Examining the Trade-off Between NICU Length of Stay and Postdischarge Monitoring: An Instrumental Variables Approach.

EXECUTIVE SUMMARY: Treatment of very low birth weight infants in a neonatal intensive care unit (NICU) can be expensive, particularly in rural areas, but may potentially reduce long-term treatment costs and improve short- and long-term health outcomes. Few studies look at this trade-off. We employed an instrumental variables approach (fuzzy discontinuity) based on changes in practice for the treatment of very low birth weight infants in a perinatal referral center's NICU in 2000-2001. The strategy of keeping infants in a NICU longer reduced the likelihood of discharge with an apnea/cardio monitor. The primary instrumental variables specification estimated that every additional 100 g of discharge weight reduced the likelihood of discharge with an apnea/cardio monitor by 4.8%. Extending an infant's length of stay (LOS) thus has important benefits. Greater expenses on days in the NICU are partially compensated by reduced monitoring post discharge. In contexts where postdischarge monitoring is particularly difficult or expensive, extending LOS may be cost effective and potentially improve outcomes.

Thinking outside the curve, part II: modeling fetal-infant mortality.

BACKGROUND: Greater epidemiologic understanding of the relationships among fetal-infant mortality and its prognostic factors, including birthweight, could have vast public health implications. A key step toward that understanding is a realistic and tractable framework for analyzing birthweight distributions and fetal-infant mortality. The present paper is the second of a two-part series that introduces such a framework. METHODS: We propose estimating birthweight-specific mortality within each component of a normal mixture model representing a birthweight distribution, the number of components having been determined from the data rather than fixed a priori. RESULTS: We address a number of methodological issues related to our proposal, including the construction of confidence intervals for mortality risk at any given birthweight within a component, for odds ratios comparing mortality within two different components from the same population, and for odds ratios comparing mortality within analogous components from two different populations. As an illustration we find that, for a population of white singleton infants, the odds of mortality at 3000 g are an estimated 4.15 times as large in component 2 of a 4-component normal mixture model as in component 4 (95% confidence interval, 2.04 to 8.43). We also outline an extension of our framework through which covariates could be probabilistically related to mixture components. This extension might allow the assertion of approximate correspondences between mixture components and identifiable subpopulations. CONCLUSIONS: The framework developed in this paper does not require infants from compromised pregnancies to share a common birthweight-specific mortality curve, much less assume the existence of an interval of birthweights over which all infants have the same curve. Hence, the present framework can reveal heterogeneity in mortality that is undetectable via a contaminated normal model or a 2-component normal mixture model.

Thinking outside the curve, part I: modeling birthweight distribution.

BACKGROUND: Greater epidemiologic understanding of the relationships among fetal-infant mortality and its prognostic factors, including birthweight, could have vast public health implications. A key step toward that understanding is a realistic and tractable framework for analyzing birthweight distributions and fetal-infant mortality. The present paper is the first of a two-part series that introduces such a framework. METHODS: We propose describing a birthweight distribution via a normal mixture model in which the number of components is determined from the data using a model selection criterion rather than fixed a priori. RESULTS: We address a number of methodological issues, including how the number of components selected depends on the sample size, how the choice of model selection criterion influences the results, and how estimates of mixture model parameters based on multiple samples from the same population can be combined to produce confidence intervals. As an illustration, we find that a 4-component normal mixture model reasonably describes the birthweight distribution for a population of white singleton infants born to heavily smoking mothers. We also compare this 4-component normal mixture model to two competitors from the existing literature: a contaminated normal model and a 2-component normal mixture model. In a second illustration, we discover that a 6-component normal mixture model may be more appropriate than a 4-component normal mixture model for a general population of black singletons. CONCLUSIONS: The framework developed in this paper avoids assuming the existence of an interval of birthweights over which there are no compromised pregnancies and does not constrain birthweights within compromised pregnancies to be normally distributed. Thus, the present framework can reveal heterogeneity in birthweight that is undetectable via a contaminated normal model or a 2-component normal mixture model.

Predictors of intimate partner problem-related suicides among suicide decedents in Kentucky.

BACKGROUND: Suicide is the 10th leading cause of death in the United States. Furthermore, intimate partner problems are amid the top precipitating circumstances among suicide decedents. The aim of this study was to determine circumstantial associations of intimate partner problem-related suicides in suicide decedents in Kentucky. METHODS: All suicides that were reported to the Kentucky Violent Death Reporting System between 2005 and 2012 were eligible for this study. Multiple logistic regression was used to explore predictors (precipitating health-related problems, life stressors, and criminal/legal issues) of intimate partner problem-related suicides. RESULTS: Of the 4,754 suicides, included in this study, approximately 17% had intimate partner problems prior to suicide. In the adjusted analysis, mental health issues, alcohol problems, history of suicides attempts, suicides precipitated by another crime, and other legal problems increased the odds of having an intimate partner-related suicide. However, having physical health problems, prior to the suicide, decreased the odds of intimate partner-related suicide. CONCLUSIONS: These results provide insight for the development of suicide interventions for individuals with intimate partner problems by targeting risk factors that are prevalent among this population. Moreover, these results may help marriage/relationship and/or family/divorce court representatives identify individuals with intimate partner problems more at risk for suicide and alleviate the influence these suicide risk factors have on individuals experiencing Intimate partner problems.

Identifying health disparities and social inequities affecting childbearing women and infants.

This article presents health disparities and social inequities that may underlie adverse outcomes for childbearing women and infants in the United States. It also presents Internet-accessible databases that nurses can use to assess maternal and infant health disparities at a national or state level. Such assessments are basic to planning programs to address gaps in health care and advocating for practice and policy changes to improve the health care of childbearing women and infants.