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111 results for “EHR”
Application of Economics & Social Psychology to Improve Opioid Prescribing Safety Trial 1: EHR Nudges
ClinicalTrials.gov study NCT04477304. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Data from: Assessing completeness of cancer family history in EHRs using genetically-defined kinships: a cross-sectional study
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Longitudinal trends of EHR concepts in pediatric patients
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Antibiotic Resistance Microbiology Dataset (ARMD): A resource for antimicrobial resistance from EHRs
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Machine learning feature data from EHR, labels, and estimates for next generation sequencing-based assay
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Ehre dem Bergmann - Bergmann Denkmal - Zwönitz
Ehre dem Bergmann - Bergmanndenkmal - Zwönitz Source: Objaverse 1.0 / Sketchfab
Generalizable EHR-R-REDCap pipeline for a national multi-institutional rare tumor patient registry
<p><strong>Objective</strong>: To develop a clinical informatics pipeline designed to capture large-scale structured EHR data for a national patient registry.</p> <p><strong>Materials and Methods</strong>: The EHR-R-REDCap pipeline is implemented using R-statistical software to remap and import structured EHR data into the REDCap-based multi-institutional Merkel Cell Carcinoma (MCC) Patient Registry using an adaptable data dictionary.</p> <p><strong>Results</strong>: Clinical laboratory data were extracted from EPIC Clarity across several participating institutions. Labs were transformed, remapped and imported into the MCC registry using the EHR labs abstraction (eLAB) pipeline. Forty-nine clinical tests encompassing 482,450 results were imported into the registry for 1,109 enrolled MCC patients. Data-quality assessment revealed highly accurate, valid labs. Univariate modeling was performed for labs at baseline on overall survival (N=176) using this clinical informatics pipeline.</p> <p><strong>Conclusion</strong>: We demonstrate feasibility of the facile eLAB workflow. EHR data is successfully transformed, and bulk-loaded/imported into a REDCap-based national registry to execute real-world data analysis and interoperability.</p>
EHR screen, test, and refer to HFMH DPP
<p>Objective: Determine if certified electronic health record technology (CEHRT) can be used to identify and refer patients with prediabetes to lifestyle change programs (LCPs) recognized by the National Diabetes Prevention Program (DPP).</p> <p>Materials and Methods: This pilot utilized a prediabetes registry, patient portal, and clinical decision support to increase referrals.</p> <p>Results: Data from 36 primary care providers showed 4,930 patients were eligible for DPP LCP, 293 referrals were generated, compared to 20 referrals in the baseline period, and 116 patients enrolled. Referral to enrollment conversion rates were 41% in the study period and 69% in the post-study 1-year period.</p> <p>Discussion: CEHRT functionalities can support systematic identification and management of prediabetes. The referral rate increased seven-fold compared to the baseline period, with high referral to enrollment conversion rates.</p> <p>Conclusions: CEHRT coupled with active provider engagement can serve as a tool to identify prediabetes patients and facilitate LCP referrals and enrollment.</p>
FIGURES 24–30 in Stephanodiscus Ehr. species from Holocene sediments in the Faiyum Depression (Middle Egypt)
FIGURES 24–30. Stephanodiscus galileensis, LM. Fig. 25. External convex valve note irregular spines and sub-marginal silica ring. Fig. 25. Internal convex valve with rimoportula arrowed. Fig. 26. Detail of same valve showing central area ring of fultoportulae with two or three satellite pores. Fig. 27. External concave valve with ring of spines and raised interfascicular ribs. Fig. 28. Internal concave valve showing ring of sub-marginal fultoportulae and rimoportulae (arrowed). Fig. 29. Similar showing detail of a rimoportula, a submarginal fultoportula with two satellite pores and marginal fultoportulae. Fig. 30. Detail of a sub-marginal fultoportula with three satellite pores and surrounding domed cribra. Scale bars = 10 µm (Figs 24, 25, 27, 28), 1 µm (Figs 26, 29), and 0.5 µm (Fig. 30).
FIGURES 15–18. Stephanodiscus neoaegypticus v. fekrii, SEM. Fig. 15. External valve with a convex central area. Fig. 16 in Stephanodiscus Ehr. species from Holocene sediments in the Faiyum Depression (Middle Egypt)
FIGURES 15–18. Stephanodiscus neoaegypticus v. fekrii, SEM. Fig. 15. External valve with a convex central area. Fig. 16. Internal valve showing two rimoportulae (arrowed). Fig. 17. Detail of internal marginal zone showing fultoportulae with either three or four satellite pores. Fig. 18. Internal central area fultoportula with two satellite pores. Scale bars = 2 µm (Fig. 15), 5 µm (Fig. 16), and 1 µm (Figs 17, 18).
