Results

Total Results: over 10,000 records

Showing results for "assessed".

8421. Medication errors resulting from computer entry by nonprescribers.   | PSNet
      psnet.ahrq.gov/issue/medication-errors-resulting-computer-entry-nonprescribers
      January 02, 2017 - Study Medication errors resulting from computer entry by nonprescribers.   Citation Text: Santell JP, Kowiatek JG, Weber RJ, et al. Medication errors resulting from computer entry by nonprescribers. Am J Health Syst Pharm. 2009;66(9):843-53. doi:10.2146/ajhp080208. Copy Citation …

8422. Excess cost and length of stay associated with voluntary patient safety event reports in hospitals. | PSNet
      psnet.ahrq.gov/issue/excess-cost-and-length-stay-associated-voluntary-patient-safety-event-reports-hospitals
      October 19, 2022 - Study Excess cost and length of stay associated with voluntary patient safety event reports in hospitals. Citation Text: Paradis AR, Stewart VT, Bayley KB, et al. Excess Cost and Length of Stay Associated With Voluntary Patient Safety Event Reports in Hospitals. American Journal of M…

8423. How patients can improve the accuracy of their medical records. | PSNet
      psnet.ahrq.gov/issue/how-patients-can-improve-accuracy-their-medical-records
      July 20, 2022 - Study How patients can improve the accuracy of their medical records. Citation Text: Dullabh P, Sondheimer N, Katsh E, et al. How Patients Can Improve the Accuracy of their Medical Records. eGEMs (Generating Evidence & Methods to improve patient outcomes). 2014;2(3). doi:10.13063/2327-92…

8424. Characteristics and trends of medical diagnostic errors in the United States. | PSNet
      psnet.ahrq.gov/issue/characteristics-and-trends-medical-diagnostic-errors-united-states
      December 14, 2022 - Study Characteristics and trends of medical diagnostic errors in the United States. Citation Text: Ao HS, Matthews T. Characteristics and trends of medical diagnostic errors in the United States. Patient Safety. 2024;6(1):123603. doi:10.33940/001c.123603. Copy Citation Format: …

8425. Association between surgeon stress and major surgical complications. | PSNet
      psnet.ahrq.gov/issue/association-between-surgeon-stress-and-major-surgical-complications
      November 29, 2023 - Study Association between surgeon stress and major surgical complications. Citation Text: Awtry J, Skinner S, Polazzi S, et al. Association between surgeon stress and major surgical complications. JAMA Surg. 2025;160(3):332-340. doi:10.1001/jamasurg.2024.6072. Copy Citation Format:…

8426. Understanding factors influencing safety and team functionality at operative vaginal birth through multidisciplinary perspectives: a mixed methods study. | PSNet
      psnet.ahrq.gov/issue/understanding-factors-influencing-safety-and-team-functionality-operative-vaginal-birth
      September 01, 2016 - Study Understanding factors influencing safety and team functionality at operative vaginal birth through multidisciplinary perspectives: a mixed methods study. Citation Text: Skinner SM, Kippen E, Rolnik DL, et al. Understanding factors influencing safety and team functionality at operat…

8427. Thematic analysis of women's perspectives on the meaning of safety during hospital-based birth. | PSNet
      psnet.ahrq.gov/issue/thematic-analysis-womens-perspectives-meaning-safety-during-hospital-based-birth
      May 08, 2019 - Study Thematic analysis of women's perspectives on the meaning of safety during hospital-based birth. Citation Text: Lyndon A, Malana J, Hedli LC, et al. Thematic Analysis of Women's Perspectives on the Meaning of Safety During Hospital-Based Birth. J Obstet Gynecol Neonatal Nurs. 2018;4…

8428. Evaluation of Measure Dx, a resource to accelerate diagnostic safety learning and improvement. | PSNet
      psnet.ahrq.gov/issue/evaluation-measure-dx-resource-accelerate-diagnostic-safety-learning-and-improvement
      February 07, 2024 - Study Evaluation of Measure Dx, a resource to accelerate diagnostic safety learning and improvement. Citation Text: Bradford A, Tran A, Ali KJ, et al. Evaluation of Measure Dx, a resource to accelerate diagnostic safety learning and improvement. J Gen Intern Med. . 2024;Epub Oct 22. doi:…

8429. Artificial intelligence in clinical diagnosis: opportunities, challenges, and hype. | PSNet
      psnet.ahrq.gov/issue/artificial-intelligence-clinical-diagnosis-opportunities-challenges-and-hype
      December 21, 2022 - Commentary Artificial intelligence in clinical diagnosis: opportunities, challenges, and hype. Citation Text: Kulkarni PA, Singh H. Artificial intelligence in clinical diagnosis: opportunities, challenges, and hype. JAMA. 2023;330(4):317-318. doi:10.1001/jama.2023.11440. Copy Citation …

8430. First Annual Report to Congress on High-Priority Evidence Gaps for Clinical Preventive Services | United States Preventive Services Taskforce
      www.uspreventiveservicestaskforce.org/uspstf/about-uspstf/reports-congress/first-annual-report-congress-high-priority-evidence-gaps-clinical-preventive-services
      December 01, 2011 - First Annual Report to Congress on High-Priority Evidence Gaps for Clinical Preventive Services Share to Facebook Share to X Share to WhatsApp Share to Email Print The U.S. Preventive Services Task Force (USPSTF or Task Force),  scientificall…

