedure, and tumor description. We utilize a deep learning-based approach, bidirectional Long Short-term Memory (LSTM) Conditional Random Field (CRF), which uses both character and word embeddings. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371330PMC
December 2018
1 Read

Communication Technology Use and Preferences for Pregnant Women and Their Caregivers.

AMIA Annu Symp Proc 2018 5;2018:1515-1523. Epub 2018 Dec 5.

Vanderbilt University Medical Center, Nashville, TN.

The rapid evolution of communication technologies has created new ways for healthcare consumers to manage their health. In a mixed-methods study, we examined technology use and willingness to use in pregnant women and caregivers, using surveys and semi-structured interviews. Most participants had used text messaging, automated phone calls, Skype/FaceTime, social media, and online discussion forums. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371273PMC
December 2018

Incorporating Knowledge-Driven Insights into a Collaborative Filtering Model to Facilitate the Differential Diagnosis of Rare Diseases.

AMIA Annu Symp Proc 2018 5;2018:1505-1514. Epub 2018 Dec 5.

Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.

Rare diseases, although individually rare, collectively affect one in ten Americans. Because of their rarity, patients with rare diseases are typically left misdiagnosed or undiagnosed, which leads to a prolonged medical journey. The diagnosis pathway of a rare disease is highly dependent on the associated clinical phenotypes, i. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371266PMC
December 2018

Identifying Cases of Metastatic Prostate Cancer Using Machine Learning on Electronic Health Records.

AMIA Annu Symp Proc 2018 5;2018:1498-1504. Epub 2018 Dec 5.

Department of Biomedical Informatics, Stanford School of Medicine, CA.

Cancer stage is rarely captured in structured form in the electronic health record (EHR). We evaluate the performance of a classifier, trained on structured EHR data, in identifying prostate cancer patients with metastatic disease. Using EHR data for a cohort of 5,861 prostate cancer patients mapped to the Observational Health Data Sciences and Informatics (OHDSI) data model, we constructed feature vectors containing frequency counts of conditions, procedures, medications, observations and laboratory values. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371284PMC
December 2018
1 Read

When an Alert is Not an Alert: A Pilot Study to Characterize Behavior and Cognition Associated with Medication Alerts.

AMIA Annu Symp Proc 2018 5;2018:1488-1497. Epub 2018 Dec 5.

University of Utah, Department of Biomedical Informatics, Salt Lake City, Utah.

. Preventable adverse drug events are a significant patient-safety concern, yet most medication alerts are disregarded. Pharmacists encounter the highest number of medication alerts and likely have developed behaviors to cope with alerting inefficiencies. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371356PMC
December 2018

Systematic Literature Review of Prescription Drug Monitoring Programs.

AMIA Annu Symp Proc 2018 5;2018:1478-1487. Epub 2018 Dec 5.

Arizona Osteopathic Medical Association, Phoenix, Arizona.

Prescription opioid abuse has become a serious national problem. To respond to the opioid epidemic, states have implemented prescription drug monitoring programs (PDMPs) to monitor and reduce opioid abuse. We conducted a systematic literature review to better understand the PDMP impact on reducing opioid abuse, improving prescriber practices, and how EHR integration has impacted PDMP usability. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371270PMC
December 2018
1 Read

Low Screening Rates for Diabetes Mellitus Among Family Members of Affected Relatives.

AMIA Annu Symp Proc 2018 5;2018:1471-1477. Epub 2018 Dec 5.

Value Institute, NewYork-Presbyterian Hospital, New York, NY.

Cardiovascular disease is the leading cause of death in the United States, and abnormal blood glucose is an important risk factor. Delayed diagnosis of diabetes mellitus can increase patients' morbidity. In an urban academic medical center with a large clinical data warehouse, we used a novel algorithm to identify 56,794 family members of diabetic patients that were eligible for disease screening. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371358PMC
December 2018

Evaluating the Impact of Uncertainty on Risk Prediction: Towards More Robust Prediction Models.

AMIA Annu Symp Proc 2018 5;2018:1461-1470. Epub 2018 Dec 5.

Medical Imaging & Informatics, Department of Radiological Sciences and Bioengineering.

Risk prediction models are crucial for assessing the pretest probability of cancer and are applied to stratify patient management strategies. These models are frequently based on multivariate regression analysis, requiring that all risk factors be specified, and do not convey the confidence in their predictions. We present a framework for uncertainty analysis that accounts for variability in input values. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371325PMC
December 2018

The Sublanguage of Clinical Problem Lists: A Corpus Analysis.

