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Showing results for "learned".

4461. Medical Mistakes and What Doctors Can Learn From Pilots | PSNet
      psnet.ahrq.gov/training-catalog/medical-mistakes-and-what-doctors-can-learn-pilots
      July 21, 2025 - Medical Mistakes and What Doctors Can Learn From Pilots Save Save to your library Print Share Facebook Twitter Linkedin Copy URL Organization: Organization American Academy of Ophthalmology Even…

4462. A machine learning approach to reclassifying miscellaneous patient safety event reports. | Digital Healthcare Research
      digital.ahrq.gov/ahrq-funded-projects/developing-evidence-based-user-centered-design-and-implementation-guidelines/citation/machine
      January 01, 2023 - A machine learning approach to reclassifying miscellaneous patient safety event reports. Citation Fong A, Behzad S, Pruitt Z, Ratwani RM. A machine learning approach to reclassifying miscellaneous patient safety event reports. J Patient Saf. 2021 Dec 1;17(8):e829-e833. doi: 10.1097/PTS.000000000000073…

4463. Unsupervised machine learning analysis to identify patterns of ICU medication use for fluid overload prediction. | Digital Healthcare Research
      digital.ahrq.gov/ahrq-funded-projects/artificial-intelligence-based-health-it-tools-optimize-critical-care/citation/unsupervised
      January 01, 2023 - Unsupervised machine learning analysis to identify patterns of ICU medication use for fluid overload prediction. Citation Keats K, Deng S, Chen X, Zhang T, Devlin JW, Murphy DJ, Smith SE, Murray B, Kamaleswaran R, Sikora A. Unsupervised machine learning analysis to identify patterns of ICU medication …

4464. Machine-learning-based electronic triage more accurately differentiates patients with respect to clinical outcomes compared with the emergency severity index. | Digital Healthcare Research
      digital.ahrq.gov/ahrq-funded-projects/hopscore-electronic-outcomes-based-emergency-triage-system/citation/machine-learning
      January 01, 2023 - Machine-learning-based electronic triage more accurately differentiates patients with respect to clinical outcomes compared with the emergency severity index. Citation Levin S, Toerper M, Hamrock E, et al. Machine-learning-based electronic triage more accurately differentiates patients with respect to…

4465. USA, GA, Athens | Digital Healthcare Research
      digital.ahrq.gov/location/usa-ga-athens
      January 01, 2023 - USA, GA, Athens Machine Learning Validation of Medication Regimen Complexity for Critical Care Pharmacist Resource Prediction Description This research will develop and validate machine learning enhanced predictive models improving the allocation of critical care pharmacists t…

4466. Use of machine learning to develop and evaluate models using preoperative and intraoperative data to identify risks of postoperative complications. | Digital Healthcare Research
      digital.ahrq.gov/ahrq-funded-projects/anesthesiology-control-tower-feedback-alerts-supplement-treatment-actfast/citation/use
      January 01, 2023 - Use of machine learning to develop and evaluate models using preoperative and intraoperative data to identify risks of postoperative complications. Citation Xue B, Li D, Lu C, King CR, Wildes T, Avidan MS, Kannampallil T, Abraham J. Use of machine learning to develop and evaluate models using preopera…

4467. University of Georgia | Digital Healthcare Research
      digital.ahrq.gov/organization/university-georgia
      January 01, 2023 - University of Georgia Machine Learning Validation of Medication Regimen Complexity for Critical Care Pharmacist Resource Prediction Description This research will develop and validate machine learning enhanced predictive models improving the allocation of critical care pharmac…

4468. Applying machine learning in distributed data networks for pharmacoepidemiologic and pharmacovigilance studies: Opportunities, challenges, and considerations. | Digital Healthcare Research
      digital.ahrq.gov/ahrq-funded-projects/improving-missing-data-analysis-distributed-research-networks/citation/applying
      January 01, 2023 - Applying machine learning in distributed data networks for pharmacoepidemiologic and pharmacovigilance studies: Opportunities, challenges, and considerations. Citation Wong J, Prieto-Alhambra D, Rijnbeek PR, Desai RJ, Reps JM, Toh S. Applying machine learning in distributed data networks for pharmacoe…

4469. National Center for Pediatric Practice Based Research and Learning - Final Report | Digital Healthcare Research
      digital.ahrq.gov/ahrq-funded-projects/national-center-pediatric-practice-based-research-and-learning/final-report
      January 01, 2023 - National Center for Pediatric Practice Based Research and Learning - Final Report Citation Fiks A. National Center for Pediatric Practice Based Research and Learning - Final Report. (Prepared by the American Academy of Pediatrics under Grant No. P30 HS021645). Rockville, MD: Agency for Healthcare Rese…

4470. Psn-Pdf (pdf file)
      psnet.ahrq.gov/node/45462/psn-pdf
      August 31, 2016 - Learning From Mistakes. August 31, 2016 London, UK: Parliamentary and Health Service Ombudsman; July 18, 2016. ISBN: 9781474135764. https://psnet.ahrq.gov/issue/learning-mistakes The National Health Service (NHS) has a history of sharing analyses of problems in its system. Summarizing an NHS investigation into the…

