Research Data Center Research Articles

The distributional effects of early school stratification - non-parametric evidence from Germany

Whether early school stratification is conducive or detrimental to scholastic performance has been subject to controversial debates in educational policy and science across many countries. We exploit a reform in Lower Saxony, Germany, where performance based tracking was preponed from grade 7 to grade 5 in 2004, i.e. with the completion of primary school. In particular, we measure the long-run effects of this reform on PISA achievement test scores based on a difference-in-differences setup. In order to disentangle average from distributional achievement effects, we complementarily rely on a changes-in-changes framework. Our results indicate that preponed school tracking increases test scores in the upper tail of the skill distribution and lowers test scores in the lower tail of the skill distribution, compensating each other on average.11This study does not represent a comprehensive evaluation of the exploited reform in Lower Saxony in 2004. We are grateful for the data provided by the Research Data Center (FDZ) at the Institute for Educational Quality Improvement (IQB) associated with the Humboldt University of Berlin. Marcus Roller acknowledges financial support by the WWZ Förderverein. We are grateful for valuable inputs from Blaise Melly and two anonymous referees. In addition, we thank the participants of the EEA Annual Congress 2017, the SSES Annual Congress 2017, the Spring Meeting of Young Economists 2018 and seminar participants at the Universities of Basel and Tübingen. The views expressed in this article are those of the authors and do not necessarily reflect those of PricewaterhouseCoopers.

Payer effects of personalized preventive care for patients with diabetes.

To examine the effects of MD-Value in Prevention (MDVIP) enrollment on Medicare expenditures and utilization among fee-for-service (FFS) beneficiaries with diabetes over a 5-year period. We obtained participating physician and beneficiary enrollment lists from MDVIP and Medicare FFS claims data through the Virtual Research Data Center to compare changes in outcomes, before and after enrollment dates, with those of nonenrolled beneficiaries receiving primary care in the same local market. We employed propensity score matching to identify comparison beneficiaries similar in observed characteristics and preenrollment trends. Individual fixed effects were used to control for time-consistent differences between treatment and comparison populations. We found that enrollment is statistically associated with reductions in outpatient expenditures, Medicare expenditures in year 5, emergency department (ED) utilization, and unplanned inpatient admissions, accompanied by significant increases in evaluation and management visits and expenditures. Total Medicare expenditures over the 5-year period, as well as all inpatient admissions, were not statistically different between the MDVIP and comparison groups. Our finding of reduced unplanned inpatient admissions and ED utilization supports the previous findings regarding MDVIP enrollees. We did not find significant changes in overall third-party expenditures, although savings were estimated in year 5, the last year of observation, and may occur later. Our approach, however, strengthens controls for baseline characteristics of the population and uses a comparison population drawn from the same markets who do not experience the loss of their primary care physician at the time of enrollment.

Application of Deep Learning Algorithm in Clinical Analysis of Patients With Serum Electrolyte Disturbance

This article analyzes the serum electrolyte disturbances of patients through deep learning algorithms. Among the 104 patients with electrolyte disturbances, 6 cases of serum potassium, sodium, chloride, calcium, phosphorus, and magnesium electrolyte disturbances have occurred, the proportion of occurrence The order is sodium > chlorine > calcium > potassium > phosphorus > magnesium. This paper proposes a deep learning algorithm for serum electrolyte disorder, and analyzes and implements the functions at various levels according to the characteristics of the Hadoop framework. The system includes electronic medical records shared storage, distributed realization of definite learning algorithms, classification and recognition of myocardial ischemia by deep learning, and Web system assisting doctor diagnosis, which lays the foundation for the construction of serum electrolyte disorder scientific research data center. In order to explore this relationship, without artificially extracting features, a deep learning model of convolution and long-term and short-term memory circulation neural network cascade was proposed to determine the positive or negative myocardial ischemia by classifying serum disorders. Conduct clinical experiments, including patients with suspected coronary heart disease and coronary angiography as the research object, taking coronary angiography results as the detection standard. Experimental results show that the model has an accuracy of 89.0% for detecting myocardial ischemia, a sensitivity of 91.7%, and a specificity of 81.5%. A linear combination model of CNN and LSTM is proposed to classify and recognize serum electrolyte disorders. Determine the learning theory to dynamically model the ST-T segment in the ECG to obtain serum electrolyte disturbance, which more vividly shows the changes in electrical information under myocardial ischemia. In order to reveal the relationship between serum electrolyte disturbance and myocardial ischemia, this paper builds a neural network model to learn and train serum electrolyte disturbance data to realize the classification of positive or negative myocardial ischemia. Tests on serum electrolyte disturbance data collected in clinical experiments show that this model can better achieve early detection of myocardial ischemia.