AMIA Annu Symp Proc 2018 5;2018:1451-1460. Epub 2018 Dec 5.

Department of Health Sciences Research, Mayo Clinic, Rochester, MN.

Summary-level clinical text is an important part of the overall clinical record as it provides a condensed and efficient view into the issues pertinent to the patient, or their "problem list." These problem lists contain a wealth of information pertaining to the patient's history as well as current state and well-being. In this study, we explore the structure of these problem list entries both grammatically and semantically in an attempt to learn the specialized rules, or "sublanguage" that governs them. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371258PMC
December 2018

Assessing Information Congruence of Documented Cardiovascular Disease between Electronic Dental and Medical Records.

AMIA Annu Symp Proc 2018 5;2018:1442-1450. Epub 2018 Dec 5.

Indiana University School of Dentistry, Indianapolis, IN.

Dentists are more often treating patients with Cardiovascular Diseases (CVD) in their clinics; therefore, dentists may need to alter treatment plans in the presence of CVD. However, it's unclear to what extent patient-reported CVD information is accurately captured in Electronic Dental Records (EDRs). In this pilot study, we aimed to measure the reliability of patient-reported CVD conditions in EDRs. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371326PMC
December 2018

Identifying Key Players in the Care Process of Patients with Diabetes Using Social Network Analysis and Administrative Data.

AMIA Annu Symp Proc 2018 5;2018:1435-1441. Epub 2018 Dec 5.

School of Medicine, Indiana University, West Lafayette, IN.

Determining networks of healthcare providers quantitatively can identify impactful care processes that improve health outcomes for a high-risk populations such as elderly people with multiple chronic conditions. By applying social network analysis to health claim data of a large university in the Midwest, we measured healthcare provider networks of patients with diabetes for two consecutive years. Networks were built based on the assumption that having common patients may indicate potential working relationships between providers. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371373PMC
December 2018
1 Read

Must We Bust the Trust?: Understanding How the Clinician-Patient Relationship Influences Patient Engagement in Safety.

AMIA Annu Symp Proc 2018 5;2018:1425-1434. Epub 2018 Dec 5.

University of Washington, Seattle, WA.

Although patients desire safe care, they are reluctant to perform safety-related behaviors when they worry it could harm the relationships they have with clinicians. This influence of the clinician-patient relationship on patient engagement in safety is poorly understood, and most patient-facing safety interventions ignore its influence, focusing instead on helping patients access information about their care and report errors. We conducted semi-structured interviews with hospitalized patients to uncover their needs for patient-facing information systems that could help them prevent medical errors. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371248PMC
December 2018

Trust and Sharing in an Interprofessional Environment: A Thematic Analysis From Child Development Support Work in the Community.

AMIA Annu Symp Proc 2018 5;2018:1415-1424. Epub 2018 Dec 5.

Biomedical Informatics and Medical Education, University of Washington, Seattle, WA.

Health information technology (HIT) could aid collaboration in the complex, interprofessional space of child development. Trust between stakeholders is necessary to support collaboration, but extant research provides little guidance on designing HIT that promotes trust within interprofessional collaborations. We analyzed interview data obtained from a heterogeneous group of stakeholders (n = 46) including parents and various service providers to explore trust relationships in the child development space. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371242PMC
December 2018
1 Read

Utility of General and Specific Word Embeddings for Classifying Translational Stages of Research.

AMIA Annu Symp Proc 2018 5;2018:1405-1414. Epub 2018 Dec 5.

NYU Langone Health, New York, NY, USA.

Conventional text classification models make a bag-of-words assumption reducing text into word occurrence counts per document. Recent algorithms such as word2vec are capable of learning semantic meaning and similarity between words in an entirely unsupervised manner using a contextual window and doing so much faster than previous methods. Each word is projected into vector space such that similar meaning words such as "strong" and "powerful" are projected into the same general Euclidean space. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371342PMC
December 2018

Using Neural Multi-task Learning to Extract Substance Abuse Information from Clinical Notes.

AMIA Annu Symp Proc 2018 5;2018:1395-1404. Epub 2018 Dec 5.

University of Washington, Seattle, WA.

