From Health Research to Social Research: Privacy, Methods, Approaches

Manitoba Centre for Health Policy, Department of Community Health Sciences, Faculty of Medicine, University of Manitoba, 408-727 McDermot Avenue, Winnipeg, MB, Canada R3E 3P5.
Social Science & Medicine (Impact Factor: 2.89). 02/2008; 66(1):117-29. DOI: 10.1016/j.socscimed.2007.08.017
Source: PubMed


Information-rich environments in Canada, Australia, and the United Kingdom have been built using record linkage techniques with population-based health insurance systems and longitudinal administrative data. This paper discusses the issues in extending population-based administrative data from health to additional topics more generally connected with well being. The scope of work associated with a multi-faceted American survey, the Panel Study in Income Dynamics (PSID), is compared with that of the administrative data in Manitoba, Canada. Both the PSID and the Manitoba database go back over 30 years, include families, and have good information on residential location. The PSID has emphasized research design to maximize the opportunities associated with expensive primary data collection. Information-rich environments such as that in Manitoba depend on registries and record linkage to increase the range of variables available for analysis. Using new databases on education and income assistance to provide information on the whole Manitoba population has involved linking files while preserving privacy, scaling educational achievement, assessing exposure to a given neighborhood, and measuring family circumstances. Questions being studied concern the role of the socioeconomic gradient and infant health in child development, the comparative influence of family and neighborhood in later well being, and the long-term effects of poverty reduction. Issues of organization of research, gaps in the data, and productivity are discussed.

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    • "Encrypted identifiers that facilitate data linkage permit following students across several school systems and, where feasible, into other domains such as health and social services. Statistical techniques originally developed by Mosteller and Tukey have helped creating population-based achievement indices using multiple data sources [13] [14] . "
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    ABSTRACT: Administrative databases are often used to manage systems or to investigate research questions. The data may be derived from population registries, vital statistics or other records of life events, or from information on services. Questions that may be addressed by administrative datasets include the determinants of variation in utilization, costs, and outcomes of different services. Factors associated with individuals, types of organization, or geography may all be studied. Strengths and weaknesses of this approach are reviewed, and several new directions identified.
    Full-text · Chapter · Jun 2015
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    • "Record linkage of files from the Ministry of Education (the education data) and the Ministry of Entrepreneurship, Training and Trade (the income assistance data) with the registry allowed identification of cohort members in the province but not enrolled in school [38]. Linkage quality was high; for example, only 2.8% of all students enrolled in 2002 could not be linked to the December 2001 registry [42]. "
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    ABSTRACT: Background Well-organized administrative data with large numbers of cases (building on linked files from several government departments) and a population registry facilitate new studies of population health and child development. Analyses of family relationships and a number of outcomes--educational achievement, health, teen pregnancy, and receipt of income assistance--are relatively easy to conduct using several birth cohorts. Looking both at means/proportions and at sibling correlations enriches our study of opportunity and well-being in late adolescence. With observational research possibly exaggerating the causal effects of risk factors, sibling comparisons involving individuals sharing both many family characteristics and many genes help deal with such criticisms. Methods This paper uses a rich dataset from one Canadian province (Manitoba) covering a wide range of geographical areas (cities to rural regions). Influences on opportunity and well-being are analyzed looking at both means/proportions and sibling correlations. We measure a variety of outcomes that may reflect different causal influences. A creative application of linear programming advances the use of data on residential location. Results Predicting educational achievement using available variables was much easier than predicting adolescent health status (R-square of .200 versus R-square of .043). Low levels of educational achievement, high levels of teenage pregnancy, and high sibling correlations outside Winnipeg and within Winnipeg’s lower income areas highlight inequalities across socioeconomic and geographic backgrounds. Stratifying our analyses by different variables, such as income quintiles, reveals differences in means and correlations within outcomes and across groups. Particular events--changes in mother’s marital status and in place of residence--were associated with less favorable outcomes in late adolescence. Conclusion Our findings suggest a paradox: Canadian developmental outcomes through late adolescence appear quite similar to those in the United States, even though intergenerational mobility in Canada is closer to mobility in the Nordic countries than to that in the United States.
    Full-text · Article · May 2014 · BMC Public Health
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    • "Although some countries have linkable population-based health and social welfare registers [1], large-scale data linkage research is still a fairly novel area with relatively few long-established units, such as those in Australia [2], Canada [3] [4], Scotland [5], England [6], as well as the Secure Anonymous Information Linkage System (SAIL) system in Wales [7]. However, it is an area that is developing rapidly with existing work being extended and new units being created. "
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    ABSTRACT: With the current expansion of data linkage research, the challenge is to find the balance between preserving the privacy of person-level data whilst making these data accessible for use to their full potential. We describe a privacy-protecting safe haven and secure remote access system, referred to as the Secure Anonymised Information Linkage (SAIL) Gateway. The Gateway provides data users with a familiar Windows interface and their usual toolsets to access approved anonymously-linked datasets for research and evaluation. We outline the principles and operating model of the Gateway, the features provided to users within the secure environment, and how we are approaching the challenges of making data safely accessible to increasing numbers of research users. The Gateway represents a powerful analytical environment and has been designed to be scalable and adaptable to meet the needs of the rapidly growing data linkage community.
    Full-text · Article · Jan 2014 · Journal of Biomedical Informatics
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