Support Data Use Research Articles

Transforming public health systems: using data to drive organizational capacity for quality improvement and efficiency.

Introduction:This paper examines the organization, services, and priorities of public health agencies and their capacity to be learning public health systems (LPHS). An LPHS uses data to measure population health and health risks and to evaluate its services and programs, and then integrates its own research with advances in scientific knowledge to innovate and improve its efficiency and effectiveness.Public Health Agencies and Impact for LPHS:Public health agencies’ (PHA) organizational characteristics vary across states, as does their funding per capita. Variations in organization, services provided, and expenditures per capita may reflect variations in community needs or may be associated with unmet needs. The status of legal statutes defining responsibilities and authorities and their relationships to other public and private agencies also vary. Little information is available on the efficiency and effectiveness of state and local PHAs, in part due to a lack of information infrastructure to capture uniform data on services provided. There are almost no data on the relationship of quality of services, staff performance, and resources to population health outcomes. By building a capacity to collect and analyze data on population health within and across communities, and by becoming a continuous learning PHA, the allocation of resources can more closely match population health needs and improve health outcomes. Accreditation of every PHA is an important first step toward becoming a learning PHA.Conclusions:Public Health Services and Systems Research (PHSSR) is beginning to shed light on some of these issues, particularly by investigating variation across PHAs. As this emerging discipline grows, there is a need to enhance the collection and use of data in support of building organized, effective, and efficient LPHSs with the PHA capacity to continually improve the public’s health.

Regulatory and Scientific Issues Regarding Use of Foreign Data in Support of New Drug Applications in the United States: An FDA Perspective

Globalization of clinical research has led to an increase in clinical trials conducted outside of the United States that are submitted to the US Food and Drug Administration (FDA) in new drug applications. This article discusses the FDA's experience with these submissions in specific therapeutic areas, including the extent of this practice, differences between the effectiveness and safety outcomes of studies conducted inside and outside the United States, and the FDA's approach to acceptance of these trials.

A Series of Collaborations between Various Pharmaceutical Companies and Regulatory Authorities Concerning the Analysis of Biomolecules Using Capillary Electrophoresis: Additional Instruments/Buffer

An international project team (including members from US, Canada and UK) was formed from a number of interested biopharmaceutical companies and regulatory authorities to conduct a cross-organisation collaboration exercise. The results of the first comparison with eight different organisations that used instruments of the same equipment model, the same reagents, and the same methodology has been reported previously [1]. This report represents the addition of other instruments using a different run buffer. The relative migration times were different, as expected, prohibiting a direct comparison between companies. The within-organisation variability was low for both relative migration time (<0.34% RSD% for all companies save one) and the peak area (<5% RSD% for all companies save one) when measuring the purity of a representative IgG sample. The apparent molecular weight of bovine serum albumin was measured with good precision (less than 10% RSD% across all companies) to the theoretical value when all data is utilized (67.5 kDa compared to 66.4 kDa). For a representative IgG sample, the three main components, IgG Light Chain, IgG Non-glycosylated Heavy Chain, and IgG Heavy Chain, could not be separated, specifically the IgG Non-glycosylated Heavy Chain and IgG Heavy Chain. When the IgG Non-glycosylated Heavy Chain and IgG Heavy Chain were combined for all organisations, the fractional peak area for the IgG Light Chain and IgG Non-glycosylated Heavy Chain + IgG Heavy Chain peak also showed excellent agreement, with less than 7.5 and 3.5% RSD%, respectively. The value of this exercise is in demonstrating the reliability of CE for the determination of apparent size of biopharmaceutical proteins. This underpins the appropriate use of such CE data in support of regulatory submissions.

Assessing the fidelity of the fossil record by using marine bivalves

Taxa that fail to become incorporated into the fossil record can reveal much about the biases of this record and provide the information needed to correct such biases in empirical analyses of the history of life. Yet little is known about the characteristics of taxa missing from the fossil record. For the marine Bivalvia, which have become a model system for macroevolutionary and macroecological analysis in the fossil record, 308 of the 1,292 living genera and subgenera (herein termed "taxa") are not recorded as fossils. These missing taxa are not a random sample of the clade, but instead tend to have small body size, reactive shell structures, commensal or parasitic habit, deep-sea distribution, narrow geographic range, restriction to regions exposing few Neogene marine sediments, or recent date of formal taxonomic description in the neontological literature. Most missing taxa show two or more of these features and tend to be concentrated in particular families. When we exclude the smallest taxa (<1 cm) and deep-sea endemics, date of published description and geographic range become the strongest predictors of the missing taxa; other factors are statistically insignificant or have relatively small effects. These biases might influence a variety of analyses including the use of fossil data in support of phylogenetic analyses, molecular clock calibrations, and analyses of spatial and temporal dynamics of clades and biotas. Clade inventories such as these can be used to develop protocols that minimize the biases imposed by sampling and preservation.

