Fetal death certificate data quality: a tale of two U.S. counties

PurposeDescribe the relative frequency and joint effect of missing and misreported fetal death certificate (FDC) data and identify variations by key characteristics.MethodsStillbirths were prospectively identified during 2006–2008 for a multisite population-based case-control study. For this study, eligible mothers of stillbirths were not incarcerated residents of DeKalb County, Georgia, or Salt Lake County, Utah, aged ≥13 years, with an identifiable FDC. We identified the frequency of missing and misreported (any departure from the study value) FDC data by county, race/ethnicity, gestational age, and whether the stillbirth was antepartum or intrapartum.ResultsData quality varied by item and was highest in Salt Lake County. Reporting was generally not associated with maternal or delivery characteristics. Reasons for poor data quality varied by item in DeKalb County: some items were frequently missing and misreported; however, others were of poor quality due to either missing or misreported data.ConclusionsFDC data suffer from missing and inaccurate data, with variations by item and county. Salt Lake County data illustrate that high quality reporting is attainable. The overall quality of reporting must be improved to support consequential epidemiologic analyses for stillbirth, and improvement efforts should be tailored to the needs of each jurisdiction.     

Brief communication: The Mid-South Clinical Data Research Network

The Mid-South Clinical Data Research Network (CDRN) encompasses three large health systems: (1) Vanderbilt Health System (VU) with electronic medical records for over 2 million patients, (2) the Vanderbilt Healthcare Affiliated Network (VHAN) which currently includes over 40 hospitals, hundreds of ambulatory practices, and over 3 million patients in the Mid-South, and (3) Greenway Medical Technologies, with access to 24 million patients nationally. Initial goals of the Mid-South CDRN include: (1) expansion of our VU data network to include the VHAN and Greenway systems, (2) developing data integration/interoperability across the three systems, (3) improving our current tools for extracting clinical data, (4) optimization of tools for collection of patient-reported data, and (5) expansion of clinical decision support. By 18 months, we anticipate our CDRN will robustly support projects in comparative effectiveness research, pragmatic clinical trials, and other key research areas and have the capacity to share data and health information technology tools nationally.     

Implementing partnership-driven clinical federated electronic health record data sharing networks

ObjectiveBuilding federated data sharing architectures requires supporting a range of data owners, effective and validated semantic alignment between data resources, and consistent focus on end-users. Establishing these resources requires development methodologies that support internal validation of data extraction and translation processes, sustaining meaningful partnerships, and delivering clear and measurable system utility. We describe findings from two federated data sharing case examples that detail critical factors, shared outcomes, and production environment results.MethodsTwo federated data sharing pilot architectures developed to support network-based research associated with the University of Washington’s Institute of Translational Health Sciences provided the basis for the findings. A spiral model for implementation and evaluation was used to structure iterations of development and support knowledge share between the two network development teams, which cross collaborated to support and manage common stages.ResultsWe found that using a spiral model of software development and multiple cycles of iteration was effective in achieving early network design goals. Both networks required time and resource intensive efforts to establish a trusted environment to create the data sharing architectures. Both networks were challenged by the need for adaptive use cases to define and test utility.ConclusionAn iterative cyclical model of development provided a process for developing trust with data partners and refining the design, and supported measureable success in the development of new federated data sharing architectures.     

Patterns of aged care use among older Australian women: A prospective cohort study using linked data

