Development of an electronic health records datamart to support clinical and population health research.

INTRODUCTION: Electronic health record (EHR) data have emerged as an important resource for population health and clinical research. There have been significant efforts to leverage EHR data for research; however, given data security concerns and the complexity of the data, EHR data are frequently difficult to access and use for clinical studies. We describe the development of a Clinical Research Datamart (CRDM) that was developed to provide well-curated and easily accessible EHR data to Duke University investigators. METHODS: The CRDM was designed to (1) contain most of the patient-level data elements needed for research studies; (2) be directly accessible by individuals conducting statistical analyses (including Biostatistics, Epidemiology, and Research Design (BERD) core members); (3) be queried via a code-based system to promote reproducibility and consistency across studies; and (4) utilize a secure protected analytic workspace in which sensitive EHR data can be stored and analyzed. The CRDM utilizes data transformed for the PCORnet data network, and was augmented with additional data tables containing site-specific data elements to provide additional contextual information. RESULTS: We provide descriptions of ideal use cases and discuss dissemination and evaluation methods, including future work to expand the user base and track the use and impact of this data resource. CONCLUSIONS: The CRDM utilizes resources developed as part of the Clinical and Translational Science Awards (CTSAs) program and could be replicated by other institutions with CTSAs.

A Multidimensional Approach to Characterizing Psychosocial Health During Pregnancy.

Objectives Domains of psychosocial health have been separately connected to pregnancy outcomes. This study explores the relationship between five domains of psychosocial health and their joint association with prenatal health and pregnancy outcomes. Methods Women from a prospective cohort study in Durham, North Carolina were clustered based on measures of paternal support, perceived stress, social support, depression, and self-efficacy. Clusters were constructed using the K-means algorithm. We examined associations between psychosocial health and maternal health correlates, pregnancy intention, and pregnancy outcomes using Chi square tests and multivariable models. Results Three psychosocial health profiles were identified, with the first (Resilient; n = 509) characterized by low depression and perceived stress and high interpersonal support, paternal support, and self-efficacy. The second profile (Vulnerable; n = 278) was marked by high depression and perceived stress, and low interpersonal support, paternal support, and self-efficacy. The third profile (Moderate, n = 526) fell between the other profiles on all domains. Health correlates, pregnancy intention, and pregnancy outcomes varied significantly across profiles. Women with the vulnerable profile were more likely to have risky health correlates, have an unintended pregnancy, and deliver preterm. Women with the resilient profile had better birth outcomes and fewer deleterious health correlates, preconception and prenatally. Conclusions We posit that vulnerable psychosocial health, deleterious health correlates, and the stress which often accompanies pregnancy may interact to magnify risk during pregnancy. Identifying and intervening with women experiencing vulnerable psychosocial health may improve outcomes for women and their children.

Methods and initial findings from the Durham Diabetes Coalition: Integrating geospatial health technology and community interventions to reduce death and disability.

OBJECTIVE: The Durham Diabetes Coalition (DDC) was established in response to escalating rates of disability and death related to type 2 diabetes mellitus, particularly among racial/ethnic minorities and persons of low socioeconomic status in Durham County, North Carolina. We describe a community-based demonstration project, informed by a geographic health information system (GHIS), that aims to improve health and healthcare delivery for Durham County residents with diabetes. MATERIALS AND METHODS: A prospective, population-based study is assessing a community intervention that leverages a GHIS to inform community-based diabetes care programs. The GHIS integrates clinical, social, and environmental data to identify, stratify by risk, and assist selection of interventions at the individual, neighborhood, and population levels. RESULTS: The DDC is using a multifaceted approach facilitated by GHIS to identify the specific risk profiles of patients and neighborhoods across Durham County. A total of 22,982 patients with diabetes in Durham County were identified using a computable phenotype. These patients tended to be older, female, African American, and not covered by private health insurance, compared with the 166,041 persons without diabetes. Predictive models inform decision-making to facilitate care and track outcomes. Interventions include: 1) neighborhood interventions to improve the context of care; 2) intensive team-based care for persons in the top decile of risk for death or hospitalization within the coming year; 3) low-intensity telephone coaching to improve adherence to evidence-based treatments; 4) county-wide communication strategies; and 5) systematic quality improvement in clinical care. CONCLUSIONS: To improve health outcomes and reduce costs associated with type 2 diabetes, the DDC is matching resources with the specific needs of individuals and communities based on their risk characteristics.

Psychosocial differences between smokers and non-smokers during pregnancy.

Despite the well-established adverse birth and childhood health outcomes associated with maternal smoking, smoking rates among pregnant women remain high. Psychosocial health attributes, including anxiety, depression, perceived stress, self-efficacy, and personality characteristics, have especially important roles in smoking behavior. Understanding who smokes during pregnancy and what factors influence this behavior choice may be key to improving the effectiveness of smoking cessation intervention programs. We use data from a prospective cohort study of pregnant women to understand the psychosocial health profiles of women who choose to smoke during pregnancy compared to the profiles of women who do not smoke or successfully quit smoking during pregnancy. Multinomial logistic regression analyses on 1518 non-Hispanic black and non-Hispanic white women assessed the association between smoking status and psychosocial health while controlling for demographic characteristics. Higher levels of perceived stress, depression, neuroticism, negative paternal support, and perceived racism among non-Hispanic blacks were associated with higher odds of being a smoker than a non-smoker (p<0.05). Higher levels of self-efficacy, extraversion, agreeableness, conscientiousness, interpersonal support, positive paternal support, and perceived social standing were associated with lower odds of being a smoker than a non-smoker (p<0.05). Our analysis indicates that women who smoked during pregnancy experienced a more negative constellation of psychosocial adversities than women who did not smoke. Given the psychosocial needs and personality profiles experienced by smokers, more attention to the psychosocial strengths and weaknesses of these women may allow for more tailored smoking cessation programs, enhancing both the short- and long-term effectiveness of such interventions.

Mercury levels in an urban pregnant population in Durham County, North Carolina.

The adverse effects of prenatal mercury exposure, most commonly resulting from maternal fish consumption, have been detected at very low exposure levels. The omega-3 fatty acids found in fish, however, have been shown to support fetal brain and vision development. Using data from a prospective, cohort study of pregnant women from an inland area in the US South, we sought to understand the fish consumption habits and associated mercury levels across subpopulations. Over 30% of women had at least 1 µg/L of mercury in their blood, and about 2% had blood mercury levels above the level of concern during pregnancy (≥ 3.5 µg/L). Mercury levels were higher among Asian/Pacific Islander, older, higher educated, and married women. Fish consumption from any source was reported by 2/3 of the women in our study, with older women more likely to consume fish. Despite eating more fish meals per week, lower income, lower educated women had lower blood mercury levels than higher income, higher educated women. This suggests the different demographic groups consume different types of fish. Encouraging increased fish consumption while minimizing mercury exposure requires careful crafting of a complex health message.