Measuring Quality in Ethics Consultation.

For all of the emphasis on quality improvement-as well as the acknowledged overlap between assessment of the quality of healthcare services and clinical ethics-the quality of clinical ethics consultation has received scant attention, especially in terms of empirical measurement. Recognizing this need, the second edition of Core Competencies for Health Care Ethics Consultation1 identified four domains of ethics quality: (1) ethicality, (2) stakeholders' satisfaction, (3) resolution of the presenting conflict/dilemma, and (4) education that translates into knowledge. This study is the first, to our knowledge, to directly measure all of these domains. Here we describe the quality improvement process undertaken at a tertiary care academic medical center, as well as the tools developed to measure the quality of ethics consultation, which include post-consultation satisfaction surveys and weekly case conferences. The information gained through these tools helps to improve not only the process of ethics consultation, but also the measurement and assurance of quality.

Factors associated with infant sex and preterm birth status for selected birth defects from the National Birth Defects Prevention Study, 1997-2011.

BACKGROUND: Birth defects and preterm birth co-occur, with some overlapping risk factors. Many birth defects and preterm births tend to have a male preponderance. We explored potential risk factors impacting sex and preterm (<37 weeks of gestation) birth differences among infants with selected birth defects delivered from 1997 to 2011 using data from the National Birth Defects Prevention Study (NBDPS). METHODS: The NBDPS was a large multisite, population-based case-control study. Using random forests, we identified important predictors of male preterm, female preterm, and male term, each compared with female term births for each birth defect. Using logistic regression, we estimated odds ratios for associations between important predictors and sex-preterm birth status by birth defect. RESULTS: We examined 11,379 infants with nine specific birth defects. The top 10 most important predictors of sex-preterm birth status from the random forests varied greatly across the birth defects and sex-preterm comparisons within a given defect group, with several being novel factors. However, one consistency was that short interpregnancy interval was associated with sex-preterm birth status for many of the studied birth defects. Although obesity has been identified as a risk factor for preterm birth and birth defects in other research, it was not associated with sex-preterm birth status for any of the examined defects. CONCLUSIONS: We confirmed expected associations for sex-preterm birth status differences and found new potential risk factors for further exploration among the studied birth defects.

Patterns of multiple congenital anomalies in the National Birth Defect Prevention Study: Challenges and insights.

BACKGROUND: About 20%-30% of children with birth defects have multiple major birth defects in more than one organ system, often referred to as multiple congenital anomalies (MCAs). Evaluating the patterns of MCAs can provide clues to the underlying causes, pathogenic mechanisms, and developmental pathways. We sought to explore selected patterns of MCAs within the National Birth Defects Prevention Study (NBDPS), a population-based, case-control study that excluded cases attributed to known chromosomal or single-gene abnormalities. METHODS: We defined MCAs as having two or more NBDPS-eligible birth defects and calculated the adjusted observed-to-expected ratio for all observed MCA patterns using co-occurring defect analysis. RESULTS: Of the 50,186 case infants eligible for NBDPS, 2,734 (3.7%) had at least two eligible birth defects. We observed 209 distinct 2-way combinations of birth defects, 297 distinct 3-way combinations, 179 distinct 4-way combinations, and 69 distinct 5-way combinations. Sacral agenesis had the largest proportion of cases with MCAs (70%), whereas gastroschisis had the lowest (3%). Among the cases with MCAs, 63% had a heart defect, 23% had an oral cleft, and 21% had anorectal atresia/stenosis. Of the patterns with adjusted observed-to-expected ratios in the top 20%, most were consistent with the known associations or syndromes, including VATER/VACTERL association and CHARGE syndrome. CONCLUSIONS: Most but not all patterns that had the highest adjusted observed-to-expected ratios were instances of known syndromes or associations. These findings highlight the importance of considering birth defect combinations that suggest syndromic patterns in the absence of a formal syndromic diagnosis. New approaches for screening for sequences and associations, and VATER/VACTERL in particular, in surveillance systems with limited resources for manual review may be valuable for improving surveillance system quality. The observed MCA patterns within NBDPS may help focus future genetic studies by generating case groups of higher yield.

Maternal dietary caffeine consumption and risk of birth defects in the National Birth Defects Prevention Study, 1997-2011.

BACKGROUND: Caffeine consumption is common during pregnancy, but published associations with birth defects are mixed. We updated estimates of associations between prepregnancy caffeine consumption and 48 specific birth defects from the National Birth Defects Prevention Study (NBDPS) for deliveries from 1997 to 2011. METHODS: NBDPS was a large population-based case-control study conducted in 10 U.S. states. We categorized self-reported total dietary caffeine consumption (mg/day) from coffee, tea, soda, and chocolate as: <10, 10 to <100, 100 to <200, 200 to <300, and ≥ 300. We used logistic regression to estimate adjusted odds ratios (aORs [95% confidence intervals]). Analyses for defects with ≥5 exposed case children were adjusted for maternal race/ethnicity, age at delivery, body mass index, early pregnancy cigarette smoking and alcohol use, and study site. RESULTS: Our analysis included 30,285 case and 11,502 control children, with mothers of 52% and 54%, respectively, reporting consuming <100 mg caffeine, and 11% of mothers of both cases and controls reported consuming ≥300 mg per day. Low (10 to <100 mg/day) levels of prepregnancy caffeine consumption were associated with statistically significant increases in aORs (1.2-1.7) for 10 defects. Associations with high (≥300 mg/day) levels of caffeine were generally weaker, except for craniosynostosis and aortic stenosis (aORs = 1.3 [1.1-1.6], 1.6 [1.1-2.3]). CONCLUSIONS: Given the large number of estimates generated, some of the statistically significant results may be due to chance and thus the weakly increased aORs should be interpreted cautiously. This study supports previous observations suggesting lack of evidence for meaningful associations between caffeine consumption and the studied birth defects.

Dealing with highly skewed hospital length of stay distributions: The use of Gamma mixture models to study delivery hospitalizations.

The increased focus on addressing severe maternal morbidity and maternal mortality has led to studies investigating patient and hospital characteristics associated with longer hospital stays. Length of stay (LOS) for delivery hospitalizations has a strongly skewed distribution with the vast majority of LOS lasting two to three days in the United States. Prior studies typically focused on common LOSs and dealt with the long LOS distribution tail in ways to fit conventional statistical analyses (e.g., log transformation, trimming). This study demonstrates the use of Gamma mixture models to analyze the skewed LOS distribution. Gamma mixture models are flexible and, do not require data transformation or removal of outliers to accommodate many outcome distribution shapes, these models allow for the analysis of patients staying in the hospital for a longer time, which often includes those women experiencing worse outcomes. Random effects are included in the model to account for patients being treated within the same hospitals. Further, the role and influence of differing placements of covariates on the results is discussed in the context of distinct model specifications of the Gamma mixture regression model. The application of these models shows that they are robust to the placement of covariates and random effects. Using New York State data, the models showed that longer LOS for childbirth hospitalizations were more common in hospitals designated to accept more complicated deliveries, across hospital types, and among Black women. Primary insurance also was associated with LOS. Substantial variation between hospitals suggests the need to investigate protocols to standardize evidence-based medical care.