Cancer risk assessment for 1,3-butadiene: Data integration opportunities

The US Environmental Protection Agency recently released its new guidelines for carcinogen risk assessment together with supplemental guidance for assessing susceptibility from early-life exposure to carcinogens. In particular, these guidelines encourage the use of mechanistic data in support of dose-response characterization at doses below those at which an increase in tumor frequency over background levels might be detected. In this context of the utility of mechanistic data for human cancer risk assessment, the International Life Sciences Institute (ILSI) has developed a human relevance framework (HRF) that can be used to assess the plausibility of a mode of action (MoA) described for animal models operating in humans. The MoA is described as a sequence of key events and processes that result in an adverse outcome. A key event is a measurable precursor step that is in itself a necessary element of the MoA or is a bioindicator for such an element. A number of cellular and molecular perturbations have been identified as key events whereby DNA-reactive chemicals can produce tumors. These include DNA adducts in target tissues, gene mutations and/or chromosomal alterations in target tissues and enhanced cell proliferation in target tissues. This type of data integration approach to quantitative cancer risk assessment can be applied to 1,3-butadiene, for example, using data on biomarkers in exposed Czech workers [1]. For this study, an extensive range of biomarkers of exposure and response was assessed, including: polymorphisms in metabolizing enzymes; urinary concentrations of several metabolites of 1,3-butadiene; hemoglobin adducts; HPRT mutations in T-lymphocytes; chromosomal aberrations by FISH and conventional staining procedures; sister chromatid exchanges. Exposure levels were monitored in a comprehensive fashion. For risk assessment purposes, these data need to be considered in the context of how they inform the MoA for leukemia, the tumor type reported to be increased in synthetic rubber workers exposed to 1,3-butadiene. Also, for the HRF it is necessary to establish key events for a MoA in rodents for the induction of tumors by 1,3-butadiene. There is clearly a species difference in sensitivity to tumor induction, with mice being much more sensitive than rats; key events need to explain this difference. For butadiene, the MoA is DNA-reactivity and subsequent mutagenicity and so following the EPA's cancer guidelines, a linear extrapolation is used from the point of departure (POD), unless additional data support a non-linear extrapolation. For the present case, the human bioindicator data are not informative as far as dose-response characterization is concerned. Mouse chromosome aberration data for in vivo exposures might be used for establishing a POD, with linear extrapolation from this POD. The available cytogenetic data from rodent studies appear to be sufficiently extensive and consistent for this to be a viable approach. This approach of using MoA and key events to establish the human relevance can lead to the development of specific informative bioindicators of response that can be used as surrogates to predict the shape of the tumor dose response curve at low doses. Truly informative predictors of tumor responses should be able to provide estimates of human tumor frequencies at low, environmental exposures to 1,3-butadiene.

Practices That Support Data Use in Urban High Schools

This article presents initial findings of a case study focusing on data use in five low-performing urban high schools undergoing comprehensive schoolwide reform. The case study investigates: (a) the ways in which disaggregated data can be used to examine progress and guide improvement in the process of restructuring urban, low-performing high schools; (b) factors and conditions that either promote or act as barriers to data use; and (c) the policy and practice implications of achieving effective data use in a high school reform process. Study findings point to several key factors that have an impact on data use in the study sites: the quality and accuracy of available data, staff access to timely data, the capacity for data disaggregation, the collaborative use of data organized around a clear set of questions, and leadership structures that support schoolwide use of data. The findings build on current literature and also contribute new knowledge of the key roles played by a data team and a data coach in fostering effective data use in high school reform.

Neurotoxicity test validation, positive controls and proficiency: Are chemicals necessary?

