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Total Results: 1,710 records

Showing results for "learned".

301. EnhanCed HandOffs (ECHO) | Digital Healthcare Research
     digital.ahrq.gov/ahrq-funded-projects/enhanced-handoffs-echo
     January 01, 2025 - EnhanCed HandOffs (ECHO) Project Description Publications Research Story Implementing a machine learning-augmented sociotechnical intervention for postoperative handoffs is expected to improve interdisciplinary team communication, enhance patient safety, and creat…

302. Comprehensive Information Technology (IT) Solution for Quality and Patient Safety - 2009 | Digital Healthcare Research
     digital.ahrq.gov/ahrq-funded-projects/comprehensive-information-technology-it-solution-quality-and-patient-safety/annual-summary/2009
     January 01, 2009 - surveyed rated the success of their hospital’s implementation as "very good" or "good," and the lessons learned

303. Bar-coded Medication Administration | Digital Healthcare Research
     digital.ahrq.gov/bar-coded-medication-administration
     January 01, 2023 - While the projects described are not yet complete, some key "lessons learned" have emerged from the grantees

304. Improving Safety in Postoperative Handoff Communication with Telemedicine and Machine Learning | Digital Healthcare Research
     digital.ahrq.gov/program-overview/research-stories/improving-safety-postoperative-handoff-communication-telemedicine
     January 01, 2023 - Improving Safety in Postoperative Handoff Communication with Telemedicine and Machine Learning Theme: Optimizing Care Delivery for Clinicians Subtheme: Using Digital Healthcare Tools to Improve Patient Safety Implementing a postoperative handoff intervention augmented with telemedicine an…

305. Sikora, Andrea | Digital Healthcare Research
     digital.ahrq.gov/principal-investigator/sikora-andrea
     January 01, 2025 - Sikora, Andrea Evaluating accuracy and reproducibility of large language model performance on critical care assessments in pharmacy education. Citation Yang H, Hu M, Most A, Hawkins WA, Murray B, Smith SE, Li S, Sikora A. Evaluating accuracy and reproducibility of large langua…

306. Use of Artificial Intelligence and Machine Learning to Improve Care by Critical Care Pharmacists | Digital Healthcare Research
     digital.ahrq.gov/program-overview/research-stories/use-artificial-intelligence-and-machine-learning-improve-care
     January 01, 2023 - Use of Artificial Intelligence and Machine Learning to Improve Care by Critical Care Pharmacists Theme: Supporting Health Systems in Advancing Care Delivery Subtheme: Using Digital Healthcare Tools to Improve Patient Safety Using machine learning- and artificial intelligence-developed tool…

307. Evaluation of the Agency for Healthcare Research and Quality Patient-Centered Outcomes Research Clinical Decision Support Initiative: Findings and Recommendations for Future Initiatives (pdf file)
     digital.ahrq.gov/sites/default/files/docs/citation/cds-evaluation-summary-report-p233201500023I.pdf
     March 23, 2022 - In addition to describing the evaluation, the report provides findings and lessons learned about the … Initiative's accomplishments; and 2) generate findings related to successes, challenges, and lessons learned … In addition, strategies could describe lessons learned about engaging patients from AHRQ- funded CDS … Insights and Lessons Learned From CDS Connect Pilots. … Insights and Lessons Learned From CDS Connect Pilots • CDS Connect Presentation to U.S.

308. Using Machine Learning for Military Service Members and Veterans at Risk for Suicide | Digital Healthcare Research
     digital.ahrq.gov/program-overview/research-stories/using-machine-learning-military-service-members-and-veterans-risk
     January 01, 2023 - Using Machine Learning for Military Service Members and Veterans at Risk for Suicide Theme: Optimizing Care Delivery for Clinicians Subtheme: Leveraging Machine Learning to Assess Risk The use of a risk-prediction tool for both suicide ideation and suicide attempt has the potential to allo…

309. Using Electronic Records to Detect and Learn from Ambulatory Diagnostic Errors | Digital Healthcare Research
     digital.ahrq.gov/ahrq-funded-projects/using-electronic-records-detect-and-learn-ambulatory-diagnostic-errors
     January 01, 2023 - Using Electronic Records to Detect and Learn from Ambulatory Diagnostic Errors Project Final Report ( PDF , 244.61 KB) Disclaimer Disclaimer The findings and conclusions in this document are those of the author(s), who are responsible for its content, and do not necessarily rep…

310. Machine learning based prediction of prolonged duration of mechanical ventilation incorporating medication data. | Digital Healthcare Research
     digital.ahrq.gov/ahrq-funded-projects/machine-learning-validation-medication-regimen-complexity-critical-care/citation/machine
     January 01, 2023 - Machine learning based prediction of prolonged duration of mechanical ventilation incorporating medication data. Citation Sikora A, Zhao B, Kong Y, Murray B, Shen Y. Machine learning based prediction of prolonged duration of mechanical ventilation incorporating medication data. medRxiv [Preprint]. 202…

