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  1. www.ahrq.gov/hai/quality/tools/cauti-ltc/modules/implementation/long-term-modules/module4/guide.html
    March 01, 2017 - Module 4: Teamwork and Communication: Material Use Guide AHRQ Safety Program for Long-Term Care: HAIs/CAUTI Learning Objectives: Describe effective communication and teamwork. Describe why teamwork training and improved communication optimizes resident safety. List barriers, tools, and str…
  2. Guide (doc file)

    www.ahrq.gov/sites/default/files/wysiwyg/professionals/quality-patient-safety/quality-resources/tools/cauti-ltc/modules/implementation/long-term-modules/module4/guide.docx
    March 01, 2017 - AHRQ Safety Program for Long-Term Care: HAIs/CAUTI Long-Term Care Safety Modules Module 4: Teamwork and Communication Material Use Guide Learning Objectives: · Describe effective communication and teamwork · Describe why teamwork training and improved communication optimizes resident safety · List barriers, tools…
  3. www.ahrq.gov/sites/default/files/wysiwyg/professionals/quality-patient-safety/hais/tools/ambulatory-surgery/sections/implementation/implementation-guide/appendix-k-study-elements.docx
    June 02, 2025 - Quality Improvement Study Framework Element Definition Things To Keep in Mind The Purpose Define the problem and why it is important. · Avoid suggesting causes in the purpose statement. Cause determination will come later after the data have been analyzed. · Speculating about the cause of a problem before a th…
  4. psnet.ahrq.gov/issue/neurobehavioral-performance-residents-after-heavy-night-call-vs-after-alcohol-ingestion
    June 22, 2022 - Study Neurobehavioral performance of residents after heavy night call vs after alcohol ingestion. Citation Text: Arnedt JT, Owens J, Crouch M, et al. Neurobehavioral Performance of Residents After Heavy Night Call vs After Alcohol Ingestion. JAMA. 2005;294(9). doi:10.1001/jama.294.9.10…
  5. psnet.ahrq.gov/issue/use-patient-complaints-identify-diagnosis-related-safety-concerns-mixed-method-evaluation
    April 13, 2022 - Study Use of patient complaints to identify diagnosis-related safety concerns: a mixed-method evaluation. Citation Text: Giardina TD, Korukonda S, Shahid U, et al. Use of patient complaints to identify diagnosis-related safety concerns: a mixed-method evaluation. BMJ Qual Saf. 2021;30(12…
  6. psnet.ahrq.gov/issue/research-adverse-drug-events-and-reports-radar-project
    October 19, 2022 - Study The Research on Adverse Drug Events and Reports (RADAR) project. Citation Text: Bennett CL, Nebeker JR, Lyons A, et al. The Research on Adverse Drug Events and Reports (RADAR) project. JAMA. 2005;293(17):2131-40. Copy Citation Format: Google Scholar PubMed BibTeX En…
  7. psnet.ahrq.gov/issue/unlocking-potential-free-text-electronic-health-records-large-language-models-llm-enhancing
    October 01, 2014 - Commentary Unlocking the potential of free text in electronic health records with large language models (LLM): enhancing patient safety and consultation interactions. Citation Text: Kumarapeli P, Haddad T, de Lusignan S. Unlocking the potential of free text in electronic health records w…
  8. psnet.ahrq.gov/issue/intensive-care-unit-nurses-perceptions-safety-after-highly-specific-safety-intervention
    June 16, 2011 - Study Intensive care unit nurses' perceptions of safety after a highly specific safety intervention. Citation Text: Elder NC, Brungs SM, Nagy M, et al. Intensive care unit nurses' perceptions of safety after a highly specific safety intervention. Qual Saf Health Care. 2008;17(1):25-3…
  9. psnet.ahrq.gov/issue/effectiveness-interruptive-prescribing-alerts-ambulatory-cpoe-change-prescriber-behaviour-and
    February 02, 2022 - Review The effectiveness of interruptive prescribing alerts in ambulatory CPOE to change prescriber behaviour and improve safety. Citation Text: Cerqueira O, Gill M, Swar B, et al. The effectiveness of interruptive prescribing alerts in ambulatory CPOE to change prescriber behaviour and …
  10. www.ahrq.gov/sites/default/files/wysiwyg/professionals/systems/hospital/engagingfamilies/strategy1/Strat1_Tool_13_ShortTerm_HO_508.pdf
