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Objectives The goals of interconception care are to optimize women's health and encourage adequate spacing between pregnancies. Our study calculated trends in interpregnancy interval (IPI) patterns and measured the association of differing intervals with birth outcomes in California. Methods Women with 'non-first birth' deliveries in California hospitals from 2007 to 2009 were identified in a linked birth certificate and patient discharge dataset and divided into three IPI birth categories: <6, 6-17, and 18-50 months. Trends over the study period were tested using the Cochran-Armitage two-sided linear trend test. Chi square tests were used to test the association between IPI and patient characteristics and selected singleton adverse birth outcomes. Results Of 645,529 deliveries identified as non-first births, 5.6 % had an IPI <6 months, 33.1 % had an IPI of 6-17 months, and 61.3 % had an IPI of 18-50 months. The prevalence of IPI <6 months declined over the 3-year period (5.8 % in 2007 to 5.3 % in 2009, trend p value <0.0001).Women with an IPI <6 months had a significantly higher prevalence of early preterm birth (<34 weeks), low birthweight (<2500 g), neonatal complications, neonatal death and severe maternal complications than women with a 6-17 month or 18-50 month IPI (p < 0.005). Comparing those with a 6-17 month vs 18-50 month IPI, there were increased early preterm births and decreased maternal complications, complicated delivery, and stillbirth/intrauterine fetal deaths among those with a shorter IPI. Conclusions for Practice In California, women with an IPI <6 months were at increased risk for several birth outcomes, including composite morbidity measures. [ABSTRACT FROM AUTHOR]

The tracking of elective deliveries (ED) prior to 39 gestational weeks has become a mandatory requirement for all hospitals with ≥1,100 deliveries for accreditation by The Joint Commission (TJC); however, the feasibility and accuracy of monitoring efforts remain problematic for many hospitals. Here, we evaluated the feasibility of three operational approaches to tracking ED. We used mixed methods to evaluate the feasibility of 3 different approaches to tracking ED: (1) using administrative data, (2) using electronic medical record (EMR) data, and (3) using targeted data collection in a county-wide quality improvement (QI) effort. For (1), we analyzed data from the California 2009 linked birth cohort dataset, and calculated hospital rates of ED using TJC technical specifications. For (2), we performed a case study of a project that recruited hospitals to provide EMR data for the TJC measure calculation. For (3), we performed a case study of a project that recruited hospitals to prospectively track elective inductions of labor. For (1), hospital discharge data were insufficient without supplementation from the EMR or birth certificate. For (2), legal and operational issues surrounding data sharing, and non-standardized data elements prohibited hospital participation. For (3), the QI approach successfully established policies and data collection systems yet lacked infrastructure to assure sustainability at a hospital or regional level. In summary, ED tracking required the coordination and support of multiple resources to enable hospitals to satisfactorily report on this measure. [ABSTRACT FROM AUTHOR]

Background: In 2003, the Agency for Healthcare Quality and Research (AHRQ) published its Quality Indicators for healthcare, and set out methodological criteria for the evaluation of potential candidates. Objectives: Because perinatal infections may result from poor obstetrical practices, we intended to describe the variability of maternal and congenital neonatal infections across different types of hospital ownership (e.g., not for profit, government), and to assess whether rates of these infections meet criteria as quality indicators. Research Design: Population-based cohort study. Subjects: All laboring women without maternal, fetal, or placental complications who delivered in California in 1997, and their neonates, as reported through hospital discharge data. Measures: A Bayesian hierarchical logistic regression model was used to quantify the effects of both “patient-level” risk factors such as parity and prior cesarean history, and “hospital-level” risk factors such as ownership and teaching status. Results: The 308,841 mother–newborn pairs in this low-risk study population delivered at 281 hospitals; 0.39% had uterine infections and 1.3% had neonatal infections. Hospital ownership and teaching status were strongly associated with perinatal infection. Secondly, methods used to estimate and analyze hospital-specific infection rates identified hospitals with exceptionally high rates. Twenty-eight hospitals had neonatal infection rates that ranged from 3% to 28%. Conclusions: The methods presented here were consistent with AHRQ methods and criteria for potential Quality Indicators. They also identified hospitals with exceptionally high rates of infectious morbidity. The relationship between hospital ownership and obstetrical practice patterns, and the feasibility of practice improvement, remain to be studied. [ABSTRACT FROM AUTHOR]