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321. 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

322. Improving Diabetes and Depression Self-Management Via Adaptive Mobile Messaging | Digital Healthcare Research
     digital.ahrq.gov/ahrq-funded-projects/improving-diabetes-and-depression-self-management-adaptive-mobile-messaging
     January 01, 2024 - Improving Diabetes and Depression Self-Management Via Adaptive Mobile Messaging Project Final Report ( PDF , 544.36 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 repr…

323. Ornstein, Steven | Digital Healthcare Research
     digital.ahrq.gov/principal-investigator/ornstein-steven
     January 01, 2023 - Ornstein, Steven Learning From Primary Care EHR Exemplars About Health IT Safety - Final Report Citation Ornstein S. Learning From Primary Care EHR Exemplars About Health IT Safety - Final Report. (Prepared by Medical University of South Carolina under Grant No. R21 HS024327).…

324. 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.

325. Learning from primary care meaningful use exemplars. | Digital Healthcare Research
     digital.ahrq.gov/ahrq-funded-projects/learning-primary-care-meaningful-use-exemplars/citation/learning-primary-care
     January 01, 2023 - Learning from primary care meaningful use exemplars. Citation Ornstein SM, Nemeth LS, Nietert PJ, et al. Learning from primary care meaningful use exemplars. J Am Board Fam Med 2015;28(3):360-70. PMID: 25957369. Link https://www.ncbi.nlm.nih.gov/pubmed/25957369 Principal Investigator …

326. Using the Electronic Health Record To Identify Children Likely To Suffer Last-Minute Surgery Cancellation | Digital Healthcare Research
     digital.ahrq.gov/ahrq-funded-projects/using-electronic-health-record-identify-children-likely-suffer-last-minute
     January 01, 2023 - Using the Electronic Health Record To Identify Children Likely To Suffer Last-Minute Surgery Cancellation Project Final Report ( PDF , 1.1 MB) Disclaimer Disclaimer The findings and conclusions in this document are those of the author(s), who are responsible for its content, and …

327. Optimal Methods for Notifying Clinicians About Epilepsy Surgery Patients | Digital Healthcare Research
     digital.ahrq.gov/ahrq-funded-projects/optimal-methods-notifying-clinicians-about-epilepsy-surgery-patients
     January 01, 2023 - Optimal Methods for Notifying Clinicians About Epilepsy Surgery Patients Project Final Report ( PDF , 647.83 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…

328. Machine learning approaches to identify nicknames from a statewide Health Information Exchange. | Digital Healthcare Research
     digital.ahrq.gov/ahrq-funded-projects/enhancing-patient-matching-support-operational-health-information-exchange/citation/machine
     January 01, 2023 - Machine learning approaches to identify nicknames from a statewide Health Information Exchange. Citation Kasthurirathne SN, Grannis SJ. Machine learning approaches to identify nicknames from a statewide Health Information Exchange. AMIA Jt Summits Transl Sci Proc. 2019 May 6;2019:639-647. PMID: 312590…

329. 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."

330. 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

331. Comparison of supervised machine learning and probabilistic approaches for record linkage. | Digital Healthcare Research
     digital.ahrq.gov/ahrq-funded-projects/enhancing-patient-matching-support-operational-health-information-exchange/citation/comparison
     January 01, 2023 - Comparison of supervised machine learning and probabilistic approaches for record linkage. Citation McNutt, A.T., Grannis, S.J., Bo, N., Xu, H., Kasthurirathne, S. N.(2020, March). Comparison of supervised machine learning and probabilistic approaches for record linkage. AMIA Informatics summit 2020 C…

332. Using machine learning techniques to develop forecasting algorithms for postoperative complications: protocol for a retrospective study. | Digital Healthcare Research
     digital.ahrq.gov/ahrq-funded-projects/anesthesiology-control-tower-feedback-alerts-supplement-treatment-actfast/citation/machine
     January 01, 2023 - Using machine learning techniques to develop forecasting algorithms for postoperative complications: protocol for a retrospective study. Citation Fritz BA, Chen Y, Murray-Torres TM, et al. Using machine learning techniques to develop forecasting algorithms for postoperative complications: protocol fo…

333. Achieving Individualized Precision Prevention (IPP) through Scalable Infrastructure Employing the USPSTF Recommendations in Computable Form | Digital Healthcare Research
     digital.ahrq.gov/ahrq-funded-projects/achieving-individualized-precision-prevention-ipp-through-scalable
     January 01, 2023 - Achieving Individualized Precision Prevention (IPP) through Scalable Infrastructure Employing the USPSTF Recommendations in Computable Form Project Final Report ( PDF , 696.89 KB) Disclaimer Disclaimer   The findings and conclusions in this document are those of the author(s), …

334. Using active learning to identify health Information technology related patient safety events. | Digital Healthcare Research
     digital.ahrq.gov/ahrq-funded-projects/developing-evidence-based-user-centered-design-and-implementation-guidelines/citation/using
     January 01, 2023 - Using active learning to identify health Information technology related patient safety events. Citation Fong A, Howe JL, Adams KT, et al. Using active learning to identify health Information technology related patient safety events. Appl Clin Inform 2017 Jan 18;8(1):35-46. PMID: 28097287. Link …

335. 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.

336. Learning from Primary Care Meaningful Use Exemplars | Digital Healthcare Research
     digital.ahrq.gov/ahrq-funded-projects/learning-primary-care-meaningful-use-exemplars
     January 01, 2023 - Learning from Primary Care Meaningful Use Exemplars Project Final Report ( PDF , 358.17 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 views of AHRQ. N…

337. National Center for Pediatric Practice Based Research and Learning - Final Report | Digital Healthcare Research
     digital.ahrq.gov/ahrq-funded-projects/national-center-pediatric-practice-based-research-and-learning/final-report
     January 01, 2023 - National Center for Pediatric Practice Based Research and Learning - Final Report Citation Fiks A. National Center for Pediatric Practice Based Research and Learning - Final Report. (Prepared by the American Academy of Pediatrics under Grant No. P30 HS021645). Rockville, MD: Agency for Healthcare Rese…

338. Lessons learned from implementation of a computerized application for pending tests at hospital discharge. | Digital Healthcare Research
     digital.ahrq.gov/ahrq-funded-projects/health-information-technology-and-improving-medication-use/citation/lessons
     January 01, 2023 - Lessons learned from implementation of a computerized application for pending tests at hospital discharge. Citation Dalal AK, Poon EG, Karson AS, et al. Lessons learned from implementation of a computerized application for pending tests at hospital discharge. J Hosp Med 2011 Jan;6(1):16-21. Link…

339. A machine learning approach to reclassifying miscellaneous patient safety event reports. | Digital Healthcare Research
     digital.ahrq.gov/ahrq-funded-projects/developing-evidence-based-user-centered-design-and-implementation-guidelines/citation/machine
     January 01, 2023 - A machine learning approach to reclassifying miscellaneous patient safety event reports. Citation Fong A, Behzad S, Pruitt Z, Ratwani RM. A machine learning approach to reclassifying miscellaneous patient safety event reports. J Patient Saf. 2021 Dec 1;17(8):e829-e833. doi: 10.1097/PTS.000000000000073…

340. Medical University of South Carolina | Digital Healthcare Research
     digital.ahrq.gov/organization/medical-university-south-carolina
     January 01, 2023 - Medical University of South Carolina Leveraging Health System Telehealth and Informatics Infrastructure to Create a Continuum of Services for COVID-19 Screening, Testing, and Treatment: A Learning Health System Approach Description This research aims to examine a health system…