4.7 Article

Trends in Neonatal Intensive Care Unit Utilization in a Large Integrated Health Care System

期刊

JAMA NETWORK OPEN
卷 3, 期 6, 页码 -

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AMER MEDICAL ASSOC
DOI: 10.1001/jamanetworkopen.2020.5239

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资金

  1. Kaiser Permanente Direct Community Benefit Funds

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Question How are neonatal intensive care unit (NICU) admission rates and NICU patient-days changing over time for various birth weight, gestational age, and acuity subgroups? Findings In this cohort study of neonates in a large integrated health care system, the risk-adjusted NICU admission rate and NICU patient-days decreased from 2010 through 2018 without an increase in readmission or mortality rates. The decrease was associated with the high gestational age and birth weight subgroup. Meaning These findings suggest that substantial decreases in NICU utilization across large birth populations are possible, and the remaining unexplained variation suggests that further changes are also possible. Importance There are few population-based studies addressing trends in neonatal intensive care unit (NICU) admission and NICU patient-days, especially in the subpopulation that, by gestational age (GA) and birth weight (BW), might otherwise be able to stay in the room with their mothers. Objective To describe population-based trends in NICU admissions, NICU patient-days, readmissions, and mortality in the birth population of a large integrated health care system. Design, Setting, and Participants This cohort study was conducted using data extracted from electronic medical records at Kaiser Permanente Southern California (KPSC) health care system. Participants included all women who gave birth at KPSC hospitals and their newborns from January 1, 2010, through December 31, 2018. Data extraction was limited to data entry fields whose contents were either numbers or fixed categorical choices. Rates of NICU admission, NICU patient-days, readmission rates, and mortality rates were measured in the total population, in newborns with GA 35 weeks or greater and BW 2000 g or more (high GA and BW group), and in the remaining newborns (low GA and BW group). Admissions to the NICU and NICU patient-days were risk adjusted with a machine learning model based on demographic and clinical characteristics before NICU admission. Changes in the trends were assessed with 2-sided correlated seasonal Mann-Kendall test. Data analysis was performed in August 2019. Exposures Admission to the NICU and NICU patient-days among the birth cohort. Main Outcomes and Measures The primary outcomes were NICU admission and NICU patient-days in the total neonatal population and GA and BW subgroups. The secondary outcomes were readmission and mortality rates. Results Over the study period there were 320 340 births (mean [SD] age of mothers, 30.1 [5.7] years; mean [SD] gestational age, 38.6 [1.97] weeks; mean [SD] birth weight, 3302 [573] g). The risk-adjusted NICU admission rate decreased from a mean of 14.5% (95% CI, 14.2%-14.7%) to 10.9% (95% CI, 10.7%-11.7%) (P for trend = .002); 92% of the change was associated with changes in the care of newborns in the high GA and BW group. The number of risk-adjusted NICU patient-days per birth decreased from a mean of 1.50 patient-days (95% CI, 1.43-1.54 patient-days) to 1.40 patient-days (95% CI, 1.36-1.48 patient-days) (P for trend = .03); 70% of the change was associated with newborns in the high GA and BW group. The unadjusted 30-day readmission rates and mortality rates did not change. Conclusions and Relevance Admission rates to the NICU and numbers of NICU patient-days decreased over the study period without an increase in readmissions or mortality. The observed decrease was associated with the high GA and BW newborn population. How much of this decrease is attributable to intercurrent health care systemwide quality improvement initiatives would require further investigation. The remaining unexplained variation suggests that further changes are also possible. This cohort study describes population-based trends in neonatal intensive care unit admissions and patient-days, readmissions, and mortality rates in the birth population of a large integrated health care system.

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