93 hasil untuk "Wilcox, Adam"
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Artikel Jurnal Teks lengkap
Advancing Decision Support Systems with Data, Informatics, and Learning Health Systems in a Post-Meaningful Use Era
The HITECH Act and Meaningful Use (MU) successfully drove widespread EHR adoption but largely missed the strategic goal of healthcare transformation. While EHRs are now ubiquitous, few institutions have transitioned to a true Learning Health System (LHS). To support achieving transformative impact…
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Reference Standards, Judges, and Comparison Subjects
Medical informatics systems are often designed to perform at the level of human experts. Evaluation of the performance of these systems is often constrained by lack of reference standards, either because the appropriate response is not known or because no simple appropriate response exists. Even…
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Sustaining the Effective Use of Health Care Data: A Message from the Editors
INTRODUCTION: Over the past decade, several initiatives have funded large projects to develop clinical research data infrastructures totaling several hundred million dollars. While most of this funding has ended or is expected to end soon, the projects themselves must struggle to continue…
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Mission and Sustainability of Informatics for Integrating Biology and the Bedside (i2b2)
INTRODUCTION: A visible example of a successfully disseminated research project in the healthcare space is Informatics for Integrating Biology and the Bedside, or i2b2. The project serves to provide the software that can allow a researcher to do direct, self-serve queries against the electronic…
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Simplified data science approach to extract social and behavioural determinants: a retrospective chart review
OBJECTIVES: We aim to extract a subset of social factors from clinical notes using common text classification methods. DESIGN: Retrospective chart review. SETTING: We collaborated with a local level I trauma hospital located in an underserved area that has a housing unstable patient population of…
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Assessing the Predictive and Analytics Capability of Electronic Clinical Data for High-Cost Patients
Hotspotting may prevent high healthcare costs surrounding a minority of patients when void of issues such as availability, completeness, and accessibility of information in electronic health records (EHRs). We performed a descriptive study using Barnes-Jewish Hospital patients to assess the…
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The Role of Domain Knowledge in Automating Medical Text Report Classification
Objective: To analyze the effect of expert knowledge on the inductive learning process in creating classifiers for medical text reports. Design: The authors converted medical text reports to a structured form through natural language processing. They then inductively created classifiers for medical…
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Using Personal Health Records for Automated Clinical Trials Recruitment: the ePaIRing Model
We describe the development of a model describing the use of patient information to improve patient recruitment in clinical trials. This model, named ePaIRing (electronic Participant Identification and Recruitment Model) describes variations in how information flows between stakeholders, and how…
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Knowledge Discovery Using the Electronic Medical Record
Knowledge discovery and data mining is one of the most promising areas of current informatics research. However, real successes of clinical data mining have mainly been limited to algorithms research, to specific prospectively created datasets, or to administrative databases requiring manual…
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Natural Language as a Tool in the Development of a Controlled Vocabulary
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The Effect of Longitudinal EMR Access on Laboratory Ordering
A longitudinal electronic medical record (EMR) allows physicians to access laboratory results in the context of the patient’s medical history. Daily lab order volumes were tracked for physicians with access to an EMR and physicians with no EMR access to assess whether physicians with EMR access…
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A Review of Predictive Analytics Solutions for Sepsis Patients
Background Early detection and efficient management of sepsis are important for improving health care quality, effectiveness, and costs. Due to its high cost and prevalence, sepsis is a major focus area across institutions and many studies have emerged over the past years with different models or…
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Looking Forward to AI and Medicine: Where Are We, and Where Are We Going?
Artificial intelligence (AI) has emerged as a significant area of interest in medicine, with the potential to influence various aspects of health care. However, the real benefits of applications of AI to medicine often become obscured by the considerable attention, and hype, around its…
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Large Language Models for Efficient Medical Information Extraction
Extracting valuable insights from unstructured clinical narrative reports is a challenging yet crucial task in the healthcare domain as it allows healthcare workers to treat patients more efficiently and improves the overall standard of care. We employ ChatGPT, a Large language model (LLM), and…
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The effect of sample size and disease prevalence on supervised machine learning of narrative data.
This paper examines the independent effects of outcome prevalence and training sample sizes on inductive learning performance. We trained 3 inductive learning algorithms (MC4, IB, and Naïve-Bayes) on 60 simulated datasets of parsed radiology text reports labeled with 6 disease states. Data sets…
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Comparisons among Health Behavior Surveys: Implications for the Design of Informatics Infrastructures That Support Comparative Effectiveness Research
INTRODUCTION: To address the electronic health data fragmentation that is a methodological limitation of comparative effectiveness research (CER), the Washington Heights Inwood Informatics Infrastructure for Comparative Effectiveness Research (WICER) project is creating a patient-centered research…
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Security Approaches in Using Tablet Computers for Primary Data Collection in Clinical Research
Next-generation tablets (iPads and Android tablets) may potentially improve the collection and management of clinical research data. The widespread adoption of tablets, coupled with decreased software and hardware costs, has led to increased consideration of tablets for primary research data…
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Could Patient Self-reported Health Data Complement EHR for Phenotyping?
Electronic health records (EHRs) have been used as a valuable data source for phenotyping. However, this method suffers from inherent data quality issues like data missingness. As patient self-reported health data are increasingly available, it is useful to know how the two data sources compare…
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Minimizing electronic health record patient-note mismatches
We measured the prevalence (or rate) of patient-note mismatches (clinical notes judged to pertain to another patient) in the electronic medical record. The rate ranged from 0.5% (95% CI 0.2% to 1.7%) before a pop-up window intervention to 0.3% (95% CI 0.1% to 1.1%) after the intervention…