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301. Synthesizing Lessons Learned Using Health Information Technology - Final Report | Digital Healthcare Research
     digital.ahrq.gov/ahrq-funded-projects/synthesizing-lessons-learned-using-health-information-technology/final-report
     January 01, 2023 - Synthesizing Lessons Learned Using Health Information Technology - Final Report Citation Nemeth L. Synthesizing Lessons Learned Using Health Information Technology - Final Report. (Prepared by the Medical University of South Carolina under Grant No. R03 HS018830). Rockville, MD: Agency for Healthcare …

302. AHRQ’s Digital Healthcare Research Program: Milestones and Achievements | Digital Healthcare Research
     digital.ahrq.gov/dhr-20/ahrq-digital-healthcare-research-program-milestones-achievements
     January 01, 2023 - We invite you to explore the detailed timeline below to learn more about the significant contributions

303. Exploring Clinically-relevant Image Retrieval for Diabetic Retinopahty Diagnosis - 2012 | Digital Healthcare Research
     digital.ahrq.gov/ahrq-funded-projects/exploring-clinically-relevant-image-retrieval-diabetic-retinopathy-diagnosis/annual-summary/2012
     January 01, 2012 - The team solicited feedback from an ophthalmologist to learn about the end-user’s experience with the

304. Retrospective | Digital Healthcare Research
     digital.ahrq.gov/research-method/retrospective
     January 01, 2025 - Retrospective A Machine Learning Health System to Integrate Care for Substance Misuse and HIV Treatment and Prevention Among Hospitalized Patients - Final Report Citation Held M., Thompson H. A Machine Learning Health System to Integrate Care for Substance Misuse and HIV Treat…

305. 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…

306. Project ECHO: Extension for Community Healthcare Outcomes - 2008 | Digital Healthcare Research
     digital.ahrq.gov/ahrq-funded-projects/project-echo-extension-community-healthcare-outcomes/annual-summary/2008
     January 01, 2008 - This particular form of case-based learning, called “learning loops,” allow community providers to learn

307. 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…

308. Using Health Information Technology to Improve Delivery of HPV Vaccine - 2011 | Digital Healthcare Research
     digital.ahrq.gov/ahrq-funded-projects/using-health-information-technology-improve-delivery-hpv-vaccine/annual-summary/2011
     January 01, 2011 - Rand will complete the following education objectives: 1) learn health informatics theory and be able

309. Secure Messaging in a Pediatric Respiratory Medicine Setting - 2009 | Digital Healthcare Research
     digital.ahrq.gov/ahrq-funded-projects/secure-messaging-pediatric-respiratory-medicine-setting/annual-summary/2009
     January 01, 2009 - Interviews with patients and guardians who did use the secure messaging system were conducted to learn

310. Exploring Clinically-relevant Image Retrieval for Diabetic Retinopathy Diagnosis (pdf file)
     digital.ahrq.gov/sites/default/files/docs/activity/r21hs019792-li-annual-summary-2012.pdf
     January 01, 2012 - The team solicited feedback from an ophthalmologist to learn about the end-user’s experience with the

311. 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…

312. Nemeth, Lynne | Digital Healthcare Research
     digital.ahrq.gov/principal-investigator/nemeth-lynne
     January 01, 2023 - Nemeth, Lynne Synthesizing Lessons Learned Using Health Information Technology - Final Report Citation Nemeth L. Synthesizing Lessons Learned Using Health Information Technology - Final Report. (Prepared by the Medical University of South Carolina under Grant No. R03 HS018830)…

313. Toolkit Available for Assessing the Impact of Health InformationTechnology on Workflow in Provider Offices (pdf file)
     digital.ahrq.gov/sites/default/files/docs/page/CarayonSuccessStory.pdf
     December 31, 2010 - They also conducted an environmental scan to learn what others were doing with regards to health IT

314. The Give Teens Vaccines Study - 2010 | Digital Healthcare Research
     digital.ahrq.gov/ahrq-funded-projects/give-teens-vaccines-study/activity/give-teens-vaccines-study/annual-summary/2010
     January 01, 2010 - project team conducted a pilot study involving interviews with 20 parent-clinician-adolescent triads, to learn

315. Partners in Safety: The Walworth County (Wisconsin) Patient Safety Council (pdf file)
     digital.ahrq.gov/sites/default/files/docs/page/2006LeonhardtPagel_052411comp.pdf
     June 01, 2006 - .” – “Doctors need to learn how we think.

316. Chicago Alliance of Community Health Centers Pioneers EHR Implementation with AHRQ Support | AHRQ Digital Healthcare Research: Informing Improvement in Care Quality, Safety, and Efficiency
     digital.ahrq.gov/ahrq-funded-projects/past-initiatives/transforming-healthcare-quality-through-health-it/chicago-alliance-community
     August 31, 2007 - You have to rethink things as you learn."

317. Leveraging Health IT to Test Solutions That Are Replicable, Scalable, and Improve Patient Safety | Digital Healthcare Research
     digital.ahrq.gov/2018-year-review/research-spotlights/leveraging-health-it-test-solutions-are-replicable-scalable-and
     January 01, 2018 - take advantage of the unique capacity of digital tools to allow clinicians and health care systems to learn

318. Health IT Hazard Manager Beta-Test (pdf file)
     digital.ahrq.gov/sites/default/files/docs/citation/HealthITHazardManagerFinalReport.pdf
     May 01, 2012 - Data aggregation at multiple levels: enabling CDOs (and health IT vendors and researchers) to learn … • IT production-support teams primarily learn about hazards from users, often when the hazard has … • Patient Safety teams typically learn about the subset of hazards that contribute to identifiable … • Prior to upgrading to a new product release, learn about hazards others have reported with that … • Learn which other vendors’ products frequently contribute to hazards when paired with their own

319. Case Study: Developing a State Medicaid Health IT Plan (SMHP): Lessons Learned From Oklahoma Medicaid | Digital Healthcare Research
     digital.ahrq.gov/ahrq-funded-projects/medicaid-and-chip/case-study-developing-state-medicaid-health-it-plan-smhp
     January 01, 2023 - Case Study: Developing a State Medicaid Health IT Plan (SMHP): Lessons Learned From Oklahoma Medicaid Case Study Developing a State Medicaid Health IT Plan (SMHP): Lessons Learned From Oklahoma Medicaid Prepared for: Agency for Healthcare Research and Quality U.S. Document Case Study: Developi…

320. A Geofencing-Based Adaptive Messaging System to Support Patient Self-Management of a Low-Sodium Diet in Hypertension | Digital Healthcare Research
     digital.ahrq.gov/ahrq-funded-projects/geofencing-based-adaptive-messaging-system-support-patient-self-management-low
     January 01, 2023 - Most felt it was easy to use and that others could learn to use it quickly.