Jesse O. Wrenn

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Objective Although electronic notes have advantages compared to handwritten notes, they take longer to write and promote information redundancy in electronic health records (EHRs). We sought to quantify redundancy in clinical documentation by studying collections of physician notes in an EHR. Design and methods We implemented a retrospective design to(More)
OBJECTIVE: To refine the Physician Documentation Quality Instrument (PDQI) and test the validity and reliability of the 9-item version (PDQI-9). METHODS: Three sets each of admission notes, progress notes and discharge summaries were evaluated by two groups of physicians using the PDQI-9 and an overall general assessment: one gold standard group consisting(More)
Natural language processing, an important tool in biomedicine, fails without successful segmentation of words and sentences. Tokenization is a form of segmentation that identifies boundaries separating semantic units, for example words, dates, numbers and symbols, within a text. We sought to construct a highly generalizeable tokenization algorithm with no(More)
Clinical task, or "to-do" lists are a common element in the physician document known as signout. Such lists are used to capture and track patient care plan items, supporting daily workflow and collaborative patient management continuity across care transitions. While physician task lists have been shown to be important to patient safety, the tasks(More)
BACKGROUND The Infobutton Manager (IM) is an application that provides clinical users with context-specific links to health information resources. Usage of the first version (IM-1) suggested that the user interface was suboptimal. METHODS We conducted a laboratory-based observational study of IM-1, use, applied standard user interface design techniques to(More)
Signout is an unofficial clinical document used traditionally to facilitate patient handoff. Qualitative studies have suggested its importance in clinical care. We used a novel technique to quantify the use of signout by analyzing clinical information system logfiles. Viewing and editing events were collected for 1,677 unique patients admitted to our(More)
Predicting a patient's expected length of stay for an Emergency Department encounter is valuable to anticipate impending operational bottlenecks that may lead to diversion. We developed and validated an artificial neural network using data from >16,000 patients using clinical and operational parameters that are commonly available early during an encounter.(More)
BACKGROUND Educators need efficient and effective means to track students' clinical experiences to monitor their progress toward competency goals. AIM To validate an electronic scoring system that rates medical students' clinical notes for relevance to priority topics of the medical school curriculum. METHOD The Vanderbilt School of Medicine Core(More)
Competence is essential for health care professionals. Current methods to assess competency, however, do not efficiently capture medical students' experience. In this preliminary study, we used machine learning and natural language processing (NLP) to identify geriatric competency exposures from students' clinical notes. The system applied NLP to generate(More)
OBJECTIVE To develop an electronic health record that facilitates rapid capture of detailed narrative observations from clinicians, with partial structuring of narrative information for integration and reuse. DESIGN We propose a design in which unstructured text and coded data are fused into a single model called structured narrative. Each major clinical(More)