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Purpose: Patient-reported outcomes and experiences (PRO) data are an integral component of health care quality measurement and PROs are now being collected by many healthcare systems. However, hospital organizational capacity-building for the collection and sharing of PROs is a complex process. We sought to identify the factors that facilitated capacity-building for PRO data collection in a nascent quality improvement learning collaborative of 16 hospitals that has the goal of improving the childbirth experience. Description: We used standard qualitative case study methodologies based on a conceptual framework that hypothesizes that adequate organizational incentives and capacities allow successful achievement of project milestones in a collaborative setting. The 4 project milestones considered in this study were: (1) Agreements; (2) System Design; (3) System Development and Operations; and (4) Implementation. To evaluate the success of reaching each milestone, critical incidents were logged and tracked to determine the capacities and incentives needed to resolve them. Assessment: The pace of the implementation of PRO data collection through the 4 milestones was uneven across hospitals and largely dependent on limited hospital capacities in the following 8 dimensions: (1) Incentives; (2) Leadership; (3) Policies; (4) Operating systems; (5) Information technology; (6) Legal aspects; (7) Cross-hospital collaboration; and (8) Patient engagement. From this case study, a trajectory for capacity-building in each dimension is discussed. Conclusion: The implementation of PRO data collection in a quality improvement learning collaborative was dependent on multiple organizational capacities for the achievement of project milestones. Significance: Patient-Reported Outcomes (PRO) are measures of a patient's health status. PROs are self-reported and do not require interpretation by the provider. PROs are being collected by many healthcare systems as a patient-centered approach to measuring and reporting healthcare quality. This case study outlines the critical issues involved in collecting PRO data and identifies the factors that facilitate capacity-building for PRO data collection. It provides an example of how the PRO data could be applied to improve patient satisfaction with the childbirth hospital experience. [ABSTRACT FROM AUTHOR]

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]

Objective: Because postpartum hemorrhage may result from factors related to obstetrical practice patterns, we examined the variability of postpartum hemorrhage and related risk factors (obstetrical trauma, chorioamnionitis, and protracted labor) across hospital types and hospitals in California. Methods: Linked birth certificate and hospital discharge data from 507,410 births in California in 1997 were analyzed. Cases were identified using International Classification of Diseases, Ninth Edition, Clinical Modification (ICD-9-CM) codes. Comparisons were made across hospital types and individual hospitals. Risk adjustments were made using 1) sample restriction to a subset of 324,671 low-risk women, and 2) Bayesian hierarchical logistic regression model to simultaneously quantify the effects of patient-level and hospital-level risk factors. Results: Postpartum hemorrhage complicated 2.4% of live births. The incidence ranged from 1.6% for corporate hospitals to 4.9% for university hospitals in the full sample, and from 1.4% for corporate hospitals to 3.9% for university hospitals in the low-risk sample. Low-risk women who delivered at government, HMO and university hospitals had two- to threefold increased odds (odds ratios 1.98 to 2.71; 95% confidence sets ranged from 1.52 to 4.62) of having postpartum hemorrhage compared to women who delivered at corporate hospitals, irrespective of patient-level characteristics. They also had significantly higher rates of obstetrical trauma and chorioamnionitis. Greater variations were observed across individual hospitals. Conclusion: The incidence of postpartum hemorrhage and related risk factors varied substantially across hospital types and hospitals in California. Further studies using primary data sources are needed to determine whether these variations are related to the processesof care. [ABSTRACT FROM AUTHOR]