    June 02, 2025 - Strategy 1: Working with Patients & Families as Advisors (Tool 13) Guide to Patient and Family Engagement :: 1 Working With Patient and Family Advisors on Short-Term Projects Are you (or is your unit) planning to work on a short-term project to improve quality and safety? Partnering with patient and family a…
  11. www.ahrq.gov/sites/default/files/wysiwyg/professionals/systems/hospital/engagingfamilies/strategy1/Strat1_Tool_13_ShortTerm_HO_508.docx
    June 02, 2025 - Strategy 1: Working with Patients & Families as Advisors (Tool 13) Strategy 1: Working With Patients & Families as Advisors (Tool 13) Working With Patient and Family Advisors on Short-Term Projects Are you (or is your unit) planning to work on a short-term project to improve quality and safety? Partnering with patient…
  12. psnet.ahrq.gov/issue/long-term-care-healthcare-associated-infections-2021-analysis-17971-reports
    July 06, 2022 - Study Long-term care healthcare-associated infections in 2021: an analysis of 17,971 reports. Citation Text: Kepner S, Adkins JA, Jones RM. Long-term care healthcare-associated infections in 2021: an analysis of 17,971 reports. Patient Saf. 2022;4(2):6-17. doi:10.33940/data/2022.6.1. C…
  13. digital.ahrq.gov/population/clinical-staff
    January 01, 2024 - Clinical Staff/Clinician Bedside Notes: A Multicenter Trial to Improve Family Clinical Note Access and Outcomes for Hospitalized Children Description This research will evaluate the effectiveness of Bedside Notes, a digital health solution designed to provide caregivers with r…
  14. psnet.ahrq.gov/issue/frequency-and-types-patient-reported-errors-electronic-health-record-ambulatory-care-notes
    June 05, 2019 - Study Classic Frequency and types of patient-reported errors in electronic health record ambulatory care notes. Citation Text: Bell SK, Delbanco T, Elmore JG, et al. Frequency and types of patient-reported errors in electronic health record ambulatory care notes…
  15. digital.ahrq.gov/care-setting/ambulatory-clinic
    January 01, 2023 - Ambulatory Setting Development and Assessment of Artificial Intelligence (AI)-Enhanced Pretreatment Peer-review Process to Improve Patient Safety in Radiation Oncology Description This research develops and evaluates an artificial intelligence-enhanced pretreatment peer-review…
  16. www.ahrq.gov/funding/grantee-profiles/grtprofile-zhou.html
    July 01, 2024 - Grantee Profile Using Technology to Alert Clinicians to Potential Allergy, Drug Interactions Li Zhou, M.D., Ph.D. Professor of Medicine, Harvard Medical School Lead investigator, Brigham and Women’s Hospital Li Zhou, M.D., Ph.D. “I really appreciate how AHRQ looks for ways to use technology to improve patie…
  17. www.ahrq.gov/tools/index.html
    December 01, 2015 - Comprehensive Unit-based Safety Program (CUSP) The CUSP toolkit includes training tools to make care safer. More The SHARE Approach Five-step process for clinicians and their patients More EvidenceNOW Tools for Change Helping practices implement evidence More Tools The …
  18. digital.ahrq.gov/health-care-theme/patient-safety
    January 01, 2023 - Patient Safety Bedside Notes: A Multicenter Trial to Improve Family Clinical Note Access and Outcomes for Hospitalized Children Description This research will evaluate the effectiveness of Bedside Notes, a digital health solution designed to provide caregivers with real-time a…
  19. psnet.ahrq.gov/issue/effect-bar-code-technology-safety-medication-administration
    October 25, 2010 - Study Classic Effect of bar-code technology on the safety of medication administration. Citation Text: Poon EG, Keohane C, Yoon CS, et al. Effect of bar-code technology on the safety of medication administration. New Engl J Med. 2010;362(18):1698-1707. doi:10.10…
  20. psnet.ahrq.gov/issue/diagnostic-assessment-deep-learning-algorithms-detection-lymph-node-metastases-women-breast
    June 27, 2018 - Study Classic Diagnostic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer. Citation Text: Bejnordi BE, Veta M, van Diest PJ, et al. Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph …