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241. National Center for Pediatric Practice-Based Research and Learning | Digital Healthcare Research
     digital.ahrq.gov/ahrq-funded-projects/national-center-pediatric-practice-based-research-and-learning
     January 01, 2023 - National Center for Pediatric Practice-Based Research and Learning Project Final Report ( PDF , 502.95 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 represent the v…

242. Improving Safety and Quality of Emergency Care Using Machine Learning-Based Clinical Decision Support at Triage | Digital Healthcare Research
     digital.ahrq.gov/ahrq-funded-projects/improving-safety-and-quality-emergency-care-using-machine-learning-based
     September 30, 2023 - Improving Safety and Quality of Emergency Care Using Machine Learning-Based Clinical Decision Support at Triage Project Description Research Story The use of an emergency department triage tool informed by machine learning algorithms that is integrated into the electronic…

243. The Patient-Centered Clinical Decision Support Learning Network: Improving the Dissemination of PCOR in Patient-Centered Clinical Decision Support - Final Report (pdf file)
     digital.ahrq.gov/sites/default/files/docs/citation/u18hs024849-blumenfeld-final-report-2020.pdf
     January 01, 2020 - They provided a platform for a large number of diverse attendees to convene and learn from each other

244. El Dorado County Safety Net Technology Project/Access El Dorado County (ACCEL) | Digital Healthcare Research
     digital.ahrq.gov/ahrq-funded-projects/el-dorado-county-safety-net-technology-project-accel
     January 01, 2023 - ensure that the problem or barrier to getting appropriate health care is resolved and that clients learn

245. Engaging Patients to Enable Interoperable Lung Cancer Decision Support at Scale | Digital Healthcare Research
     digital.ahrq.gov/ahrq-funded-projects/engaging-patients-enable-interoperable-lung-cancer-decision-support-scale
     July 31, 2025 - MyLungHealth will be “prescribed” to eligible patients so they can learn about lung cancer screening;

246. Artificial Intelligence-Based Health Information Technology Tools to Optimize Critical Care Pharmacist Resources Through Adverse Drug Event Prediction | Digital Healthcare Research
     digital.ahrq.gov/ahrq-funded-projects/artificial-intelligence-based-health-it-tools-optimize-critical-care
     January 01, 2025 - Artificial Intelligence-Based Health Information Technology Tools to Optimize Critical Care Pharmacist Resources Through Adverse Drug Event Prediction Project Description Publications Research Story Developing artificial intelligence-based health information technol…

247. 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…

248. Improving Health Care Quality through Health IT for Persons with Intellectual Disabilities: A Final Report and Lessons Learned (pdf file)
     digital.ahrq.gov/sites/default/files/docs/publication/r21hs018766-rimmer-final-report-2012.pdf
     January 01, 2012 - Participants felt that the PHR-ID was easy to learn (78%) and use (72%). … consistent throughout the record 17 13 (76.4) 2 (11.8) 2 (11.8) 2.18 (.88) Most people will learn … Forty-four percent of participants felt that they needed to learn more before they could use the PHR … ) I feel very confident using the PHR 17 5 (29.4) 2 (11.8) 10 (58.8) 3.29 (1.11) I need to learn

249. Patient Computer Use (pdf file)
     digital.ahrq.gov/sites/default/files/docs/survey/patient-use-computer.pdf
     June 16, 2021 - Overall, how interested would you be to learn more about how to use the Internet and email to communicate

250. The RHIO as Convener and Catalyst: The Birth of EHR of Rhode Island. (pdf file)
     digital.ahrq.gov/sites/default/files/docs/page/2006Adams_051311comp.pdf
     June 05, 2006 - guiding principles (and practice them) – Invite the early adopter/opinion leaders to participate – Learn

251. 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…

252. 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…

253. Synthesizing Lessons Learned Using Health Information Technology | Digital Healthcare Research
     digital.ahrq.gov/ahrq-funded-projects/synthesizing-lessons-learned-using-health-information-technology
     January 01, 2023 - Synthesizing Lessons Learned Using Health Information Technology Project Final Report ( PDF , 182.32 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 represent the vie…

254. Detecting Med (Medication) Errors in Rural Hospitals Using Technology - 2008 | Digital Healthcare Research
     digital.ahrq.gov/ahrq-funded-projects/detecting-med-medication-errors-rural-hospitals-using-technology/annual-summary/2008
     January 01, 2008 - It is essential to assure hospital administrators that the reporting system is easy to learn, easy to

255. 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…

256. Healthy Teens TXT ME; IT to Change Teen Health Risk Behaviors - 2010 | Digital Healthcare Research
     digital.ahrq.gov/ahrq-funded-projects/healthy-teens-txt-me-it-change-teen-health-risk-behaviors/annual-summary/2010
     January 01, 2010 - of those who expressed interest in more frequent exercise provided telephone contact information to learn

257. Using Health Information Technology to Support Population-Based Clinical Practice - 2012 | Digital Healthcare Research
     digital.ahrq.gov/ahrq-funded-projects/using-health-information-technology-support-population-based-clinical-practice/annual-summary/2012
     January 01, 2012 - This site serves as a companion tool that clinics can give patients who want to learn more about conditions

258. Optimizing Medication History Value in Clinical Encounters with Elderly Patients - 2011 | Digital Healthcare Research
     digital.ahrq.gov/ahrq-funded-projects/optimizing-medication-history-value-clinical-encounters-elderly-patients/annual-summary/2011
     January 01, 2011 - , the research team developed the algorithms and worked with an e-prescribing software developer to learn

259. Baron RJ et al. 2005 "Electronic health records: just around the corner? Or over the cliff?" | Digital Healthcare Research
     digital.ahrq.gov/health-it-tools-and-resources/workflow-assessment-health-it-toolkit/experience/baron-rj-et-al-2005
     January 01, 2005 - The medical assistants had to record vital signs and chief symptoms in the computer and had to learn

260. 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…