311. ML-ROVER: Machine Learning to Reduce Laboratory Test Overutilization | Digital Healthcare Research
     digital.ahrq.gov/ahrq-funded-projects/ml-rover-machine-learning-reduce-laboratory-test-overutilization
     January 01, 2025 - ML-ROVER: Machine Learning to Reduce Laboratory Test Overutilization Project Description Publications Implementing a validated machine learning based clinical decision support tool to reduce laboratory testing overutilization in pediatric intensive care unit patients will…

312. Building and maintaining trust in clinical decision support: Recommendations from the Patient‐Centered CDS Learning Network. | Digital Healthcare Research
     digital.ahrq.gov/ahrq-funded-projects/patient-centered-outcomes-research-clinical-decision-support-learning-network/citation/building
     January 01, 2023 - Building and maintaining trust in clinical decision support: Recommendations from the Patient‐Centered CDS Learning Network. Citation Richardson JE, Middleton B, Platt JE, et al. Building and maintaining trust in clinical decision support: Recommendations from the Patient‐Centered CDS Learning Network…

313. CDS Connect - Year 1 Final Report (pdf file)
     digital.ahrq.gov/sites/default/files/docs/citation/cds-connect-year1-final-report.pdf
     October 01, 2017 - Interoperability was recognized as important based upon past lessons learned and is supported via the … Lessons learned regarding IP constraints are included in the associated section below. … Lessons Learned Through the CDS Connect project’s base year, several valuable lessons were learned that … The lesson learned is that there are likely many clinical organizations that lack sufficient CDS, so … Through various interactions with multidisciplinary stakeholders, we’ve learned how critical it will

314. Machine Learning to Improve Patient Triage in the Emergency Department | Digital Healthcare Research
     digital.ahrq.gov/program-overview/research-stories/machine-learning-improve-patient-triage-emergency-department
     January 01, 2023 - Machine Learning to Improve Patient Triage in the Emergency Department Theme: Supporting Health Systems in Advancing Care Delivery Subtheme: Advancing Health Equity The use of an emergency department triage tool informed by machine learning has the potential to improve predictions around…

315. Research Centers in Primary Care Practice Based Research and Learning - Final Report | Digital Healthcare Research
     digital.ahrq.gov/ahrq-funded-projects/research-centers-primary-care-practice-based-research-and-learning/final-report
     January 01, 2023 - Research Centers in Primary Care Practice Based Research and Learning - Final Report Citation Ornstein S. Research Centers in Primary Care Practice Based Research and Learning - Final Report. (Prepared by the Medical University of South Carolina under Grant No. P30 HS021678). Rockville, MD: Agency for…

316. Learning from Primary Care Meaningful Use Exemplars - Final Report | Digital Healthcare Research
     digital.ahrq.gov/ahrq-funded-projects/learning-primary-care-meaningful-use-exemplars/final-report
     January 01, 2023 - Learning from Primary Care Meaningful Use Exemplars - Final Report Citation Ornstein, S. Learning from Primary Care Meaningful Use Exemplars - Final Report. (Prepared by the Medical University of South Carolina under Grant No. R18 HS022701). Rockville, MD: Agency for Healthcare Research and Quality, 2…

317. Using Electronic Records to Detect and Learn from Ambulatory Diagnostic Errors - Final Report | Digital Healthcare Research
     digital.ahrq.gov/ahrq-funded-projects/using-electronic-records-detect-and-learn-ambulatory-diagnostic-errors/final-report
     January 01, 2023 - Using Electronic Records to Detect and Learn from Ambulatory Diagnostic Errors - Final Report Citation Thomas E. Using Electronic Records to Detect and Learn from Ambulatory Diagnostic Errors - Final Report. (Prepared by University of Texas Health Science Center - Houston under Grant No. R18 HS017244…

318. Patient care in complex Sociotechnological ecosystems and learning health systems. | Digital Healthcare Research
     digital.ahrq.gov/ahrq-funded-projects/connected-cancer-care-ehr-communication-networks-virtual-cancer-care-teams/citation/patient
     January 01, 2024 - Patient care in complex Sociotechnological ecosystems and learning health systems. Citation Tu SP, Garcia B, Zhu X, Sewell D, Mishra V, Matin K, Dow A. Patient care in complex Sociotechnological ecosystems and learning health systems. Learn Health Syst. 2024 May 23;8(Suppl 1):e10427. doi: 10.1002/lrh2…

319. 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 Citation Sherwin R. Enhancing an EMR-Based Real-Time Sepsis Alert System Performance Through Machine Learning - Final Report. (Prepared by Wayne State University under Grant No. R21 HS024750). Rock…

320. A model of academic-practice collaboration for facilitating informatics capacity and building a learning health system framework in public health. | Digital Healthcare Research
     digital.ahrq.gov/ahrq-funded-projects/advancing-population-and-public-health-reporting-and-outcomes-vaccination-data-exchange-approve/citation/model
     January 01, 2024 - A model of academic-practice collaboration for facilitating informatics capacity and building a learning health system framework in public health. Citation Rajamani S, Solarz S, Muscoplat MH, Schmit AD, Gonderinger A, Brueske C, Fritz J, Emerson E, Melton GB. A model of academic-practice collaboration…