作者: Jean Guglielminotti , Ruth Landau , Cynthia A. Wong , Guohua Li
DOI: 10.1007/S10995-018-2596-9
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摘要: Background The incidence of severe maternal morbidity (SMM) during childbirth is increasing in the United States. A better characterization risk factors for SMM may identify targets improving outcomes. This study aims to characterize patient-, hospital-, and neighborhood-level associated with childbirth. Methods was identified 2013-2014 State Inpatients Database New York. Hospital neighborhood characteristics were abstracted from American Association Area Health Resources files. Multilevel modeling used SMM, without blood transfusion, its between-hospital variation. Results 403,116 delivery-related discharges 139 hospitals analyzed; 1557 (0.39%) recorded transfusion. In final multilevel model, 7 patient-level a greater than fourfold increase SMM: pulmonary hypertension, postpartum hemorrhage, placenta accreta, chronic kidney disease, cardiac conduction disorders, emergent cesarean delivery, preeclampsia. Three hospital-level proportion non-White patients, Medicaid beneficiaries, coding intensity. No predictive SMM. variation explained by model 23.5 23.2% related factors. 55% variation, primarily Similar results observed Conclusions confirms association between It identifies as major driver Efforts improve outcomes should target