Substance abuse carries many negative health consequences. Detailed information about patients' substance abuse history is usually captured in free-text clinical notes. Automatic extraction of substance abuse information is vital to assess patients' risk for developing certain diseases and adverse outcomes. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371261PMC
December 2018

Secondary Use of Electronic Health Record Data for Prediction of Outpatient Visit Length in Ophthalmology Clinics.

AMIA Annu Symp Proc 2018 5;2018:1387-1394. Epub 2018 Dec 5.

Departments of Medical Informatics and Clinical Epidemiology, OHSU, Portland, OR.

Electronic health record systems have dramatically transformed the process of medical care, but one challenge has been increased time requirements for physicians. In this study, we address this challenge by developing and validating analytic models for predicting patient encounter length based on secondary EHR data. Key findings from this study are: (1) Secondary use of EHR data may be captured to predict provider interaction time with patients; (2) Modeling results using secondary data may provide more accurate predictions of provider interaction time than an expert provide; (3) These findings suggest that secondary use of EHR data may be used to develop effective customized scheduling methods to improve clinical efficiency. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371379PMC
December 2018

Balancing Performance and Interpretability: Selecting Features with Bootstrapped Ridge Regression.

AMIA Annu Symp Proc 2018 5;2018:1377-1386. Epub 2018 Dec 5.

Vanderbilt University Medical Center, Nashville, TN.

Informctticists sometimes attempt to predict chronic healthcare events that are not fully understood. The resulting models often incorporate copious numbers of predictors derived across diverse datasets. This approach may yield desirable performance characteristics, but it sacrifices interpretability and portability. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371276PMC
December 2018

Mining clinical big data for drug safety: Detecting inadequate treatment with a DNA sequence alignment algorithm.

AMIA Annu Symp Proc 2018 5;2018:1368-1376. Epub 2018 Dec 5.

INSERM, UMR 1099, Rennes, F-35000, France.

Health data mining can bring valuable information for drug safety activities. We developed a visual analytics tool to find specific clinical event sequences within the data contained in a clinical data warehouse. To this aim, we adapted the Smith-Waterman DNA sequence alignment algorithm to retrieve clinical event sequences with a temporal pattern from the electronic health records included in a clinical data warehouse. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371253PMC
December 2018

Integrated machine learning pipeline for aberrant biomarker enrichment (i-mAB): characterizing clusters of differentiation within a compendium of systemic lupus erythematosus patients.

AMIA Annu Symp Proc 2018 5;2018:1358-1367. Epub 2018 Dec 5.

Department of Biostatistics, Epidemiology, and Informatics.

Clusters of differentiation () are cell surface biomarkers that denote key biological differences between cell types and disease state. CD-targeting therapeutic monoclonal antibodies () afford rich trans-disease repositioning opportunities. Within a compendium of systemic lupus erythematous () patients, we applied the Integrated machine learning pipeline for aberrant biomarker enrichment () to profile gene expression features affecting CD20, CD22 and CD30 gene aberrance. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371296PMC
December 2018

DrKnow: A Diagnostic Learning Tool with Feedback from Automated Clinical Decision Support.

AMIA Annu Symp Proc 2018 5;2018:1348-1357. Epub 2018 Dec 5.

School of Computing and Information Systems, Melbourne School of Engineering, University of Melbourne, Australia.

Providing medical trainees with effective feedback is critical to the successful development of their diagnostic reasoning skills. We present the design of DrKnow, a web-based learning application that utilises a clinical decision support system (CDSS) and virtual cases to support the development of problem-solving and decision-making skills in medical students. Based on the clinical information they request and prioritise, DrKnow provides personalised feedback to help students develop differential and provisional diagnoses at key decision points as they work through the virtual cases. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371235PMC
December 2018
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Integration of Transcriptomic Data Identifies Global and Cell-Specific Asthma-Related Gene Expression Signatures.

AMIA Annu Symp Proc 2018 5;2018:1338-1347. Epub 2018 Dec 5.

Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, PA, USA.

Over 140,000 transcriptomic studies performed in healthy and diseased cell and tissue types, at baseline and after exposure to various agents, are available in public repositories. Integrating results of transcriptomic datasets has been an attractive approach to identify gene expression signatures that are more robust than those obtained for individual datasets, especially datasets with small sample size. We developed Reproducible Analysis and Validation of Expression Data (RAVED), a pipeline that facilitates the creation of R Markdown reports detailing reproducible analysis of publicly available transcriptomic data, and used it to analyze asthma and glucocorticoid response microarray and RNA-Seq datasets. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371257PMC
December 2018
3 Reads

Re-Identification Risk in HIPAA De-Identified Datasets: The MVA Attack.

AMIA Annu Symp Proc 2018 5;2018:1329-1337. Epub 2018 Dec 5.

Department of Biomedical Informatics, Jacobs School of Medicine and Biomedical Sciences, State University of New York at Buffalo, Buffalo, NY.

We present a re-identification attack that uses indirect (non-HIPAA) identifiers to target a vulnerable subset of records de-identified to the HIPAA Safe Harbor standard, those involving motor vehicle accidents (MVAs). Documentation of an MVA in a patient note creates a significant risk to patient privacy through the MVA re-identification attack, with a relative risk of 537 compared to the general population. Patients in a significant MVA resulting in either permanent injury, hospitalization or death (for any victim) should have the accident location information omitted due to the significant risk of re-identification of HIPAA de-identified data. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371259PMC
December 2018

Using Demographic Factors and Comorbidities to Develop a Predictive Model for ICU Mortality in Patients with Acute Exacerbation COPD.

AMIA Annu Symp Proc 2018 5;2018:1319-1328. Epub 2018 Dec 5.

Alpert Medical School and Center for Biomedical Informatics, Brown University, Providence, RI.

Recognizing factors associated with mortality in patients admitted to the ICU with acute exacerbation of chronic obstructive pulmonary disease could reduce healthcare costs and improve end-of-life care. Previous studies have identified possible predictive variables, but analysis is lacking on the combined effect of demographic factors and comorbidities. Using the MIMIC-III database, this study examined factors associated with mortality in a model incorporating comorbidities, comorbidity indices, and demographic factors. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371239PMC
December 2018

Clinical Documentation in Electronic Health Record Systems: Analysis of Similarity in Progress Notes from Consecutive Outpatient Ophthalmology Encounters.

AMIA Annu Symp Proc 2018 5;2018:1310-1318. Epub 2018 Dec 5.

Medical Informatics & Clinical Epidemiology.

Content importing technology enables duplication of large amounts of clinical text in electronic health record (EHR) progress notes. It can be difficult to find key sections such as Assessment and Plan in the resulting note. To quantify the extent of text length and duplication, we analyzed average ophthalmology note length and calculated novelty of each major note section (Subjective, Objective, Assessment, Plan, Other). Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371381PMC
December 2018

Disease comorbidity-guided drug repositioning: a case study in schizophrenia.

AMIA Annu Symp Proc 2018 5;2018:1300-1309. Epub 2018 Dec 5.

Department of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland OH 44106.

The key to any computational drug repositioning is the availability of relevant data in machine-understandable format. While large amount of genetic, genomic and chemical data are publicly available, large-scale higher-level disease and drug phenotypic data are limited. We recently constructed a large-scale disease-comorbidity relationship knowledge base (dCombKB) and a comprehensive drug-treatment relationship knowledge base (TreatKB) from 21 million biomedical research articles and other resources. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371343PMC
December 2018

Recovery in My Lens: A Study on Stroke Vlogs.

AMIA Annu Symp Proc 2018 5;2018:1300-1309. Epub 2018 Dec 5.

Department of Informatics, University of California, Irvine, Irvine, California, USA.

Stroke is a chronic condition and a leading cause of disability. After hospital discharge, patients need to transition into home-based rehabilitation, a long and distressful process. However, they are often ill-prepared to manage recovery at home; and many are socially isolated. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371286PMC
December 2018
3 Reads

Defining and Developing a Generic Framework for Monitoring Data Quality in Clinical Research.

AMIA Annu Symp Proc 2018 5;2018:1300-1309. Epub 2018 Dec 5.

School of Medicine, Faculty of Science, Medicine and Health, University of Wollongong, Wollongong NSW 2522, Australia.

Evidence for the need for high data quality in clinical research is well established. The rigor of clinical research conclusions rely heavily on good quality data, which relies on good documentation practices. Little attention has been given to clear guidelines and definitions to monitor data quality. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371251PMC
December 2018

Retrospective analysis of health claims to evaluate pharmacotherapies with potential for repurposing: Association of bupropion and stimulant use disorder remission.

AMIA Annu Symp Proc 2018 5;2018:1292-1299. Epub 2018 Dec 5.

University of Kentucky, Lexington, KY, USA.

Drug repurposing is the identification of novel indication(s) for existing medications. Health claims data provide a burgeoning resource to evaluate pharmacotherapies with repurposing potential. To demonstrate a workflow for drug repurposing using claims data, we assessed the association between prescription of bupropion and stimulant use disorder (StUD) remission. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371318PMC
December 2018
4 Reads

Exploring the Design of an Inpatient Peer Support Tool: Views of Adult Patients.

AMIA Annu Symp Proc 2018 5;2018:1282-1291. Epub 2018 Dec 5.

University of Washington, Seattle, WA.

Despite wide recognition of the value, expertise, and support that patient-peers provide in a variety of health contexts, mechanisms to design and enable peer support in the inpatient setting have not been sufficiently explored. To better understand the opportunities for an inpatient peer support tool, we surveyed 100 adult patients and caregivers, and conducted follow-up, semi-structured interviews with 15 adult patients. In this paper, we describe five key peer support needs that our adult patient participants expressed: (1) adjusting to the hospital environment, (2) understanding and normalizing medical care, (3) communicating with providers, (4) reporting and preventing medical errors, and (5) empowering peers. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371245PMC
December 2018

Providers' Perspectives on Sharing Health Information through Acute Care Patient Portals.

AMIA Annu Symp Proc 2018 5;2018:1273-1281. Epub 2018 Dec 5.

Department of Biomedical Informatics, Columbia University, New York, NY.

Engaging healthcare providers in acute care patient portal implementation is critical to ensure productive use. However, few studies have assessed provider's perceptions of an acute care portal after implementation. In this study, we surveyed 63 nurses, physicians, and physician assistants following a 3-year randomized trial of an acute care portal. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371328PMC
December 2018
5 Reads

Exploring Older Adults' Strengths, Problems, and Wellbeing Using De-identified Electronic Health Record Data.

AMIA Annu Symp Proc 2018 5;2018:1263-1272. Epub 2018 Dec 5.

School of Nursing, University of Minnesota, Minneapolis, MN 55455.

As new data sources including individuals' strengths emerge in electronic health records, such data provide whole-person oriented information to generate integrated knowledge for person-centered practice. The purpose of this study is to describe older adults' strengths and problems within a wellbeing context documented by the Omaha System. The Wellbeing Model is employed as a conceptual framework for wellbeing and is operationalized by the Omaha System Problem Classification Scheme. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371293PMC
December 2018
6 Reads

Improving breast cancer risk prediction by using demographic risk factors, abnormality features on mammograms and genetic variants.

AMIA Annu Symp Proc 2018 5;2018:1253-1262. Epub 2018 Dec 5.

University of Wisconsin Department of Radiology, Madison, WI.

The predictive capability of combining demographic risk factors, germline genetic variants, and mammogram abnormality features for breast cancer risk prediction is poorly understood. We evaluated the predictive performance of combinations of demographic risk factors, high risk single nucleotide polymorphisms (SNPs), and mammography features for women recommended for breast biopsy in a retrospective case-control study (n = 768) with four logistic regression models. The AUC of the baseline demographic features model was 0. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371301PMC
December 2018
6 Reads

The Use of General Health Apps Among Users with Specific Conditions: Why College Women with Disordered Eating Adopt Food Diary Apps.

AMIA Annu Symp Proc 2018 5;2018:1243-1252. Epub 2018 Dec 5.

University of California, Irvine, Irvine, California, USA.

There is a myriad of mobile health applications designed to address a variety of health conditions. While these apps hold significant promise for the management of these conditions, users sometimes turn to general health apps, rather than those designed with their specific condition in mind, which can lead to unmet needs and worsened conditions. We outline one example by focusing on college women with disordered eating behaviors and their use of general food diary apps, rather than eating disorder-specific apps. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371267PMC
December 2018
5 Reads

In Search of Vital Signs: A Comparative Study of EHR Documentation.

AMIA Annu Symp Proc 2018 5;2018:1233-1242. Epub 2018 Dec 5.

Department of Biomedical Informatics, Arizona State University, AZ, US.

Vital sign documentation is an essential part of perioperative workflow. Health information technology can introduce complexity into all facets of documentation and burden clinicians with high cognitive load. The Mayo Clinic enterprise is in the process of documenting current EHR-mediated workflow prior to a system-wide EHR conversion. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371263PMC
December 2018

Deep Learning for Image Quality Assessment of Fundus Images in Retinopathy of Prematurity.

