Suchergebnisse

ObjectivesData sharing and administrative data access for multi-jurisdictional research must accommodate all local requirements for the protection of personal information and personal health data. Navigating the different safeguards for data sharing found in all relevant Canadian provincial and territorial legislation requires exploring innovative, privacy compliant solutions.
ApproachHealth Data Research Network Canada (HDRN Canada) and one of its provincial data centre partners, New Brunswick Institute for Research, Data and Training (NB-IRDT), are undertaking unconventional approaches to data sharing that balance legislative compliance and data access needs. Three approaches are being pursued: harmonizing data sharing agreements between a national longitudinal study and 10 provincial data centres; facilitating 4 individual data sharing agreements with one regional cohort of a nationwide study; and coordinating data sharing between 4 provincial government departments and one national data centre. Each approach has unique features that presented problems needing innovative resolutions.
ResultsThe experiences and challenges of these three approaches to data sharing for multi-regional research have been perplexing but ultimately are leading to productive outcomes. Learnings acquired enable partners to move beyond anecdotal perceptions of data sharing limitations to practical solutions that can be applied in future data sharing partnerships.
The ongoing project management approach of these initiatives identified a core set of somewhat predictable devices to ensure the advancement of simultaneous multiple regional data sharing agreements. These include the assignment of a project coordinator role, clear and ongoing communication, and the ability to negotiate and manage expectations. More innovative, however, is the roadmap that evolved, laying out the necessary (previously unanticipated) measures and sequence in which they should occur for the most expedient outcome.
ConclusionTo harness the potential of multi-regional research in Canada, provinces and territories must identify feasible and efficient data sharing solutions. The identification of adoptable and replicable legislatively compliant data sharing practices will increase potential data accessibility. This will increase available data and data platforms for research informed policy decisions.

ObjectiveTo describe how the Better Evidence Better Outcomes Linked Data (BEBOLD) platform has been used to partner with government agencies to generate evidence to support service reform that contributes to improving outcomes for children and families in contact with the child protection system.
ApproachData was drawn from the BEBOLD platform, a whole-of-population linked de-identified administrative data platform for all children in South Australia born from 1991-2016 (n~500,000), as well as their parents. Data linked included birth registrations, perinatal statistics, child protection services, family health services, education, youth justice, housing and homelessness, emergency department presentations and hospitalisation, as well as adult drug and alcohol services.
ResultsWe present case studies illustrating how the BEBOLD platform has been used to 1) investigate the descriptive epidemiology of child protection contact patterns with a focus on priority populations (e.g. young parents); 2) describe service interactions of child protection populations in a way that highlights prevention potential (e.g. the overlap between public housing and child protection); and 3) identify policy defined target populations to inform contracting of support services (e.g. estimate counterfactual reunification rates for a defined population to inform development of a Social Impact Bond).
ConclusionUsing linked data to take an intelligent system view of potential priority populations can inform policy and service delivery in a resource restricted setting. Descriptive epidemiology of child protection contact patterns, population sizes, transitions, and characteristics can aid services to explore elements of service or system design including eligibility criteria.

Dieser Jahresbericht stellt die Arbeiten des bei GESIS angesiedelten Forschungsdatenzentrums Wahlen
(FDZ Wahlen) aus dem Jahr 2012 dar. Angebunden an bereits bestehende Dienstleistungsangebote und
Forschungsaktivitäten von GESIS ist das Forschungsdatenzentrum seit 2009 Bestandteil der Forschungsdateninfrastruktur
des Rats für Sozial- und WirtschaftsDaten (RatSWD). Das Forschungsdatenzentrum
knüpft an die Schwerpunktsetzung von GESIS im Bereich der Umfrage- und Wahlforschung
an. Hierzu zählen Bundes- und Landtagswahlstudien, Politbarometer, DeutschlandTrend und Forsa-Bus.
Als größtes Projekt kam 2009 die German Longitudinal Election Study (GLES) hinzu. Zu den Aufgaben
des Forschungsdatenzentrums Wahlen gehören die Aufbereitung und ausführliche Dokumentation von
Primärdaten im Sinne ihrer langfristigen Nutzbarkeit in Forschung und Lehre, wissenschaftliche Mehrwertdienste,
Wissensvermittlung und Forschung. Im Jahr 2012 wurden mehrere GLES-Datensätze und
die Jahreskumulationen des ZDF-Politbarometers 2011 (West/Ost), der ARD-DeutschlandTrend 2011,
der Forsa-Bus 2011 sowie mehrere Studien der Konrad-Adenauer-Stiftung aufbereitet und veröffentlicht.

In an increasingly digital economy, mastering the quality of data is an increasingly vital yet still, in most organizations, a considerable task. The necessity of better governance and reinforcement of international rules and regulatory or oversight structures (Sarbanes Oxley, Basel II, Solvency II, IAS-IFRS, etc.) imposes on enterprises the need for greater transparency and better traceability of their data. All the stakeholders in a company have a role to play and great benefit to derive from the overall goals here, but will invariably turn towards their IT department in search of the answ.

Efforts to collaboratively manage the risk of flooding are ultimately based on individuals learning about risks, the decision process, and the effectiveness of decisions made in prior situations. This article argues that much can be learned about a governance setting by explicitly evaluating the relationships through which influential individuals and their immediate contacts receive and send information to one another. We define these individuals as "brokers," and the networks that emerge from their interactions as "learning spaces." The aim of this article is to develop strategies to identify and evaluate the properties of a broker's learning space that are indicative of a collaborative flood risk management arrangement. The first part of this article introduces a set of indicators, and presents strategies to employ this list so as to systematically identify brokers, and compare their learning spaces. The second part outlines the lessons from an evaluation that explored cases in two distinct flood risk management settings in Germany. The results show differences in the observed brokers' learning spaces. The contacts and interactions of the broker in Baden-Württemberg imply a collaborative setting. In contrast, learning space of the broker in North Rhine-Westphalia lacks the same level of diversity and polycentricity.

AbstractThe following figure (p. 53) was omitted from "Strategic Planning for Research and Management of the Albacore Tuna Fishery" by D. J. Mackett, published in Systems Research Vol. 2, No. 3, pp. 201–210. This figure, Fig. 4, is a graphic display of the final results of the design process described in the article.

Insun Kim and Kenneth G. Keppel. ; Caption title. ; Shipping list no.: 98-0100-P. ; "December 1997." ; Also available via Internet from the NCHS web site (PDF file only). ; Includes bibliographical references (p. 10).