FIGURE 31 in Stephanodiscus Ehr. species from Holocene sediments in the Faiyum Depression (Middle Egypt)
FIGURE 31. Size distributions for diatom valve diameters (see text). Fig. 31a: Stephanodiscus neoaegypticus sensu lato from material at 430 cm depth in core GARK1. Fig. 31b. Stephanodiscus galileensis Hakansson & Ehrlich from material at 1930 cm depth in core QARU9.
FIGURES 19–23 in Stephanodiscus Ehr. species from Holocene sediments in the Faiyum Depression (Middle Egypt)
FIGURES 19–23. Stephanodiscus galileensis, LM. Fig. 19. Convex valve showing a distinct sub-marginal hyaline ring in focus. Fig. 20. Similar showing marginal ring of spines and valve central area in focus. Fig. 21. Concave valve showing finer fascicle structure (see S. galileensis morphotype B, Hakansson & Locker 1987) and valve face fultoportulae (arrowed). Fig. 22. Similar showing valve central area in focus. Fig. 23. Similar, but valve is more strongly silicified. Scale bars = 5 µm (Figs 19–23).
FIGURES 3–8 in Stephanodiscus Ehr. species from Holocene sediments in the Faiyum Depression (Middle Egypt)
FIGURES 3–8. Stephanodiscus neoaegypticus, LM. Fig. 3. Valve showing an indistinct sub-marginal hyaline ring and broad interfascicular ribs. Fig. 4. Valve focused to show the valve face-mantle zone with occasional bifurcating interfascicular ribs (arrowed). Fig. 5. A strongly silicified valve. Fig. 6. A part dissolved valve with eroded margin and diminished interfascicular ribs. Figs 7–8. S. neoaegypticus v. fekrii LM. Fig. 7. Whole valve focused to show the broad interfascicular ribs and marginal bifurcations (arrowed). Fig. 8. The same whole valve (Fig. 7) focused to show the central area. Scale bars = 5 µm (Figs 3–8)
FIGURE 2 in Stephanodiscus Ehr. species from Holocene sediments in the Faiyum Depression (Middle Egypt)
FIGURE 2. Gross sediment stratigraphies of the three cores, QARU9, QARU10 and GARK1 (see text for sediment descriptions). Note the basal sands below finely laminated diatom marl sediment in QARU9 & 10.
FIGURES 9–14. Stephanodiscus neoaegypticus, SEM. Fig. 9. Iconotype, external valve showing small concentric convex undulation with out spines. Fig. 10 in Stephanodiscus Ehr. species from Holocene sediments in the Faiyum Depression (Middle Egypt)
FIGURES 9–14. Stephanodiscus neoaegypticus, SEM. Fig. 9. Iconotype, external valve showing small concentric convex undulation with out spines. Fig. 10. External valve showing small concentric concave undulation and external rimoportula opening (arrowed). Fig. 11. Internal valve showing sub-marginal rimoportulae (arrowed). Fig. 12. Detail of the same valve showing two sub-marginal rimoportulae and marginal ring fultoportulae. Fig. 13. Detail of the central ring of fultoportulae (each with two satellite pores). Stephanodiscus neoaegypticus v. fekrii SEM. Fig. 14. Iconotype, external valve with a concave central area, marginal ring of fultoportula apertures and external opening of a rimoportula (arrowed). Scale bars = 10 µm (Figs 9–11, 14), 1 µm (Fig. 12), and 2 µm (Fig. 13).
FIGURE 1 in Stephanodiscus Ehr. species from Holocene sediments in the Faiyum Depression (Middle Egypt)
FIGURE 1. Lake Qarun situated in northern part of the Faiyum Depression, Egypt. Three terrestrial sediment core locations are shown with QARU9 and 10 on the southern shore of the lake and GARK1 in the Gharak region of south west Faiyum. Note diatomite exposures are indicated to the west and northeast of the modern lake.
Evaluating the Effects of EHRs, P4P and Medical Home Redesign in the Hudson Valley
ClinicalTrials.gov study NCT00793065. IPD Sharing: Not stated. Countries: 1. Publications: 3.
EHR-based Patient Identification and Panel Management of Patients With Iron Deficiency Anemia
ClinicalTrials.gov study NCT05365308. IPD Sharing: NO. Countries: 1. Publications: 1.
Individualizing Antidepressant Treatment Using Pharmacogenomics and EHR-driven Clinical Decision Support
ClinicalTrials.gov study NCT03952494. IPD Sharing: NO. Countries: 1. Publications: 5.
Addressing Under-treatment and Health Equity in AS and MR Using an Integrated EHR Platform
ClinicalTrials.gov study NCT06099665. IPD Sharing: NO. Countries: 1. Publications: 0.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.