AMIA Annu Symp Proc 2018 5;2018:1224-1232. Epub 2018 Dec 5.

Medical Informatics & Clinical Epidemiology, and.

Accurate image-based medical diagnosis relies upon adequate image quality and clarity. This has important implications for clinical diagnosis, and for emerging methods such as telemedicine and computer-based image analysis. In this study, we trained a convolutional neural network (CNN) to automatically assess the quality of retinal fundus images in a representative ophthalmic disease, retinopathy of prematurity (ROP). Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371336PMC
December 2018
3 Reads

Using Wayfinding Data to Understand Patient Travel Within a Medical Center.

AMIA Annu Symp Proc 2018 5;2018:1216-1223. Epub 2018 Dec 5.

Vanderbilt University, Nashville, TN.

Navigating through parking lots, public areas, and hallways is a stressful task for patients visiting large medical centers. Little is known about the patient experience from when they arrive at a medical center to when they check-in at their clinic. In a pilot study, we used requests for wayfinding directions from a mobile application to form a network of patient movement through the Vanderbilt University Medical Center (VUMC). Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371236PMC
December 2018

Multi-Trajectory Modeling to Predict Acute Kidney Injury in Chronic Kidney Disease Patients.

AMIA Annu Symp Proc 2018 5;2018:1196-1205. Epub 2018 Dec 5.

The H. John Heinz III College of Information Systems and Public Policy.

Risk-stratifying chronic disease patients in real time has the potential to facilitate targeted interventions and improve disease management and outcomes. We apply group-based multi-trajectory modeling to risk stratify patients with chronic kidney disease (CKD) and its major complications into distinct trajectories of disease development and predict acute kidney injury (AKI), a serious, under-diagnosed outcome of CKD that is both preventable and treatable with early detection. Utilizing Electronic Health Record data of 1,947 patients, we identify eight risk groups with distinct trajectories and profiles. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371306PMC
December 2018
1 Read

Identifying Similar Non-Lattice Subgraphs in Gene Ontology based on Structural Isomorphism and Semantic Similarity of Concept Labels.

AMIA Annu Symp Proc 2018 5;2018:1186-1195. Epub 2018 Dec 5.

Department of Computer Science, University of Kentucky, Lexington, KY.

Non-Lattice Subgraphs (NLSs) are graph fragments of a terminology which violates the lattice property, a desirable property for a well-formed terminology. They have been proven to be useful in identifying inconsistencies in biomed-ical terminologies. Similar NLSs may denote similar inconsistencies that may suggest possibly similar remediations. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371383PMC
December 2018

Privacy-preserving biomedical data dissemination via a hybrid approach.

AMIA Annu Symp Proc 2018 5;2018:1176-1185. Epub 2018 Dec 5.

Dept. of Biomedical Informatics, University of California San Diego, La Jolla, CA, USA.

Sharing medical data can benefit many aspects of biomedical research studies. However, medical data usually contains sensitive patient information, which cannot be shared directly. Summary statistics, like histogram, are widely used in medical research which serves as a sanitized synopsis of the raw health dataset such as Electrical Health Records (EHR). Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371369PMC
December 2018
1 Read

Applying Blockchain Technology for Health Information Exchange and Persistent Monitoring for Clinical Trials.

AMIA Annu Symp Proc 2018 5;2018:1167-1175. Epub 2018 Dec 5.

Informatics Institute.

"Blockchain" is a distributed ledger technology originally applied in the financial sector. This technology ensures the integrity of transactions without third-party validation. Its functions of decentralized transaction validation, data provenance, data sharing, and data integration are a good fit for the needs of health information exchange and clinical trials. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371378PMC
December 2018
5 Reads

Overlapping Complex Concepts Have More Commission Errors, Especially in Intensive Terminology Auditing.

AMIA Annu Symp Proc 2018 5;2018:1157-1166. Epub 2018 Dec 5.

National Library of Medicine, Bethesda, MD, US.

SNOMED CT is a large, complex and widely-used terminology. Auditing is part of the life cycle of terminologies. A review of terminologies' content can identify two error categories: commission errors, such as an incorrect parent or attribute relationship, indicating errors in a concept's modeling, and omission errors, such as missing a parent or attribute relationship, representing incomplete modeling of a concept. Read More

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6371375PMC
December 2018
5 Reads