Approach to CDISC Standardization of Clinical Research Data at Clinical Research Data Center, Tohoku University Hospital

Approach to CDISC Standardization of Clinical Research Data at Clinical Research Data Center, Tohoku University Hospital

Advanced Technologies Adoption and Use by U.S. Firms: Evidence from the Annual Business Survey

We introduce a new survey module intended to complement and expand research on the causes and consequences of advanced technology adoption. The 2018 Annual Business Survey (ABS), conducted by the Census Bureau in partnership with the National Center for Science and Engineering Statistics (NCSES), provides comprehensive and timely information on the diffusion among U.S. firms of advanced technologies including artificial intelligence (AI), cloud computing, robotics, and the digitization of business information. The 2018 ABS is a large, nationally representative sample of over 850,000 firms covering all private, nonfarm sectors of the economy. We describe the motivation for and development of the technology module in the ABS, as well as provide a first look at technology adoption and use patterns across firms and sectors. We find that digitization is quite widespread, as is some use of cloud computing. In contrast, advanced technology adoption is rare and generally skewed towards larger and older firms. Adoption patterns are consistent with a hierarchy of increasing technological sophistication, in which most firms that adopt AI or other advanced business technologies also use the other, more widely diffused technologies. Finally, while few firms are at the technology frontier, they tend to be large so technology exposure of the average worker is significantly higher. This new data will be available to qualified researchers on approved projects in the Federal Statistical Research Data Center network.

On the Respective Roles of National Libraries, National Archives and Research Data Centers in the Preservation of and Access to Research Data

A meeting was held in Berlin on the 22nd of June, 2010, under the aegis of the UK Data Forum and the German Data Forum (RatSWD). The purpose of this meeting was to consider the role of libraries and archives for the acquisition, management and preservation of research data in the behavioural, social and economic sciences.For the purposes of this document we define research data broadly as “the primary inputs into research, as well as the first-order results of that research.” Our conclusion from the meeting was that it would be useful to formulate a memorandum on the respective roles of national libraries, national archives and research data centres. In our capacities as the chairpersons of the UK and German Data Forums we have written the following short overview and memorandum.

U.S. Decennial Census Digitization and Linkage Project

The U.S. Census Bureau maintains a large longitudinal research infrastructure that currently includes linked data from the 1940 census, the 2000-2010 censuses, major national surveys going back to 1973, and administrative records dating back to the 1990s. These restricted data are accessible to researchers around the U.S. via the Federal Statistical Research Data Centers (FSRDC) network. The major shortcoming of this infrastructure is that it lacks linkable files from the decennial censuses of 1950 through 1990. Full-count microdata from these censuses are available for research, but datasets from these years do not include respondent names and therefore have not been linked over time. Respondent names for these censuses are available only via the original census returns, which are stored on 258,000 reels of microfilm.
 The Decennial Census Digitization and Linkage project (DCDL) is an initiative to recover names from the 1960-1990 censuses and to produce linked restricted microdata files for research use. We describe the results of a pilot project we completed on the 1990 census. For that pilot, we created digital images from census microfilm, hand-keyed "truth data" from those images, supported two teams' attempts to conduct Handwriting Recognition on the images, appended recovered names to already-existing microdata files, and linked the new 1990 census microdata records to previous and subsequent censuses. We describe our processes, the accuracy of the Handwriting Recognition, and the accuracy of the record linkage with the recovered names. We conclude by providing an update on the recently-initiated project to carry out these processes on a production scale for the 1960 through 1990 censuses.
 When combined with existing linkages between the censuses of 1940, 2000, 2010, the soon-to-be public 1950 census, and the future 2020 census, DCDL will provide the final component in a massive longitudinal data infrastructure that covers most of the U.S. population since 1940. As a multi-purpose statistical tool, the DCDL will further the U.S. Census Bureau's mission to provide high quality data on the U.S. population and support cutting-edge research in the FSRDC network. The resulting data resource will expand our understanding of population dynamics in the U.S. far beyond what is currently possible, providing transformational opportunities for research, education, and evidence-building across the social, behavioral, and economic sciences.

