4 resultados para Health Sciences, Obstetrics and Gynecology

em Duke University


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This qualitative study explored the rural to urban migration’s effect and its related factors on later life health status and health perception among Kazakh Chinese. The participants were same sex sibling pairs, of which one moved from rural to urban areas in early life and the other stayed in rural areas. Rural participants tend to have more selected chronic diseases conditions and other self-reported conditions than urban participants but less physical limitations in older age. There is no clear difference on the health perceptions between rural and urban participants. Health care access and environmental factors are the major differences that may affect health in later life for rural participants.

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Background: Worldwide, it is estimated that there are up to 150 million street children. Street children are an understudied, vulnerable population. While many studies have characterized street children’s physical health, few have addressed the circumstances and barriers to their utilization of health services.

Methods: A systematic literature review was conducted to understand the barriers and facilitators that street children face when accessing healthcare in low and middle income countries. Six databases were used to search for peer review literature and one database and Google Search engine were used to find grey literature (theses, dissertations, reports, etc.). There were no exclusions based on study design. Studies were eligible for inclusion if the study population included street children, the study location was a low and middle income country defined by the World Bank, AND whose subject pertained to healthcare.

In addition, a cross-sectional study was conducted between May 2015 and August 2015 with the goal of understanding knowledge, attitudes, and health seeking practices of street children residing in Battambang, Cambodia. Time location and purposive sampling were used to recruit community (control) and street children. Both boys and girls between the ages of 10 and 18 were recruited. Data was collected through a verbally administered survey. The knowledge, attitudes and health seeking practices of community and street children were compared to determine potential differences in healthcare utilization.

Results: Of the 2933 abstracts screened for inclusion in the systematic literature review, eleven articles met all the inclusion criteria and were found to be relevant. Cost and perceived stigma appeared to be the largest barriers street children faced when attempting to seek care. Street children preferred to receive care from a hospital. However, negative experiences and mistreatment by health providers deterred children from going there. Instead, street children would often self treat and/or purchase medicine from a pharmacy or drug vendor. Family and peer support were found to be important for facilitating treatment.

The survey found similar results to the systematic review. Forty one community and thirty four street children were included in the analysis. Both community and street children reported the hospital as their top choice for care. When asked if someone went with them to seek care, both community and street children reported that family members, usually mothers, accompanied them. Community and street children both reported perceived stigma. All children had good knowledge of preventative care.

Conclusions: While most current services lack the proper accommodations for street children, there is a great potential to adapt them to better address street children’s needs. Street children need health services that are sensitive to their situation. Subsidies in health service costs or provision of credit may be ways to reduce constraints street children face when deciding to seek healthcare. Health worker education and interventions to reduce stigma are needed to create a positive environment in which street children are admitted and treated for health concerns.

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OBJECTIVE: To demonstrate the application of causal inference methods to observational data in the obstetrics and gynecology field, particularly causal modeling and semi-parametric estimation. BACKGROUND: Human immunodeficiency virus (HIV)-positive women are at increased risk for cervical cancer and its treatable precursors. Determining whether potential risk factors such as hormonal contraception are true causes is critical for informing public health strategies as longevity increases among HIV-positive women in developing countries. METHODS: We developed a causal model of the factors related to combined oral contraceptive (COC) use and cervical intraepithelial neoplasia 2 or greater (CIN2+) and modified the model to fit the observed data, drawn from women in a cervical cancer screening program at HIV clinics in Kenya. Assumptions required for substantiation of a causal relationship were assessed. We estimated the population-level association using semi-parametric methods: g-computation, inverse probability of treatment weighting, and targeted maximum likelihood estimation. RESULTS: We identified 2 plausible causal paths from COC use to CIN2+: via HPV infection and via increased disease progression. Study data enabled estimation of the latter only with strong assumptions of no unmeasured confounding. Of 2,519 women under 50 screened per protocol, 219 (8.7%) were diagnosed with CIN2+. Marginal modeling suggested a 2.9% (95% confidence interval 0.1%, 6.9%) increase in prevalence of CIN2+ if all women under 50 were exposed to COC; the significance of this association was sensitive to method of estimation and exposure misclassification. CONCLUSION: Use of causal modeling enabled clear representation of the causal relationship of interest and the assumptions required to estimate that relationship from the observed data. Semi-parametric estimation methods provided flexibility and reduced reliance on correct model form. Although selected results suggest an increased prevalence of CIN2+ associated with COC, evidence is insufficient to conclude causality. Priority areas for future studies to better satisfy causal criteria are identified.

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INTRODUCTION: The ability to reproducibly identify clinically equivalent patient populations is critical to the vision of learning health care systems that implement and evaluate evidence-based treatments. The use of common or semantically equivalent phenotype definitions across research and health care use cases will support this aim. Currently, there is no single consolidated repository for computable phenotype definitions, making it difficult to find all definitions that already exist, and also hindering the sharing of definitions between user groups. METHOD: Drawing from our experience in an academic medical center that supports a number of multisite research projects and quality improvement studies, we articulate a framework that will support the sharing of phenotype definitions across research and health care use cases, and highlight gaps and areas that need attention and collaborative solutions. FRAMEWORK: An infrastructure for re-using computable phenotype definitions and sharing experience across health care delivery and clinical research applications includes: access to a collection of existing phenotype definitions, information to evaluate their appropriateness for particular applications, a knowledge base of implementation guidance, supporting tools that are user-friendly and intuitive, and a willingness to use them. NEXT STEPS: We encourage prospective researchers and health administrators to re-use existing EHR-based condition definitions where appropriate and share their results with others to support a national culture of learning health care. There are a number of federally funded resources to support these activities, and research sponsors should encourage their use.