Eric S. Kirkendall

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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 neonatal intensive care unit (NICU) environment. Objective This paper presents two phenotyping AE and ME(More)
Microbiology study results are necessary for conducting many comparative effectiveness research studies. Unlike core laboratory test results, microbiology results have a complex structure. Federating and integrating microbiology data from six disparate electronic medical record systems is challenging and requires a team of varied skills. The PHIS+(More)
OBJECTIVE To evaluate a proposed natural language processing (NLP) and machine-learning based automated method to risk stratify abdominal pain patients by analyzing the content of the electronic health record (EHR). METHODS We analyzed the EHRs of a random sample of 2100 pediatric emergency department (ED) patients with abdominal pain, including all with(More)
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 nutrition, and insulin using the electronic health record (EHR); to evaluate rates of MAEs in neonatal care; and to compare the performance of(More)
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 neonatal intensive care unit (NICU) environment. OBJECTIVE This paper presents two phenotyping AE and ME(More)
OBJECTIVES To examine healthcare worker's perceptions, expectations, and experiences regarding how work processes, patient-related safety, and care were affected when a quaternary care center transitioned from one computerized provider order entry (CPOE) system to a full electronic health record (EHR). METHODS The I-SEE survey was administered prior to(More)
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