A Simulation-Based Approach to Data Center Thermal Efficiency Optimization

Abstract The energy consumption for cooling electronic equipment in data centers using central systems is significant and will continue to rise. The motivation of the present research study is based on the need to determine optimization strategies to improve and optimize the thermal efficiency of data centers using a simulation-based approach. Here, simulation is used to model and optimize a proposed research data center for use as an environment to test equipment and investigate best practices and strategies such as containment and hybrid cooling. The optimization technique used in this study finds the optimal operating conditions and containment strategies of the data center while meeting specific thermal conformance criteria. More specifically, optimum supply airflow rate and temperature setpoint of cooling units are sought under different containment configurations, including both hot aisle and cold aisle containment strategies in both full and partial setups. The results of the computational fluid dynamics (CFD) simulations indicated a lower probability of hot spots with full hot aisle containment strategy in a data center operating at lower supply airflow rate and higher supply temperature setpoint. The optimization approach helped to determine a more efficient cooling system without the risk of under-provisioning. The study considered steady-state conditions with static heat load and fixed equipment layout. However, the generalized optimization process developed in the present study should add to the repertoire of tools presently used for the optimization of new air-cooled data centers.

Definition of Variables in Hospital Discharge Data: Pitfalls and Proposed Solutions

In Germany, the Diagnosis-Related Group Statistics (DRG Statistics) supply full coverage of inpatient episodes in acute care hospitals. The Research Data Centres of the Federal Statistical Office and the Statistical Offices of the Federal States provide the microdata of the DRG Statistics, namely hospital discharge files of each inpatient case, for scientific research. Hospital discharge data are generated for administrative purposes. As well as other data sources, they have specific features and characteristics, which should be considered in planning and designing research studies. A key challenge is the appropriate and sophisticated operationalization of units of analysis, targets variables, and other study variables. The methodological approach should consider, among other factors, differing coding behaviour between hospitals in order to minimize the risk of bias. This contribution shows by practical examples what should be incorporated in variable definition to ensure that the risk of bias by coding behaviour or other factors is minimized to the greatest possible degree. First of all, the features and characteristics of the German hospital discharge data are outlined. Based on the authors' experiences, basic steps and challenges in observational health services research studies are described. Examples are illustrated by our own calculations, derived from previous studies based on the microdata of the DRG Statistics. The reliability and validity of analyses based on hospital discharge data are crucially dependent on the appropriateness of variable definition. To minimize the risk of bias and misinterpretation, extensive preliminary considerations are required which involve clinical aspects, as well as the context of data collection and technical classification opportunities. Hopefully, there will be greater acceptance of research based on hospital discharge data, so that these valuable data will be used more frequently for research purposes in the future.

Erratum: "Mortality Risk and Fine Particulate Air Pollution in a Large, Representative Cohort of U.S. Adults".

