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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]

Objectives. We examined trends in maternal comorbidities in California. Methods. We conducted a retrospective cohort study of 1 551 017 California births using state-linked vital statistics and hospital discharge cohort data for 1999, 2002, and 2005. We used International Classification of Diseases, Ninth Revision, Clinical Modification codes to identify the following conditions, some of which were preexisting: maternal hypertension, diabetes, asthma, thyroid disorders, obesity, mental health conditions, substance abuse, and tobacco use. We estimated prevalence rates with hierarchical logistic regression models, adjusting for demographic shifts, and also examined racial/ethnic disparities. Results. The prevalence of these comorbidities increased over time for hospital admissions associated with childbirth, suggesting that pregnant women are getting sicker. Racial/ethnic disparities were also significant. In 2005, maternal hypertension affected more than 10% of all births to non-Hispanic Black mothers; maternal diabetes affected nearly 10% of births to Asian/Pacific Islander mothers (10% and 43% increases, respectively, since 1999). Chronic hypertension, diabetes, obesity, mental health conditions, and tobacco use among Native American women showed the largest increases. Conclusions. The prevalence of maternal comorbidities before and during pregnancy has risen substantially in California and demonstrates racial/ethnic disparity independent of demographic shifts. [ABSTRACT FROM AUTHOR]

OBJECTIVE: This study tested multivariate models exploring unit-level predictors of medication administration (MA) accuracy. BACKGROUND: During MA, nurses are both the last line of defense from medication-related errors and a potential perpetrator of error. Direct observation reveals safe practices and the accuracy of medication delivery. METHODS: Using a direct-observation, cross-sectional design, data submitted by 124 adult patient care units for 15 600 medication doses, from January 2009 to April 2010, were studied. RESULTS: Distractions and interruptions were the most common safe practice deviation. Characteristics of patient care units and RN hours of care affected nurses' safe practices and MA accuracy. Safe practices predict and mediate MA accuracy. A 5% decrease in safe practice deviations would reduce MA errors by 46% without any change in RN hours of care. CONCLUSION: Nurses' adherence to MA safe practices, combined with unit characteristics and staffing factors, has the potential to dramatically improve MA accuracy. [ABSTRACT FROM AUTHOR]

OBJECTIVE: Predictive models for falls, injury falls, and restraint prevalence were explored within nursing unit structures and processes of care. BACKGROUND: The patient care team is responsible for patient safety, and improving practice models may prevent injuries and improve patient safety. METHODS: Using unit-level self-reported data from 215 hospitals, falls, injury falls, and restraint prevalence were modeled with significant covariates as predictors. RESULTS: Fewer falls/injury falls were predicted by populations with fewer frail and at-risk patients, more unlicensed care hours, and prevention protocol implementation, but not staffing per se, restraint use, or RN expertise. Lower restraint use was predicted by fewer frail patients, shorter length of stay, more RN hours, more certified RNs, and implementation of fall prevention protocols. CONCLUSION: In the presence of risk, patient injuries and safety were improved by optimizing staffing skill mix and use of prevention protocols. [ABSTRACT FROM AUTHOR]