BackgroundWomen live longer than men and have an increased need for long-term care. The objective of this study was to identify patterns of aged care use among older Australian women and to examine how these patterns were associated with their demographic and health-related characteristics.MethodsThe sample consisted of 8768 women from the 1921–1926 birth cohort of the Australian Longitudinal Study on Women’s Health (ALSWH), who had survived to age 75-80 years. ALSWH survey and linked administrative aged care and death datasets from 2001 to 2011 were utilized. Patterns of aged care use were identified using a repeated measure latent class analysis.ResultsWe identified four patterns of aged care use over time, differentiated by timing of service onset, types of service use and time of death. Approximately 41% of the sample were non-users or using basic home and community care (HACC), while 24% were at high risk of using moderate to high-level HACC/community aged care package (CACP). Only 11% had a greater risk of using residential aged care (RAC) over time. Being widowed, residing in remote/regional areas, having difficulty in managing income, having a chronic condition, reporting poor/fair self-rated health, and lower SF-36 quality of life scores were associated with an increased odds of being a member of the following classes: 1) moderate to high-level HACC/CACP, 2) increasing RAC, and 3) early mortality, compared with the non-user class.ConclusionsDistinct patterns of aged care use were identified. These results will facilitate future capacity planning for aged care systems in Australia.     

Is autoimmunology a discipline of its own? A big data-based bibliometric and scientometric analyses

Autoimmunology is a super-specialty of immunology specifically dealing with autoimmune disorders. To assess the extant literature concerning autoimmune disorders, bibliometric and scientometric analyses (namely, research topics/keywords co-occurrence, journal co-citation, citations, and scientific output trends – both crude and normalized, authors network, leading authors, countries, and organizations analysis) were carried out using open-source software, namely, VOSviewer and SciCurve. A corpus of 169,519 articles containing the keyword “autoimmunity” was utilized, selecting PubMed/MEDLINE as bibliographic thesaurus. Journals specifically devoted to autoimmune disorders were six and covered approximately 4.15% of the entire scientific production. Compared with all the corpus (from 1946 on), these specialized journals have been established relatively few decades ago. Top countries were the United States, Japan, Germany, United Kingdom, Italy, China, France, Canada, Australia, and Israel. Trending topics are represented by the role of microRNAs (miRNAs) in the ethiopathogenesis of autoimmune disorders, contributions of genetics and of epigenetic modifications, role of vitamins, management during pregnancy and the impact of gender. New subsets of immune cells have been extensively investigated, with a focus on interleukin production and release and on Th17 cells. Autoimmunology is emerging as a new discipline within immunology, with its own bibliometric properties, an identified scientific community and specifically devoted journals.     

State-of-the-art Tools for Computational Site of Metabolism Predictions: Comparative Analysis,Mechanistical Insights,and Future Applications

In drug design, it is crucial to have reliable information on how a chemical entity behaves in the presence of metabolizing enzymes. This requires substantial experimental efforts. Consequently, being able to predict the likely site/s of metabolism in any compound, synthesized or virtual, would be highly beneficial and time efficient.

In this work, six different methodologies for predictions of the site of metabolism (SOM) have been compared and validated using structurally diverse data sets of drug-like molecules with well-established metabolic pattern in CYP3A4, CYP2C9, or both. Three of the methods predict the SOM based on the ligand's chemical structure, two additional methods use structural information of the enzymes, and the sixth method combines structure and ligand similarity and reactivity. The SOM is correctly predicted in 50 to 90% of the cases, depending on method and enzyme, which is an encouraging rate. We also discuss the underlying mechanisms of cytochrome P450 metabolism in the light of the results from this comparison.     

初创社科类英文学术期刊国际影响力提升的探索与实践——以Financial Innovation为例

【目的】 探讨如何在稿源欠缺、显示度低、参与度差的情况下快速有效提升我国初创社科类英文学术期刊的国际影响力。【方法】 结合数据统计分析,结合《金融创新》(Financial Innovation)实际案例,归纳初创英文学术期刊提升国际影响力的途径及方法。【结果】 《金融创新》创刊5年中,跨越式实现从无到有,再到进入SSCI检索并进入学科Q1分区的进步。【结论】 前沿专刊筹措、邮件精准推广、期刊数据库挖掘是初创英文学术期刊在有限资源下取得突破、提升国际影响力的重要路径。     

Multi-Center Analysis of Liver Transplantation for Combined Hepatocellular Carcinoma-Cholangiocarcinoma Liver Tumors

1. Download : Download high-res image (269KB)
2. Download : Download full-size image