Vol. 127, No. 9 ErratumOpen AccessErratum: “Mortality Risk and Fine Particulate Air Pollution in a Large, Representative Cohort of U.S. Adults”is correction ofMortality Risk and Fine Particulate Air Pollution in a Large, Representative Cohort of U.S. Adults C. Arden Pope III, Jacob S. Lefler, Majid Ezzati, Joshua D. Higbee, Julian D. Marshall, Sun-Young Kim, Matthew Bechle, Kurtis S. Gilliat, Spencer E. Vernon, Allen L. Robinson, and Richard T. Burnett C. Arden Pope III Search for more papers by this author , Jacob S. Lefler Search for more papers by this author , Majid Ezzati Search for more papers by this author , Joshua D. Higbee Search for more papers by this author , Julian D. Marshall Search for more papers by this author , Sun-Young Kim Search for more papers by this author , Matthew Bechle Search for more papers by this author , Kurtis S. Gilliat Search for more papers by this author , Spencer E. Vernon Search for more papers by this author , Allen L. Robinson Search for more papers by this author , and Richard T. Burnett Search for more papers by this author Published:27 September 2019CID: 099002https://doi.org/10.1289/EHP6182Cited by:7AboutSectionsPDF ToolsDownload CitationsTrack Citations ShareShare onFacebookTwitterLinked InReddit In the final sentence of the Acknowledgments section, the sentence “Findings and conclusions of this research are those of the authors and do not necessarily represent the views of the National Center for Health Statistics (NCHS) Research Data Center (RDC), the NCHS, the U.S. EPA, or the Centers for Disease Control and Prevention” should be “Findings and conclusions of this research are those of the authors and do not necessarily represent the views of the National Center for Health Statistics (NCHS) Research Data Center (RDC), the NCHS, the U.S. EPA, the Centers for Disease Control and Prevention, or Cornerstone Research.”The authors apologize for the error.FiguresReferencesRelatedDetailsCited by Thind M, Tessum C and Marshall J (2022) Environmental Health, Racial/Ethnic Health Disparity, and Climate Impacts of Inter-Regional Freight Transport in the United States, Environmental Science & Technology, 10.1021/acs.est.2c03646, 57:2, (884-895), Online publication date: 17-Jan-2023. Wu Y, Xu Z, Liu S, Tang M and Lu S (2022) Emission Characteristics of Particulate Matter from Coal-Fired Power Units with Different Load Conditions, Water, Air, & Soil Pollution, 10.1007/s11270-022-05919-9, 233:11, Online publication date: 1-Nov-2022. Jun Y, Song I, Kim O and Kim S (2022) Impact of limited residential address on health effect analysis of predicted air pollution in a simulation study, Journal of Exposure Science & Environmental Epidemiology, 10.1038/s41370-022-00412-1, 32:4, (637-643), Online publication date: 1-Jul-2022. Cano M, Reina T, Portillo E, Gallego Fernández L and Navarrete B (2021) Characterization of emissions of condensable particulate matter under real operation conditions in cement clinker kilns using complementary experimental techniques, Science of The Total Environment, 10.1016/j.scitotenv.2021.147472, 786, (147472), Online publication date: 1-Sep-2021. Kataoka H, Tanaka K, Tazuya-Murayama K, Yamashita T and Nishikawa J (2021) Cytotoxic Effects of Water-Soluble Extracts of Coarse and Fine Atmospheric Particulate Matter on Mast Cell Lines, Biological and Pharmaceutical Bulletin, 10.1248/bpb.b20-00576, 44:1, (57-62), Online publication date: 1-Jan-2021. Ou J, Hanson H, Ramsay J, Kaddas H, Pope C, Leiser C, VanDerslice J and Kirchhoff A (2020) Fine Particulate Matter Air Pollution and Mortality among Pediatric, Adolescent, and Young Adult Cancer Patients, Cancer Epidemiology, Biomarkers & Prevention, 10.1158/1055-9965.EPI-19-1363, 29:10, (1929-1939), Online publication date: 1-Oct-2020. Coffman E, Burnett R and Sacks J (2020) Quantitative Characterization of Uncertainty in the Concentration–Response Relationship between Long-Term PM 2.5 Exposure and Mortality at Low Concentrations , Environmental Science & Technology, 10.1021/acs.est.0c02770 Related articlesMortality Risk and Fine Particulate Air Pollution in a Large, Representative Cohort of U.S. Adults24 July 2019Environmental Health Perspectives Vol. 127, No. 9 September 2019Metrics About Article Metrics Publication History Manuscript received5 September 2019Manuscript accepted17 September 2019Originally published27 September 2019 Financial disclosuresPDF download License information EHP is an open-access journal published with support from the National Institute of Environmental Health Sciences, National Institutes of Health. All content is public domain unless otherwise noted. Note to readers with disabilities EHP strives to ensure that all journal content is accessible to all readers. However, some figures and Supplemental Material published in EHP articles may not conform to 508 standards due to the complexity of the information being presented. If you need assistance accessing journal content, please contact [email protected]. Our staff will work with you to assess and meet your accessibility needs within 3 working days.

Challenges of using nationally representative, population-based surveys to assess rural cancer disparities

Population-based surveys provide important information about cancer-related health behaviors across the cancer care continuum, from prevention to survivorship, to inform cancer control efforts. These surveys can illuminate cancer disparities among specific populations, including rural communities. However, due to small rural sample sizes, varying sampling methods, and/or other study design or analytical concerns, there are challenges in using population-based surveys for rural cancer control research and practice. Our objective is three-fold. First, we examined the characterization of “rural” in four, population-based surveys commonly referenced in the literature: 1) Health Information National Trends Survey (HINTS); 2) National Health Interview Survey (NHIS); 3) Behavioral Risk Factor Surveillance System (BRFSS); and 4) Medical Expenditures Panel Survey (MEPS). Second, we identified and described the challenges of using these surveys in rural cancer studies. Third, we proposed solutions to address these challenges. We found that these surveys varied in use of rural-urban classifications, sampling methodology, and available cancer-related variables. Further, we found that accessibility of these data to non-federal researchers has changed over time. Survey data have become restricted based on small numbers (i.e., BRFSS) and have made rural-urban measures only available for analysis at Research Data Centers (i.e., NHIS and MEPS). Additionally, studies that used these surveys reported varying proportions of rural participants with noted limitations in sufficient representation of rural minorities and/or cancer survivors. In order to mitigate these challenges, we propose two solutions: 1) make rural-urban measures more accessible to non-federal researchers and 2) implement sampling approaches to oversample rural populations.