The USEPA neurotoxicity guidelines require the use of positive control data in support of toxicology studies submitted to the Agency and emphasize the use of chemicals to accomplish this requirement. These guidelines, though, propose a number of different rationales for the use of chemicals as positive control agents. We re-evaluated the potential roles of positive control data in addressing three questions: 1) what does the test measure? 2) is the performing laboratory proficient in the use of the test? 3) do the complementary data submitted in support of neurotoxicity studies conducted with the test material provide enough context for the interpretation of the biological significance of an effect? While, for most types of guideline neurotoxicity tests, the use of test chemicals has been emphasized for positive control testing, the use of non-chemical procedures (i.e., systematic manipulation of the experimental parameters of a test, which poses less risk of adverse effects to the test animals) should be strongly considered as a potential alternative.

Contribution of a European spatial data infrastructure to the effectiveness of EIA and SEA studies

Environmental Impact Assessments (EIA) and Strategic Environmental Assessments (SEA) frequently rely on spatial analysis underpinned by spatial data. However, the potential of spatial analysis is often not fully exploited. A questionnaire survey prepared by the European Commission (EC) revealed the existence of problems with the use of spatial data for the preparation of EIA and SEA reports, that have important implications for the preparation of environmental impact studies. This survey has been conducted in the context of the preparation of an extended impact assessment of a proposal for a Directive on INSPIRE—an Infrastructure for Spatial Information in Europe. The INSPIRE initiative intends to deal with a range of barriers that now prevent the widespread use of spatial data in support of good governance that contributes to sustainable development. If INSPIRE could help overcoming the problems related with the availability, access and interoperability of spatial datasets, it would decrease the time and cost needed for the preparation of EIA and SEA reports, improve their quality and reliability and facilitate public participation. Therefore it would contribute to better and more transparent environmental decision-making, thus promoting sustainable development.

Spatial Integration in Construction

Work in construction always requires moving within, and interacting with, a complex environment while handling heavy materials and building elements to be joined, inserted, or aligned. Modern design software is able to digitally model all of those elements in their spatially correct configuration, and without interference. When it comes to the actual construction, however, the spatial models do not find any use. Twenty years after the manufacturing industry began using electronic design data to control their machinery, construction is also getting ready to move away from its longstanding tradition of working with paper-based blueprints. The newest steps on the path toward the use of three-dimensional digital design data in support of site operation are stimulated by the global positioning system and the many uses of lasers. Surveying has always performed critical functions on construction sites, such as marking building layouts, anchor bolts, concrete formwork, or bridge bearings. The objective of spatial...

A test of long-term, predictive, geochemical transport modeling at the Akrotiri archaeological site

A study of elemental transport at the Akrotiri archeological site on the island of Santorini, Greece, has been conducted to evaluate the use of natural analog data in support of long-term predictive modeling of the performance of a proposed geologic repository for nuclear waste at Yucca Mountain, Nevada. Akrotiri and Yucca Mountain have many analogous features including silicic volcanic rocks, relatively dry climates, and oxidizing, hydrologically unsaturated subsurface conditions. Transport of trace elements from artifacts buried in volcanic ash 3600 years ago at Akrotiri is analogous to transport of radioactive wastes in the proposed repository. Subtle evidence for a plume of Cu, Zn, and Pb has been detected by selective leaching of packed earth and bedrock samples collected immediately beneath the site where bronze and lead artifacts were excavated. The geologic setting of the artifacts and the hydraulic properties of the enclosing media were characterized. A numerical model of the type used in repository performance assessments was developed for elemental transport at the site. Site characterization data were used to build the model but no prior information on the nature of the contaminant plume was provided to the modelers. Some model results are qualitatively consistent with field data, including the small amount of material transported, limited amounts of sorbed material, and relatively elevated sorption on a packed earth layer, However, discrepancies result from incomplete representation of heterogeneity and complexity and poorly constrained model parameters. Identification of such system characteristics and model limitations in relevant systems is a major contribution that analog studies can contribute in support of repository modeling.

The use of software engineering data in support of project management

Based on software metrics data from alarge (19 working-years)software development project, a number of analyses have been carried out. The results reveal the causes for cost overruns, show how effort planning can be refined during developemt, and identify a relationship between the quality of the design documents and the effort consumed for their production. This given an insight into the development process and establishes norms for interpreting metrics values obtained in future projects. In this way, it is a first step for a company towards increasing its software development process maturity level.