From Health Research to Social Research: Privacy, Methods, Approaches
ABSTRACT 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.
- "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   . "
Chapter: Administrative Databases[Show abstract] [Hide abstract]
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.Wiley StatsRef: Statistics Reference Online, 06/2015: chapter Administrative Databases: pages 1-17; Wiley Online Library.
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- "Although some countries have linkable population-based health and social welfare registers , large-scale data linkage research is still a fairly novel area with relatively few long-established units, such as those in Australia , Canada  , Scotland , England , as well as the Secure Anonymous Information Linkage System (SAIL) system in Wales . However, it is an area that is developing rapidly with existing work being extended and new units being created. "
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.Journal of Biomedical Informatics 01/2014; 50. DOI:10.1016/j.jbi.2014.01.003 · 2.48 Impact Factor
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- "Administrative Health Care Data.—Populationbased , deidentified administrative data from the Manitoba Population Health Research Data Repository, housed at the Manitoba Centre for Health Policy (MCHP; Roos et al., 2008 "
ABSTRACT: Purpose of the Study:This study evaluates a nursing home Fall Management program to see if residents' mobility increased and injurious falls decreased. DESIGN AND METHODS: Administrative health care use and fall occurrence report data were analyzed from 2 rural health regions in Manitoba, Canada, from June 1, 2003 to March 31, 2008. A quasiexperimental, pre-post, comparison group design was used to compare rates of three outcomes, falls, injurious falls, and falls resulting in hospitalization, by RHA (program vs nonprogram nursing homes) and period (preprogram vs postprogram). Data collectors entered occurrence report information into spreadsheets. This was supplemented with administrative health care use data. RESULTS: The program appears to have benefitted residents-falls trended upward, injurious falls remained stable, and hospitalized falls decreased significantly (0.036-0.021 per person-year [ppy]; p = .043). Compared with nonprogram residents in the postperiod, both groups had the same fall rate, but program residents had significantly fewer injurious falls (0.596-0.746 ppy; p = .02) and hospitalized falls (0.02-0.041 ppy; p = .023). IMPLICATIONS: These results are among a small body of literature showing that Fall Management was associated with improved outcomes in program nursing homes from pre- to postperiod and compared with nonprogram nursing homes. This research provides some support for the benefits of being proactive and implementing injury prevention strategies universally and pre-emptively before a resident falls, helping to minimize injuries while keeping residents mobile and active. Larger scale research is needed to identify the true effectiveness of the Fall Management program and generalizability of results.The Gerontologist 01/2013; 53(5). DOI:10.1093/geront/gns197 · 3.21 Impact Factor