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Automated detection of medication administration errors in neonatal intensive care.
Li Q, Kirkendall ES, Hall ES, Ni Y, Lingren T, Kaiser M, Lingren N, Zhai H, Solti I, Melton K. Li Q, et al. J Biomed Inform. 2015 Oct;57:124-33. doi: 10.1016/j.jbi.2015.07.012. Epub 2015 Jul 17. J Biomed Inform. 2015. PMID: 26190267 Free PMC article.
OBJECTIVE: To improve neonatal patient safety through automated detection of medication administration errors (MAEs) in high alert medications including narcotics, vasoactive medication, intravenous fluids, parenteral nutrit …
OBJECTIVE: To improve neonatal patient safety through automated detection of medication administration
Designing and evaluating an automated system for real-time medication administration error detection in a neonatal intensive care unit.
Ni Y, Lingren T, Hall ES, Leonard M, Melton K, Kirkendall ES. Ni Y, et al. J Am Med Inform Assoc. 2018 May 1;25(5):555-563. doi: 10.1093/jamia/ocx156. J Am Med Inform Assoc. 2018. PMID: 29329456 Free PMC article.
BACKGROUND: Timely identification of medication administration errors (MAEs) promises great benefits for mitigating medication errors and associated harm. ...METHODS: Our prospective observational study included automated MAE detection
BACKGROUND: Timely identification of medication administration errors (MAEs) promises great benefits for mitigating …
Integrating and Evaluating the Data Quality and Utility of Smart Pump Information in Detecting Medication Administration Errors: Evaluation Study.
Ni Y, Lingren T, Huth H, Timmons K, Melton K, Kirkendall E. Ni Y, et al. JMIR Med Inform. 2020 Sep 2;8(9):e19774. doi: 10.2196/19774. JMIR Med Inform. 2020. PMID: 32876578 Free PMC article.
OBJECTIVE: This study aims to evaluate the quality and utility of SPRs incorporated with EHR data in detecting medication administration errors. Our overarching hypothesis is that SPRs would contribute unique information in the med-ication use process, …
OBJECTIVE: This study aims to evaluate the quality and utility of SPRs incorporated with EHR data in detecting medication a
Phenotyping for patient safety: algorithm development for electronic health record based automated adverse event and medical error detection in neonatal intensive care.
Li Q, Melton K, Lingren T, Kirkendall ES, Hall E, Zhai H, Ni Y, Kaiser M, Stoutenborough L, Solti I. Li Q, et al. J Am Med Inform Assoc. 2014 Sep-Oct;21(5):776-84. doi: 10.1136/amiajnl-2013-001914. Epub 2014 Jan 8. J Am Med Inform Assoc. 2014. PMID: 24401171 Free PMC article.
BACKGROUND: Although electronic health records (EHRs) have the potential to provide a foundation for quality and safety algorithms, few studies have measured their impact on automated adverse event (AE) and medical error (ME) detection within the ne
BACKGROUND: Although electronic health records (EHRs) have the potential to provide a foundation for quality and safety algorithms, few stud …
Measuring patient safety in neonatology.
Suresh GK. Suresh GK. Am J Perinatol. 2012 Jan;29(1):19-26. doi: 10.1055/s-0031-1286183. Epub 2011 Aug 30. Am J Perinatol. 2012. PMID: 21879457 Review.
Measurement of patient safety serves to identify opportunities to improve safety within a neonatal intensive care unit (NICU), compare the safety of care provided by different NICUs, determine changes in response to safety interventions or programs, fo …
Measurement of patient safety serves to identify opportunities to improve safety within a neonatal intensive care unit …
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