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115
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ShareScore release 0.7.1
Dataset results
115 results for “electronic health records”
Ambulatory physicians' electronic health record self-efficacy
<p><strong>Objective:</strong> To assess ambulatory providers' confidence in learning about and using the electronic health record (EHR).</p> <p><strong>Materials and Methods:</strong> Providers were administered an EHR skills self-assessment survey.</p> <p><strong>Results:</strong> 71 providers participated. Only 35% of respondents felt that they had strong EHR skills, 92% felt confident that they could learn new skills, and 90% felt they could improve with practice. 45% of faculty physicians felt confident that they could use the EHR in a time-efficient manner and 52% felt could keep up with advances but 16% felt apprehensive about using the EHR. 94% of faculty would welcome opportunities to learn more.</p> <p><strong>Discussion:</strong> Most providers viewed using the EHR as a clinical skill they could master with training and practice.</p> <p><strong>Conclusion:</strong> Physicians may be engaged by EHR training programs that focus on the use of the EHR as a clinical skill. This work has informed new training programs at our institution.</p>
Data for "Checklist and guidance on creating codelists for electronic health records research"
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PRescribing INterventions for Chronic Pain Via the Electronic Health Record Study - Opioid-Naive Population
ClinicalTrials.gov study NCT04601493. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Blood Glucose Monitoring in Electronic Health Records
ClinicalTrials.gov study NCT03542487. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Electronic Health Record (EHR)-Based Intervention for Gastroesophageal Reflux Disease (GERD) and Chronic Non-steroidal Anti-inflammatory Drug (NSAID) Use
ClinicalTrials.gov study NCT00691171. IPD Sharing: Not stated. Countries: 0. Publications: 1.
Study Based on Electronic Health RecOrds to Identify Patients at High-risk of Fabry DiseasE (HOPE Fabry)
ClinicalTrials.gov study NCT05671770. IPD Sharing: YES. Countries: 1. Publications: 0.
Leveraging Electronic Health Record (EHR) Tools to Reduce Health Disparities for Patients With Uncontrolled Hypertension
ClinicalTrials.gov study NCT05030467. IPD Sharing: NO. Countries: 1. Publications: 0.
Development and Evaluation of an Electronic Health Record-based Medication Complete Communication (EMC2) Strategy
ClinicalTrials.gov study NCT03652272. IPD Sharing: NO. Countries: 1. Publications: 0.
Implementation and Evaluation of a Rare Disease Algorithm to Identify Persons at Risk of Gaucher Disease Using Data From Electronic Health Records (EHRs) in the United States (Project Searchlight)
ClinicalTrials.gov study NCT05908656. IPD Sharing: YES. Countries: 1. Publications: 0.
Sensor and Electronic Health Records (EHR) Integration Pilot Study
ClinicalTrials.gov study NCT03357341. IPD Sharing: Not stated. Countries: 1. Publications: 0.
PRescribing INterventions for Chronic Pain Via the Electronic Health Record Study - Current Opioid-User Population
ClinicalTrials.gov study NCT04601480. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Natural History and Patient Journey in Atrial Fibrillation: a Nationwide Linked Electronic Health Records Study of 5.6 Million Individuals.
ClinicalTrials.gov study NCT04786366. IPD Sharing: Not stated. Countries: 0. Publications: 1.
Ambulatory physicians’ electronic health record self-efficacy
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Usability of electronic health record systems in UK emergency departments
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Using a custom mobile application for change management in an electronic health record implementation
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Data from: Calculating maximum morphine equivalent daily dose from prescription directions for use in the electronic health record: a case report
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Utility of routinely collected electronic health records data to support effectiveness evaluations in Inflammatory Bowel Disease: A pilot study of Tofacitinib
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Predicting the physiological effects of multiple drugs using electronic health record
<p>Supplementary Data 1. Optimized hyperparameters of XGBoost classifiers for the 20 selected measurement items.</p> <p>Supplementary Data 2. Information on 416 active pharmaceutical ingredients used to develop machine learning models for the 20 selected measurement items.</p> <p>Supplementary Data 3. List of top 20 features with the highest feature importance for each type of machine learning models according to the SHAP analysis (Fig. 4). Numbers such as “1801186” and “1362055” are APIs presented using the old version of RxCUI.</p>
Dataset for paper "Ensemble transfer learning approach for gastric cancer prediction in electronic health records"
<p>This is datasets and codes for research on "Ensemble transfer learning approach for gastric cancer prediction in electronic health records"</p>
HeartShare: Combining Omics, Deep Phenotyping, and Electronic Health Records for Heart Failure Subtypes and Treatment Targets
ClinicalTrials.gov study NCT05873634. IPD Sharing: Not stated. Countries: 1. Publications: 0.
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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.