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Assessment and Evaluation of the High Risk Neonate: The NICU Network Neurobehavioral Scale
Published on: August 25, 2014
Computer-enhanced neonatology practice evolution in an academic medical center. NICU Clinical Effectiveness Task
T F Myers1, H H Venable, J A Hansen
1Neonatal Intensive Care Unit, Ronald McDonald Children's Hospital, Loyola University Chicago, Maywood, IL 60153, USA.
Abstract:
The U.S. health care system is evolving as a result of market-place forces that demand optimal medical outcomes, cost effectiveness, and improved customer service. These demands may be in conflict with the mission of an academic neonatal intensive care unit (NICU). For more than 5 years, we have used computer-enhanced clinical practice evolution to improve quality while reducing costs. The multidisciplinary NICU Clinical Effectiveness Task Force used the Quality/Cost Improvement Cycle in an evidenced-based, data-driven approach to clinical practice change. Merger of the Neonatal Clinical Database permitted birth weight-specific cost reporting. Specific practice patterns in the Pharmacy, Clinical Laboratory, Respiratory Therapy, and Radiology cost centers were targeted for improvement based on the medical literature. Customized interactive physician order-entry pathways were created within the existing medical ordering module of the Medical Information System. Birth weight-specific neonatal survival rates were unchanged. A dramatic reduction in neonatal medication errors from 3.2 to 0.6 errors per 1000 patient days occurred. Changes in targeted clinical practices were documented. A substantial decrease in average total hospital cost per infant and average length of stay was demonstrated for infants whose birth weights were less than 1001 gm. In conclusion, clinical practices can be changed while outcomes are improved and cost is reduced in an academic NICU through implementation of computer-enhanced clinical practice evolution. There are many remaining questions regarding the best neonatal practices to optimize outcome and minimize cost.
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