Changing the conversation: applying a health equity framework to maternal mortality reviews.

The risk of maternal death in the United States is higher than peer nations and is rising and varies dramatically by the race and place of residence of the woman. Critical efforts to reduce maternal mortality include patient risk stratification and system-level quality improvement efforts targeting specific aspects of clinical care. These efforts are important for addressing the causes of an individual's risk, but research to date suggests that individual risk factors alone do not adequately explain between-group disparities in pregnancy-related death by race, ethnicity, or geography. The holistic review and multidisciplinary makeup of maternal mortality review committees make them well positioned to fill knowledge gaps about the drivers of racial and geographic inequity in maternal death. However, committees may lack the conceptual framework, contextual data, and evidence base needed to identify community-based contributing factors to death and, when appropriate, to make recommendations for future action. By incorporating a multileveled, theory-grounded framework for causes of health inequity, along with indicators of the community vital signs, the social and community context in which women live, work, and seek health care, maternal mortality review committees may identify novel underlying factors at the community level that enhance understanding of racial and geographic inequity in maternal mortality. By considering evidence-informed community and regional resources and policies for addressing these factors, novel prevention recommendations, including recommendations that extend outside the realm of the formal health care system, may emerge.

Rate of Second and Third Trimester Weight Gain and Preterm Delivery Among Underweight and Normal Weight Women.

Objectives Low gestational weight gain (GWG) in the second and third trimesters has been associated with increased risk of preterm delivery (PTD) among women with a body mass index (BMI) < 25 mg/m(2). However, few studies have examined whether this association differs by the assumptions made for first trimester gain or by the reason for PTD. Methods We examined singleton pregnancies during 2000-2008 among women with a BMI < 25 kg/m(2) who delivered a live-birth ≥28 weeks gestation (n = 12,526). Women received care within one integrated health care delivery system and began prenatal care ≤13 weeks. Using antenatal weights measured during clinic visits, we interpolated GWG at 13 weeks gestation then estimated rate of GWG (GWGrate) during the second and third trimesters of pregnancy. We also estimated GWGrate using the common assumption of a 2-kg gain for all women by 13 weeks. We examined the covariate-adjusted association between quartiles of GWGrate and PTD (28-36 weeks gestation) using logistic regression. We also examined associations by reason for PTD [premature rupture of membranes (PROM), spontaneous labor, or medically indicated]. Results Mean GWGrate did not differ among term and preterm pregnancies regardless of interpolated or assumed GWG at 13 weeks. However, only with GWGrate estimated from interpolated GWG at 13 weeks, we observed a U-shaped relationship where odds of PTD increased with GWGrate in the lowest (OR 1.36, 95 % CI 1.10, 1.69) or highest quartile (OR 1.49, 95 % CI 1.20, 1.85) compared to GWGrate within the second quartile. Further stratifying by reason, GWGrate in the lowest quartile was positively associated with spontaneous PTD while GWGrate in the highest quartile was positively associated with PROM and medically indicated PTD. Conclusions Accurate estimates of first trimester GWG are needed. Common assumptions applied to all pregnancies may obscure the association between GWGrate and PTD. Further research is needed to fully understand whether these associations are causal or related to common antecedents.

Associations of Gestational Weight Gain with Preterm Birth among Underweight and Normal Weight Women.

Studies report increased risk of preterm birth (PTB) among underweight and normal weight women with low gestational weight gain (GWG). However, most studies examined GWG over gestational periods that differ by term and preterm which may have biased associations because GWG rate changes over the course of pregnancy. Furthermore, few studies have specifically examined the amount and pattern of GWG early in pregnancy as a predictor of PTB. Within one integrated health care delivery system, we examined 12,526 singleton pregnancies between 2000 and 2008 among women with a body mass index <25 kg/m(2), who began prenatal care in the first trimester and delivered a live-birth >28 weeks gestation. Using self-reported pregravid weight and serial measured antenatal weights, we estimated GWG and the area under the GWG curve (AUC; an index of pattern of GWG) during the first and second trimesters of pregnancy (≤28 weeks). Using logistic regression adjusted for covariates, we examined associations between each GWG measure, categorized into quartiles, and PTB (<37 weeks gestation). We additionally examined associations according to the reason for PTB by developing a novel algorithm using diagnoses and procedure codes. Low GWG in the first and second trimesters was not associated with PTB [aOR 1.11, (95% CI 0.90, 1.38) with GWG <8.2 kg by 28 weeks compared to pregnancies with GWG >12.9]. Similarly, pattern of GWG was not associated with PTB. Our findings do not support an association between GWG in the first and second trimester and PTB among underweight and normal weight women.

Development of an algorithm to identify pregnancy episodes in an integrated health care delivery system.

OBJECTIVE: To develop and validate a software algorithm to detect pregnancy episodes and maternal morbidities using automated data. DATA SOURCES/STUDY SETTING: Automated records from a large integrated health care delivery system (IHDS), 1998-2001. STUDY DESIGN: Through complex linkages of multiple automated information sources, the algorithm estimated pregnancy histories. We evaluated the algorithm's accuracy by comparing selected elements of the pregnancy history obtained by the algorithm with the same elements manually abstracted from medical records by trained research staff. DATA COLLECTION/EXTRACTION METHODS: The algorithm searched for potential pregnancy indicators within diagnosis and procedure codes, as well as laboratory tests, pharmacy dispensings, and imaging procedures associated with pregnancy. PRINCIPAL FINDINGS: Among 32,847 women with potential pregnancy indicators, we identified 24,680 pregnancies occuring to 21,001 women. Percent agreement between the algorithm and medical records review on pregnancy outcome, gestational age, and pregnancy outcome date ranged from 91 percent to 98 percent. The validation results were used to refine the algorithm. CONCLUSIONS: This pregnancy episode grouper algorithm takes advantage of databases readily available in IHDS, and has important applications for health system management and clinical care. It can be used in other settings for ongoing surveillance and research on pregnancy outcomes, pregnancy-related morbidities, costs, and care patterns.