Mortality after liver surgery in Germany.

Mortality rates after liver surgery are not well documented in Germany. More than 1000 hospitals offer liver resection, but there is no central regulation of infrastructure requirements or outcome quality. Hospital mortality rates after liver resection were analysed using the standardized hospital discharge data (Diagnosis-Related Groups, ICD-10 and German operations and procedure key codes) provided by the Research Data Centre of the Federal Statistical Office and Statistical Offices of the Länder in Wiesbaden, Germany. A total of 110 332 liver procedures carried out between 2010 and 2015 were identified. The overall hospital mortality rate for all resections was 5·8 per cent. The mortality rate among 17 574 major hepatic procedures was 10·4 per cent. Patients who had surgery for colorectal liver metastases (CRLMs) had the lowest mortality rate among those with malignancy (5·5 per cent), followed by patients with gallbladder cancer (7·1 per cent), hepatocellular carcinoma (9·3 per cent) and intrahepatic cholangiocarcinoma (11·0 per cent). Patients with extrahepatic cholangiocarcinoma had the highest mortality rate (14·6 per cent). The mortality rate for extended hepatectomy was 16·2 per cent and the need for a biliodigestive anastomosis increased this to 25·5 per cent. Failure to rescue after complications led to mortality rates of more than 30 per cent in some subgroups. There was a significant volume-outcome relationship for CRLM surgery in very high-volume centres (mean 26-60 major resections for CRLMs per year). The mortality rate was 4·6 per cent in very high-volume centres compared with 7·5 per cent in very low-volume hospitals (odds ratio 0·60, 95 per cent c.i. 0·42 to 0·77; P < 0·001). This analysis of outcome data after liver resection in Germany suggests that hospital mortality remains high. There should be more focused research to understand, improve or justify factors leading to this result, and consideration of centralization of liver surgery.

Return to Work after Temporary Disability Pension

In Germany, there are no statistics available that reveal how many temporary disability pensioners return to work. The aim of this study was to analyse how many persons to whom a temporary disability pension was granted in 2006 returned to work. Their socio-demographic, health-related and vocational characteristics were examined. The scientific use file "Completed Rehabilitation 2006-2013 in the Course of Individual Pension Records" provided by the research data centre of the German Pension Fund was analysed. Return to Work was assumed if a person worked at least part-time for 183 to 365 days with not less than 8.50 euro/hour in one of the following seven years after being pensioned. The development of the cohort was assessed descriptively. Cox regression analyses were conducted to determine the influence of socio-demographic, health-related and vocational characteristics of the pensioners on their return to work. Between 2007 and 2013, 5.9% of the initial cohort (N=9.789) returned to work; 25% of these returned to work in all seven years. Between 2006 and 2014, 10.6% of the initial cohort died, 9.1% shifted to old-age pension and 1.4% were granted an unlimited disability pension. Regression analysis indicates that sociodemographic, health-related and vocational characteristics are associated with the probability of return to work: Disability pensioners aged between 18 and 39 years, with a somatic disease, who went through medical rehabilitation or were employed before the disability pension had the highest probability of return to work. The results show that only few persons with temporary disability pension returned to work. Therefore, it could be concluded that criteria for temporal limitations of pensions should be sharpened in order to reduce the amount of additional medical evaluations. On the other hand, new strategies to support pensioners' potential for return to work have to be considered.

The 2014 Ontario Child Health Study-Methodology.