4471. Psn-Pdf (pdf file)
      psnet.ahrq.gov/node/36117/psn-pdf
      July 19, 2006 - A Safer Place for Patients: Learning to Improve Patient Safety. July 19, 2006 House of Commons Committee on Public Accounts. London: The Stationery Office Limited; June 2006. https://psnet.ahrq.gov/issue/safer-place-patients-learning-improve-patient-safety-0 Using data from approximately 974,000 patient safety inc…

4472. Psn-Pdf (pdf file)
      psnet.ahrq.gov/node/842435/psn-pdf
      January 26, 2023 - Driving Learning and Improvement After RCA2 Event Reviews. January 11, 2023 Collaborative for Accountability and Improvement. January 26, 2023. https://psnet.ahrq.gov/issue/driving-learning-and-improvement-after-rca2-event-reviews Root cause analysis (RCA) is a recognized approach to examining failures by identify…

4473. Psn-Pdf (pdf file)
      psnet.ahrq.gov/node/46117/psn-pdf
      May 10, 2017 - Deep learning is a black box, but health care won't mind. May 10, 2017 Brouillette M. MIT Technol Rev. April 27, 2017. https://psnet.ahrq.gov/issue/deep-learning-black-box-health-care-wont-mind Artificial intelligence can support diagnostic decision-making. This magazine article reports on the use of algorithms to…

4474. Overview of the Comprehensive Unit-based Safety Program for Application to Mechanically Ventilated Patients: Slide Presentation | Agency for Healthcare Research and Quality
      www.ahrq.gov/hai/tools/mvp/modules/cusp/overview-cuspmvp-slides.html
      February 01, 2017 - Overview of the Comprehensive Unit-based Safety Program for Application to Mechanically Ventilated Patients: Slide Presentation AHRQ Safety Program for Mechanically Ventilated Patients Slide 1: AHRQ Safety Program for Mechanically Ventilated Patients Overview of the Comprehensive Unit-based Safety Program…

4475. CUSP Toolkit: The Role of the Nurse Manager | Agency for Healthcare Research and Quality
      www.ahrq.gov/hai/cusp/modules/nursing/sl-nursing.html
      December 01, 2012 - CUSP Toolkit: The Role of the Nurse Manager CUSP Toolkit The Role of the Nurse Manager module of the CUSP Toolkit addresses the role of nursing leaders for your quality improvement initiative. Contents Slide 1. Cover Slide. Slide 2. Learning Objectives Slide 3. What is a Nurse Manager? Slide 4. Wh…

4476. Harnessing Health Information Technology to Promote Equitable Care for Patients with Limited English Proficiency and Complex Care Needs | Digital Healthcare Research
      digital.ahrq.gov/ahrq-funded-projects/harnessing-health-information-technology-promote-equitable-care-patients-limited-english
      October 31, 2024 - Harnessing Health Information Technology to Promote Equitable Care for Patients with Limited English Proficiency and Complex Care Needs Project Description Publications Research Story A machine learning predictive analytic intervention has the potential to improve h…

4477. Introduction | Agency for Healthcare Research and Quality
      www.ahrq.gov/diagnostic-safety/resources/issue-briefs/dxsafety-patients-source-understanding-dx-error-vol1-2.html
      June 01, 2023 - Patient Experience as a Source for Understanding the Origins, Impact, and Remediation of Diagnostic Errors Introduction Previous Page Next Page Table of Contents Patient Experience as a Source for Understanding the Origins, Impact, and Remediation of Diagnostic Errors Executive Summary Introduct…

4478. High-risk medication errors: insight from the UK National Reporting and Learning System. | PSNet
      psnet.ahrq.gov/issue/high-risk-medication-errors-insight-uk-national-reporting-and-learning-system
      January 12, 2022 - Study High-risk medication errors: insight from the UK National Reporting and Learning System. Citation Text: Alrowily A, Alfaraidy K, Almutairi S, et al. High-risk medication errors: Insight from the UK National Reporting and learning system. Explor Res Clin Soc Pharm. 2025;17:100531. d…

4479. Payer | Digital Healthcare Research
      digital.ahrq.gov/population/payer
      September 01, 2024 - Payer Clinical Decision Support Innovation Collaborative 2023-2024 (Year 3) Period of Performance Report Citation Dullabh PM, Shah AS, Dhopeshwarkar RV, Desai PJ, Peterson CE, Jiménez F, Gauthreaux N, Leaphart DM, Zott C, Byrne M, Adams L. Clinical Decision Support Innovation …

4480. Learning from mistakes is easier said than done: group and organizational influences on the detection and correction of human error. | PSNet
      psnet.ahrq.gov/issue/learning-mistakes-easier-said-done-group-and-organizational-influences-detection-and
      September 25, 2024 - Study Classic Learning from mistakes is easier said than done: group and organizational influences on the detection and correction of human error. Citation Text: Edmondson AC. Learning from Mistakes is Easier Said Than Done: Group and Organizational Influences o…