A hospital trust that became the first and only organisation in Europe to achieve a HIMSS stage six validation for its use of data and its approach to data science has collaborated on a…
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What You Should Know:
– Sware, the leading provider of comprehensive GxP validation solutions for innovative life sciences and technology companies, today announced that it will deliver GxP computer systems validation of Salesforce Life Sciences Cloud.
– Life…
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Chelsea and Westminster Hospital NHS Foundation Trust is running user acceptance testing for a Referral to Treatment (RTT) clinical letters validation tool on the federated data platform (FDP).
The tool is designed to streamline RTT…
Texas-based healthcare data analytics company MedeAnalytics announced it is collaborating with fellow healthcare data analytics firms Socially Determined and Mathematica.The companies launched “Social Risk Insights, Measures and Outcomes,” a program built on the MedeAnalytics…
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Transthoracic echocardiography (TTE), commonly used for initial screening of pulmonary hypertension (PH), often lacks sufficient accuracy. To address this gap, we developed and validated a multimodal fusion model for improved PH screening (MMF-PH). The…
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In this interview, Nora Lissy, VP of Healthcare Consulting & Implementation, and James Kirtley, Senior Software Engineer at Dimensional Insight, break down why speed matters when it comes to healthcare analytics. With tighter budgets…
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Tungs’ Taichung MetroHarbor Hospital is the latest in Taiwan to get validated for the HIMSS Electronic Medical Record Adoption Model.The EMRAM measures an organisation’s adoption and maturity of their EMR capabilities.
WHY IT MATTERS
Tungs’ Hospital…
We developed and validated models to predict 1- and 2-week risk of non-elective hospitalization (NEH) and sepsis hospitalization following outpatient clinic, emergency department treat and release (EDTR), or hospitalization encounters. We employed data from…
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Sepsis real-time prediction models (SRPMs) provide timely alerts and may improve patient outcomes but face limited clinical adoption due to inconsistent validation methods and potential biases. Comprehensive evaluation, including external full-window validation with model-…
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Not all AI in healthcare carries the same risk. Some applications can be deployed quickly with minimal oversight, while others—like clinical decision support—demand rigorous validation. In this interview, Ben Scharfe, EVP of AI Initiatives…
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