Objective:To describe the methodology of the 2014 Ontario Child Health Study (OCHS): a province-wide, cross-sectional, epidemiologic study of child health and mental disorder among 4- to 17-year-olds living in household dwellings.Method:Implemented by Statistics Canada, the 2014 OCHS was led by academic researchers at the Offord Centre for Child Studies (McMaster University). Eligible households included families with children aged 4 to 17 years, who were listed on the 2014 Canadian Child Tax Benefit File. The survey design included area and household stratification by income and 3-stage cluster sampling of areas and households to yield a probability sample of families.Results:The 2014 OCHS included 6,537 responding households (50.8%) with 10,802 children aged 4 to 17 years. Lower income families living in low-income neighbourhoods were less likely to participate. In addition to measures of childhood mental disorder assessed by the Mini International Neuropsychiatric Interview for Children and Adolescents (MINI-KID) and OCHS Emotional Behavioural Scales (OCHS-EBS), the survey contains measures of neighbourhoods, schools, families and children, and includes administrative data held by the Ministries of Education and Health and Long-Term Care.Conclusions:The complex survey design and differential non-response of the 2014 OCHS required the use of sampling weights and adjustment for design effects. The study is available throughout Canada in the Statistics Canada Research Data Centres (RDCs). We urge external investigators to access the study through the RDCs or to contact us directly to collaborate on future secondary analysis studies based on the OCHS.

The Micro Data Linking-Panel: A Combined Firm Dataset

Abstract The following article informs about the Micro Data Linking-Panel (hereafter MDL-Panel), a new firm In German business statistics the statistical unit, or firm, is currently referred to as the smallest legally independent unit which keeps accounts for commercial and/or tax purposes. dataset, available since May 2018 via the Research Data Centre of the Federal Statistical Office and the Research Data Centre of the Statistical Offices of the Federal States (RDC) (Forschungsdatenzentren der Statistischen Ämter des Bundes und der Länder (2018a, 2018b). The dataset originates from two projects funded by Eurostat over the period 2014 to 2016 with the title “Micro data linking of structural business statistics and other business statistics” (MDL). The projects combined data of various business statistics for the reference years 2008 to 2013 and were aimed at offering new perspectives on business statistics topics, which are not addressed in the ordinary publication program. Furthermore, MDL served to gain insights about the involved methodological challenges of linked data in Official Statistics. The first chapter provides background information on the projects funded by Eurostat. Chapter 2 contrasts the contents of the MDL-Panel to other products available via the RDC. The third chapter describes the scope of the dataset and its content in more detail. The article closes with future prospects for the MDL-Panel.

Learning through connecting: data management as a basis for meaningful use of legacy data -The African Archaeology Archive Cologne

For more than 50 years the African Archaeology at the University of Cologne has conducted field research in various parts of Africa, particularly in the Eastern Sahara and in Namibia. The focus was on environmental history and on rock art, with internationally renowned research schemes like ACACIA (Arid Climate Adaptation and Cultural Innovation in Africa) and ‘Rock Paintings of the Upper Brandberg'. Much of it was published in close co-operation with the Heinrich-Barth-Institut, including six voluminous catalogues of rock art and 26 monographs on African archaeology. Most of the materials accumulated in the research projects are not digital in origin and are now digitized and made accessible in the digital online archive AAArC (African Archaeology Archive Cologne). Besides being a repository for tens of thousands of pictures, also whole documentations of excavation are made accessible here. Digitising the repositories of Cologne's African Archaeology within the AAArC project started in 2012, using the DAI (German Archaeological Institute) data-interfaces Arachne, DAI-Gazetteer and DAI-Zenon. Today AAArC opens web access to thousands of fieldwork documentations, pictures and tracings of rock art. Open access interoperability of metadata integrated to picture formats is achieved. Exploiting database management systems of highly varied structure in a digital repository is achieved through collaboration with IANUS (Research Data Centre Archaeology & Ancient Studies), a national long-term preservation digital archive for archaeological data. AAArC offers participation in digital heritage content management, thus perpetuating the long lasting cooperation of Cologne's African Archaeology with a number of African countries. The AAArC online archive aspires to make the full range of archaeological documentations accessible online and not just pictures. Thus AAArC ultimately enables a digital homecoming of complex research data to their countries of origin.

Public-Use vs. Restricted-Use: An Analysis Using the American Community Survey

Statistical agencies frequently publish microdata that have been altered to protect condentiality. Such data retain utility for many types of broad analyses but can yield biased or insufficiently precise results in others. Research access to de-identied versions of the restricted-use data with little or no alteration is often possible, albeit costly and time-consuming. We investigate the advantages and disadvantages of public-use and restricted-use data from the American Community Survey (ACS) in constructing a wage index. The public-use data used were Public Use Microdata Samples, while the restricted-use data were accessed via a Federal Statistical Research Data Center. We discuss the advantages and disadvantages of each data source and compare estimated CWIs and standard errors at the state and labor market levels. We find the results from the publicly available data are generally good relative to the restricted-use data, with greater similarity for larger areas and less similarity for smaller areas. Standard errors are higher in the public-used data but may still be underestimated.

