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Total Results: 72 records

Showing results for "sepsis".

1. Enhancing an EMR-Based Real-Time Sepsis Alert System Performance through Machine Learning - Final Report (pdf file)
   digital.ahrq.gov/sites/default/files/docs/citation/r21hs024750-sherwin-final-report-2019.pdf
   January 01, 2019 - The primary goal of the Sepsis-Alert was to identify ED patients highly likely to have sepsis, severe … The role of neutrophils in severe sepsis. Shock 2008;30 Suppl 1:3-9. 4. … National estimates of severe sepsis in United States emergency departments. … Surviving sepsis campaign: international guidelines for management of severe sepsis and septic shock … program targeting severe sepsis.

2. Identifying Sepsis Phenotypes Associated with Antibiotic-Resistant Pathogens Using Large Language Models and Machine Learning | Digital Healthcare Research
   digital.ahrq.gov/ahrq-funded-projects/identifying-sepsis-phenotypes-associated-antibiotic-resistant-pathogens-using
   August 01, 2024 - Identifying Sepsis Phenotypes Associated with Antibiotic-Resistant Pathogens Using Large Language Models … Description Identifying when broad-spectrum antibiotics can be safely avoided in suspected sepsis … Current guidelines recommend the immediate use of broad-spectrum antibiotics for suspected sepsis to … This research aims to improve the accuracy of sepsis treatment by identifying cases where narrow-spectrum … Identify phenotypes of suspected sepsis for whom the negative impact of overly broad early antibiotic

3. Enhancing an EMR-Based Real-Time Sepsis Alert System Performance Through Machine Learning | Digital Healthcare Research
   digital.ahrq.gov/ahrq-funded-projects/enhancing-emr-based-real-time-sepsis-alert-system-performance-through-machine
   January 01, 2023 - Enhancing an EMR-Based Real-Time Sepsis Alert System Performance Through Machine Learning … Sepsis is also expensive, representing five percent of total hospital costs each year and resulting in … the performance of Intelligent Sepsis Alert (ISA). … ISA is an artificial intelligence-enhanced version of an existing sepsis CDS tool, Sepsis Alert (SA). … Once designed, ISA was retrospectively tested on the prior year’s sepsis and nonsepsis cases.

4. Development of a Clinical Decision Support Tool for Facilitating Naturalistic Decision-Making and Improving Blood Culture Utilization - Final Report (pdf file)
   digital.ahrq.gov/sites/default/files/docs/citation/r21hs025238-xie-final-report-2020.pdf
   January 01, 2020 - Did antibiotics result in no sepsis developed or did clinician misdiagnose sepsis? … sepsis? … Did antibiotics result in no sepsis developed or did CDS tool and clinician misdiagnose sepsis? … Epidemiology of severe sepsis in the United States: analysis of incidence, outcome, and associated costs … Surviving sepsis campaign: international guidelines for management of severe sepsis and septic shock

5. Assessing the Relationship between Care Processes and Clinical Decision Support for Order Entry – Final Report (pdf file)
   digital.ahrq.gov/sites/default/files/docs/citation/r03hs0S26266-zhang-final-report-2022.pdf
   January 01, 2022 - The DISPARITY-II study: delays to antibiotic administration in women with severe sepsis or septic shock … Medicare Beneficiaries With Hospitalizations for Severe Sepsis and Septic Shock. … Hospital-wide impact of a standardized order set for the management of bacteremic severe sepsis. … Standardized order sets for the treatment of severe sepsis and septic shock. … The impact of protocolized sepsis order set on the process of care in patients with severe sepsis/septic

6. Enhancing an EMR-Based Real-Time Sepsis Alert System Performance Through Machine Learning - Final Report | Digital Healthcare Research
   digital.ahrq.gov/ahrq-funded-projects/enhancing-emr-based-real-time-sepsis-alert-system-performance-through-machine/final-report
   January 01, 2023 - Enhancing an EMR-Based Real-Time Sepsis Alert System Performance Through Machine Learning - Final Report … Enhancing an EMR-Based Real-Time Sepsis Alert System Performance Through Machine Learning - Final Report … Principal Investigator Sherwin, Robert Project Name Enhancing an EMR-Based Real-Time Sepsis

7. Sherwin, Robert | Digital Healthcare Research
   digital.ahrq.gov/principal-investigator/sherwin-robert
   January 01, 2023 - Sherwin, Robert Enhancing an EMR-Based Real-Time Sepsis Alert System … Enhancing an EMR-Based Real-Time Sepsis Alert System Performance Through Machine Learning - Final Report … Principal Investigator Sherwin, Robert Project Name Enhancing an EMR-Based Real-Time Sepsis … System Performance Through Machine Learning Enhancing an EMR-Based Real-Time Sepsis … and developed, tested, implemented, and validated a knowledge-based artificial intelligence-enhanced sepsis

8. Bacterial Infection | Digital Healthcare Research
   digital.ahrq.gov/medical-condition/bacterial-infection
   January 01, 2023 - Bacterial Infection Enhancing an EMR-Based Real-Time Sepsis Alert System … Enhancing an EMR-Based Real-Time Sepsis Alert System Performance Through Machine Learning - Final Report … Principal Investigator Sherwin, Robert Project Name Enhancing an EMR-Based Real-Time Sepsis … Health Information Technology System Design Enhancing an EMR-Based Real-Time Sepsis … and developed, tested, implemented, and validated a knowledge-based artificial intelligence-enhanced sepsis

9. USA, MI, Detroit | Digital Healthcare Research
   digital.ahrq.gov/location/usa-mi-detroit
   January 01, 2023 - USA, MI, Detroit Enhancing an EMR-Based Real-Time Sepsis Alert System … Performance Through Machine Learning Description This research took an existing sepsis-related … and developed, tested, implemented, and validated a knowledge-based artificial intelligence-enhanced sepsis

10. Wayne State University | Digital Healthcare Research
    digital.ahrq.gov/organization/wayne-state-university
    January 01, 2023 - Wayne State University Enhancing an EMR-Based Real-Time Sepsis Alert … System Performance Through Machine Learning Description This research took an existing sepsis-related … and developed, tested, implemented, and validated a knowledge-based artificial intelligence-enhanced sepsis

11. Improving the Delivery of Health Services at the Health Systems Level | Digital Healthcare Research
    digital.ahrq.gov/2019-year-review/research-summary/improving-delivery-health-services-health-systems-level
    January 01, 2019 - To enhance the clinical diagnosis of sepsis, Dr. … Robert Sherwin developed Intelligent Sepsis Alert (ISA), an AI-enhanced version of an existing sepsis … The tool integrates a real-time alert module into the EHR to identify patients with possible sepsis, … resulting in enhanced performance from the existing sepsis CDS tool, further improving sepsis management

12. Pak, Theodore R. | Digital Healthcare Research
    digital.ahrq.gov/principal-investigator/pak-theodore-r
    January 01, 2023 - Identifying Sepsis Phenotypes Associated with Antibiotic-Resistant Pathogens Using Large Language Models … and machine learning to retrospectively analyze electronic health records of patients with suspected sepsis

13. Division of Research Education, Office of Extramural Research, Education, and Priority Populations (OEREP) | Digital Healthcare Research
    digital.ahrq.gov/program/division-research-education-office-extramural-research-education-and-priority-populations
    January 01, 2023 - www.ahrq.gov/funding/training-grants/index.html Identifying Sepsis … and machine learning to retrospectively analyze electronic health records of patients with suspected sepsis

14. Assessing the Relationship Between Care Processes and Clinical Decision Support for Order Entry | Digital Healthcare Research
    digital.ahrq.gov/ahrq-funded-projects/assessing-relationship-between-care-processes-and-clinical-decision-support
    January 01, 2023 - Project Description Publications The use of order sets in patients with sepsis … conducted on data from three sites of the New York-Presbyterian Hospital system, focused on patients with sepsis … set usage was associated with less order variation and better outcomes for patients hospitalized with sepsis

15. Generative Artificial Intelligence | Digital Healthcare Research
    digital.ahrq.gov/technology/generative-artificial-intelligence
    January 01, 2023 - Generative Artificial Intelligence Identifying Sepsis Phenotypes Associated … and machine learning to retrospectively analyze electronic health records of patients with suspected sepsis

16. Development of a Clinical Decision Support Tool for Facilitating Naturalistic Decision Making and Improving Blood Culture Utilization | Digital Healthcare Research
    digital.ahrq.gov/ahrq-funded-projects/development-clinical-decision-support-tool-facilitating-naturalistic-decision
    January 01, 2023 - Care Theme Clinical Decision Making Sociotechnical Aspects Technology Usability Sepsis … Blood cultures are the only way to diagnose sepsis; however, overuse of blood cultures may result in … to identify challenges to collecting key information required for blood culture decision making and sepsis

17. Massachusetts General Hospital | Digital Healthcare Research
    digital.ahrq.gov/organization/massachusetts-general-hospital
    January 01, 2023 - Massachusetts General Hospital Identifying Sepsis Phenotypes Associated … and machine learning to retrospectively analyze electronic health records of patients with suspected sepsis

18. Medication Safety | Digital Healthcare Research
    digital.ahrq.gov/health-care-theme/medication-safety
    January 01, 2023 - Medication Safety Identifying Sepsis Phenotypes Associated with Antibiotic-Resistant … and machine learning to retrospectively analyze electronic health records of patients with suspected sepsis

19. USA, MA, Boston | Digital Healthcare Research
    digital.ahrq.gov/location/usa-ma-boston
    January 01, 2023 - HS029526 Principal Investigator(s) Wang, Hsin-Hsiao Scott Identifying Sepsis … and machine learning to retrospectively analyze electronic health records of patients with suspected sepsis

20. Predictive Monitoring: IMPact of Real-Time Predictive Monitoring in Acute Care Cardiology Trial (PM-IMPACCT) | Digital Healthcare Research
    digital.ahrq.gov/ahrq-funded-projects/predictive-monitoring-impact-real-time-predictive-monitoring-acute-care
    January 01, 2023 - with cardiac disease are at risk for sudden deterioration from complicating subacute illnesses such as sepsis … recognizing earlier in the clinical course that a patient is imminently at risk for respiratory failure, sepsis … recognize earlier in the clinical course that a patient is imminently at risk for respiratory failure, sepsis