8431. Five strategies for a safer EHR modernization journey. | PSNet
      psnet.ahrq.gov/issue/five-strategies-safer-ehr-modernization-journey
      November 11, 2020 - Commentary Five strategies for a safer EHR modernization journey. Citation Text: Sittig DF, Yackel EE, Singh H. Five strategies for a safer EHR modernization journey. J Gen Intern Med. 2023;38(S4):940-942. doi:10.1007/s11606-023-08331-z. Copy Citation Format: DOI Google Sch…

8432. Machine-Learning Prediction Model for Personalized Urinary Tract Infection Care in Children | Digital Healthcare Research
      digital.ahrq.gov/ahrq-funded-projects/machine-learning-prediction-model-personalized-urinary-tract-infection-care
      July 01, 2024 - Machine-Learning Prediction Model for Personalized Urinary Tract Infection Care in Children Project Description Implementing a practical, validated clinical decision support algorithm to identify unsafe anatomy before injury occurs has the potential to significantly reduce rena…

8433. Guidelines Into Decision Support (GLIDES) | Digital Healthcare Research
      digital.ahrq.gov/ahrq-funded-projects/guidelines-decision-support-glides
      January 01, 2023 - Guidelines Into Decision Support (GLIDES) Project Description Annual Summaries Publications Project Details - Completed Contract Number 290-08-10011 Funding Mechanism(s) Clinical Decision Support Services Project…

8434. Human-computer collaboration for skin cancer recognition. | PSNet
      psnet.ahrq.gov/issue/human-computer-collaboration-skin-cancer-recognition
      June 26, 2019 - Study Classic Human-computer collaboration for skin cancer recognition. Citation Text: Tschandl P, Rinner C, Apalla Z, et al. Human–computer collaboration for skin cancer recognition. Nat Med. 2020;26(8):1229-1234. doi:10.1038/s41591-020-0942-0. Copy Citation …

8435. A Crisis in Health Care: A Call to Action on Physician Burnout. | PSNet
      psnet.ahrq.gov/issue/crisis-health-care-call-action-physician-burnout
      February 05, 2014 - Book/Report A Crisis in Health Care: A Call to Action on Physician Burnout. Citation Text: A Crisis in Health Care: A Call to Action on Physician Burnout. Jha AK, Iliff AR, Chaoui AA, et al. Waltham, MA: Massachusetts Medical Society, Massachusetts Health and Hospital Association, Harvar…

8436. Understanding How Social Influence and Social Networks Affect Electronic Medical Record Implementation | Digital Healthcare Research
      digital.ahrq.gov/ahrq-funded-projects/understanding-how-social-influence-and-social-networks-affect-electronic
      January 01, 2023 - Understanding How Social Influence and Social Networks Affect Electronic Medical Record Implementation Project Final Report ( PDF , 367.9 KB) Disclaimer Disclaimer The findings and conclusions in this document are those of the author(s), who are responsible for its content, and…

8437. Prevalence of inappropriate antibiotic prescriptions among US ambulatory care visits, 2010–2011. | PSNet
      psnet.ahrq.gov/issue/prevalence-inappropriate-antibiotic-prescriptions-among-us-ambulatory-care-visits-2010-2011
      November 12, 2014 - Study Prevalence of inappropriate antibiotic prescriptions among US ambulatory care visits, 2010–2011. Citation Text: Fleming-Dutra KE, Hersh AL, Shapiro DJ, et al. Prevalence of Inappropriate Antibiotic Prescriptions Among US Ambulatory Care Visits, 2010-2011. JAMA. 2016;315(17):1864-18…

8438. Association of simulation training with rates of medical malpractice claims among obstetrician-gynecologists. | PSNet
      psnet.ahrq.gov/issue/association-simulation-training-rates-medical-malpractice-claims-among-obstetrician
      December 02, 2020 - Study Association of simulation training with rates of medical malpractice claims among obstetrician-gynecologists. Citation Text: Schaffer AC, Babayan A, Einbinder JS, et al. Association of simulation training with rates of medical malpractice claims among obstetrician-gynecologists. Ob…

8439. Systems approach to suicide prevention: strengthening culture, practice, and education. | PSNet
      psnet.ahrq.gov/issue/systems-approach-suicide-prevention-strengthening-culture-practice-and-education
      July 10, 2024 - Commentary Systems approach to suicide prevention: strengthening culture, practice, and education. Citation Text: Pisani AR, Boudreaux ED. Systems approach to suicide prevention: strengthening culture, practice, and education. Focus (Am Psychiatr Publ). 2023;21(2):152-159. doi:10.1176/ap…

8440. Development of "SWARM" as a model for high reliability, rapid problem solving, and institutional learning. | PSNet
      psnet.ahrq.gov/issue/development-swarm-model-high-reliability-rapid-problem-solving-and-institutional-learning
      November 16, 2022 - Commentary Development of "SWARM" as a model for high reliability, rapid problem solving, and institutional learning. Citation Text: Williams EA, Nikolai DA, Ladwig L, et al. Development of "SWARM" as a Model for High Reliability, Rapid Problem Solving, and Institutional Learning. Jt Com…