International Data Access Network (IDAN)

With legal frameworks changing, administrative data can increasingly be utilised both for official statistics and to facilitate new research, enabling the development of evidence-based policy for the public benefit. Secure access conditions generally apply to using these rich, highly detailed data. However, using data from various sources is difficult when they are fragmented in “silos” between several Research Data Centres (RDCs) as can happen at a national level, and is very likely to be the case at an international level. This is a major obstacle for international comparative research. Based on user consultations, on discussions with international organisations such as OECD and Eurostat and based on lessons learned from projects as, “Data without Boundaries” and the “Nordic Microdata Access Network”, IDAN aims to create a concrete operational international framework enabling access to controlled data for research. IDAN, founded in 2018, involves six RDCs from France, Germany, the Netherlands and the United Kingdom. Initially, the partners’ access systems are being implemented in each partners' premise based on bilateral agreements. This process involves combining requirements of security and surveillance for Safe Rooms, thus paving the way for next steps toward an integrated RDCs network. This presentation will describe how IDAN is setting up a new concrete environment for researchers to work remotely with data from the other partners within their local RDC. The paper will present first project developments, lessons and impact for research that are also of interest for national contexts where administrative data are held in multiple data centres.

International comparison in walkable environments and hospital burden in type 2 diabetes patients

IntroductionWhile some comparative work has provided evidence for a universally positive impact of built environment features that promote physical activity, less is known about chronic diseases and hospitalization among different social contexts and health care systems. Parallel international linkage efforts present an opportunity to study health impacts of the built environment.&#x0D; Objectives and ApproachThis study compares the impact of neighbourhood environments on health outcomes for patients with type 2 diabetes (T2D) in two countries. Neighborhood-level measures for walkable environments were derived for Canada and Wales using Geographic Information Systems. Hospitalization admissions from routine data sources and linked survey data responses (from the Welsh Health Survey and Canadian Community Health Survey) allow for the generation of population-based descriptive statistics on socio-demographic information, self-reported health, diagnostic patterns, and health care use. We examine the feasibility of investigating contextual differences in walkable environments, T2D, and hospitalization between Wales and Canada.&#x0D; ResultsData linkage in respective privacy protecting safe havens in the Canada Research Data Centre Network (CRDCN) and the Wales Secure Anonymised Information Linkage (SAIL) Databank show promise for a comparative study, enabling parallel modelling of environmental and socio-demographic factors with hospitalization data. Both the Canadian and Welsh surveys ask respondents about their current diabetes status, allowing us to compare hospitalization rates and neighborhood effects of those who report having diabetes with the those who do not. Moreover, the linking of survey responses and similarity in geographic scale permitted consistent measurement of walkable environments across countries. Key administrative variables have been identified relating to health and behaviors, such as socio-demographic information, smoking status, and body mass index, and hospitalization metrics in both countries are commensurable.&#x0D; Conclusion/ImplicationsThe generation of comparable linked datasets, built environment indicators and comparative research for T2D patients will have wider implications for international assessment of the impacts of environment on chronic diseases, and the hospital burden associated with these conditions.

Health services research in German radiation oncology: new opportunities to advance cancer care.

Health services research (HSR) is of increasing relevance to scientists, health-care providers, and clinicians. Complex population-based secondary data are akey source of information for analyses of health-care effects in radiation oncology. In this short paper, we examine potential applications of secondary data focusing on statistics from the diagnosis-related groups (DRG). This data set incorporating all hospitalized cases in Germany is based on claims of reimbursements and is provided by the Research Data Centers (RDC) of the Federal Statistical Office and the Statistical Offices of the federal states. Ashort outlook regarding other data sources is also presented. In radiation oncology, secondary data such as the DRG statistics have rarely been used to examine health-care effects, despite their great potential for reporting effects in abroad population-based setting. Furthermore, for most data sources, the application to use these data is accessible with minor effort. However, data concerning outpatient care are difficult to analyze on acomparable level. DRG statistics and related secondary data provide aremarkable source of information for analyses of health-care-related effects in radiation oncology.