Phylogeography is a field that focuses on the geographical lineages of species such as vertebrates or viruses. Here, geographical data, such as location of a species or viral host is as important as the sequence information extracted from the species. Together, this information can help illustrate the migration of the species over time within a geographical area, the impact of geography over the evolutionary history, or the expected population of the species within the area. Molecular sequence data from NCBI, specifically GenBank, provide an abundance of available sequence data for phylogeography. However, geographical data is inconsistently represented and sparse across GenBank entries. This can impede analysis and in situations where the geographical information is inferred, and potentially lead to erroneous results. In this paper, we describe the current state of geographical data in GenBank, and illustrate how automated processing techniques such as named entity recognition, can enhance the geographical data available for phylogeographic studies.
Major Depressive Disorder (MDD) and Posttraumatic Stress Disorder (PTSD) are highly prevalent illnesses, but the literature suggests they are under-detected and suboptimally managed by primary care practitioners (PCPs). In this paper, we propose and use an evaluation method, using digitally simulated patients (avatars) to evaluate the diagnostic and therapeutic reasoning of PCPs and compared it to the traditional use of paper-based cases. Verbal (think-aloud) protocols were captured in the context of a diagnostic and therapeutic reasoning task. Propositional and semantic representational analysis of simulation data during evaluation, showed specific deficiencies in PCP reasoning, suggesting a promise of this technology in training and evaluation in mental health. Avatars are flexible and easily modifiable and are also a cost-effective and easy-to-disseminate educational tool.
The Phoenix Children’s Hospital (PCH) Inflammatory Bowel Disease (IBD) Clinic provides care for nearly 500 patients. As a group, PCH is part of the ImproveCareNow (ICN) network—a collaboration of over 100 centers worldwide to improve IBD care. Patient care has followed ICN guidelines including a weekly pre-visit planning (PVP) session. PVP is a time intensive process of manual chart review and data gathering for upcoming clinic patients. To improve this process and patient care, our group created a real-time IBD dashboard. OBJECTIVES: The aims of the dashboard were to identify and validate our patient population, improve efficiency by automating data gathering for PVP, and create a visual representation . Secondary aim, was to optimize processes including documentation, order entry and timely follow-up. METHODS: Data is sourced from the Allscripts electronic medical record (EMR). Data retrieval is contingent upon documentation. Our population of patients with IBD was identified based on a charted ICD-10 diagnosis of CD, UC or IC. PCH has a data warehouse of orders, results, Admission-Discharge-Transfer documentation, and flowsheets from the EMR and external data sources. Data is harvested and hosted using Microsoft Power BI for live review at weekly PVP. Once desired data points were hosted, focus was on process improvement (proper documentation, follow-up orders, and patient visits every 200 days). RESULTS: The dashboard hosts patients seen within the last 200 days, provider follow-up order placement, and physician global assessment (PGA) since January 2021. The percent of patients with follow-up orders placed was 61% in 2021. With dashboard enhancements and data visibility, this improved to 99% as of October 17, 2022. Physician global assessment (PGA) was recorded in 81% of encounters in 2021. Our most recent documentation rate is 92% on October 17, 2022. Our group had seen 82% of patients within the 200 days in 2021. Currently we have seen 89% of patients within 200 days as of October 17, 2022 (of these 91% of patients with active disease have been seen). We have instituted a work-flow process with schedulers to ensure patients are contacted and scheduled and not transitioned or moved. Figure 1 Historical Data from 1/2021-10/2021 Figure 2 Current Data as of 10/17/2022 CONCLUSIONS: With time, the IBD dashboard has proven to be a powerful tool in improving process measures. Our hope is these improvements will lend themselves to improved patient outcomes. With the ability to view data in real time in an automated fashion, staff hours have been saved and reallocated to other patient care needs. With continuous review of the data and introduction of accountability, we continue to see improvement. We now have the capacity to add additional metrics to the dashboard and our this can be viewed as a proof of concept for use in other specialties and chronic disease states.
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