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IntroductionInnovative data platforms (e.g. biobanks, repositories) continually emerge to facilitate data sharing. Extant and emerging data platforms must navigate myriad tensions for successful data sharing and re-use. Two Alberta data platforms navigated such processes and factors regarding administrative, research and nonprofit data: the Child & Youth Data Laboratory (CYDL) and Secondary Analysis to Generate Evidence (SAGE). ObjectivesTo clarify the social and policy factors that influenced CYDL and SAGE establishment and implementation, and the relationships, if any, between these factors and data type. MethodsThis paper involves a qualitative secondary analysis of two developmental evaluations on CYDL and SAGE establishment. Six-years post-implementation, the CYDL evaluation entailed document review; website user analysis; informant interviews (n=30); online stakeholder survey (n=260); and an environmental scan. One-year post implementation, the SAGE evaluation included 15 interviews and document review. We used thematic analysis and comparisons with the literature to identify key factors. ResultsThree (not mutually exclusive) categories of social and policy factors influenced the navigation towards CYDL and SAGE realization: trusting relationships; sustainability amidst readiness; and privacy within social context. For these platforms to be able to manage, link or share data, trust had to be fostered and maintained across multiple, dynamic and intersecting relationships between primary data producers, data subjects, secondary users and institutions. Platform sustainability and readiness required capacity building and innovation. Privacy and information sharing evolved culturally and correspondingly for these data platforms, which required constant flexibility and awareness. ConclusionsThis commentary calls for more empirical research on the value of data re-use or the detriment in not re-using data. While the culture of information sharing is progressing towards greater openness and capacity for data sharing and re-use, successful data platforms must advocate, facilitate and mobilize analysis and innovation using data re-use while being cognizant of social and policy influences.

Background Mandates abound to share publicly-funded research data for reuse, while data platforms continue to emerge to facilitate such reuse. Birth cohorts (BC) involve longitudinal designs, significant sample sizes and rich and deep datasets. Data sharing benefits include more analyses, greater research complexity, increased opportunities for collaboration, amplification of public contributions, and reduced respondent burdens. Sharing BC data involves significant challenges including consent, privacy, access policies, communication, and vulnerability of the child. Research on these issues is available for biological data, but these findings may not extend to BC data. We lack consensus on how best to approach these challenges in consent, privacy, communication and autonomy when sharing BC data. We require more stakeholder engagement to understand perspectives and generate consensus. Methods Parents participating in longitudinal birth cohorts completed a web-based survey investigating consent preferences for sharing their, and their child’s, non-biological research data. Results from a previous qualitative inquiry informed survey development, and cognitive interviewing methods (n = 9) were used to improve the question quality and comprehension. Recruitment was via personalized email, with email and phone reminders during the 14-day window for survey completion. Results Three hundred and forty-six of 569 parents completed the survey in September 2014 (60.8%). Participants preferred consent processes for data sharing in future independent research that were less-active (i.e. no consent or opt-out). Parents’ consent preferences are associated with their communication preferences. Twenty percent (20.2%) of parents generally agreed that their child should provide consent to continue participating in research at age 12, while 25.6% felt decision-making on sharing non-biological research data should begin at age 18. Conclusions These finding reflect the parenting population’s preference for less project-specific permission when research data is non-biological and de-identified and when governance practices are highly detailed and rigourous. Parents recognize that children should become involved in consent for secondary data use, but there is variability regarding when and how involvement occurs. These findings emphasize governance processes and participant notification rather than project-specific consent for secondary use of de-identified, non-biological data. Ultimately, parents prefer general consent processes for sharing de-identified, non-biological research data with ultimate involvement of the child. Electronic supplementary material The online version of this article (10.1186/s12911-018-0683-x) contains supplementary material, which is available to authorized users.

IntroductionYouth and young adults who are involved in justice and correctional system often have complex service needs and experience poor health and social outcomes. To improve outcomes for these young Albertans, it is important to understand their characteristics and service utilization patterns across health and social areas. Objectives and ApproachThe current analysis provides cross-sector service use information on Alberta youth and young adults aged 12 to 25 who were involved in the criminal justice system from 2005 to 2011. Administrative data linked data across multiple Alberta provincial ministries were used for the analysis. These included over 20 programs and services in areas such as health, education, child intervention, disability supports, income support, and justice and corrections. ResultsOffence types and court outcomes varied by social-demographic characteristics such as age, sex, social economic status, and residential mobility. Elevated mental health and high cost health services use was observed among youth involved in the criminal justice system. Access of social programs such as Child Invention service, Child Support services, Income Support and disability support services was more prevalent among youth and young adults who were involved in the justice system. A higher number of offences was associated with worse education and health outcomes. Conclusion/ImplicationsCross-sector data linkage and analysis offer a unique opportunity for better understanding of clients/patients and services/programs at the broad system level. Knowledge gained through linked data can inform cross-ministry policies and integration of services.

IntroductionLinked datasets are important resources for research, but linkage errors can lead to incorrect results. For data security and privacy concerns, when linkage of personal identifiers is performed anonymously, it is difficult to assess the quality of the linked dataset. We describe the method used to perform linkage quality. Objectives and ApproachWe explored how to check the quality of linkages while preserving the privacy of individuals. We also adopted an approach that minimized time and burden on data providers involved in physical verification using randomly-generated appropriate sample sizes. To validate these linkages, data providers were given random samples of 50 unique records from both linked and unlinked individuals across two other Government programs. Data providers were asked to look at the records associated with those individuals in their original datasets. Three types of linkage results were validated: cross-program linkages, cross-program non-linkages, and within-program linkages. Proportions of false-matches and missed-matches were estimated. ResultsTwenty data providers checked their samples with two other programs which gave us a sample of 2000 individuals. The linkage process, based on anonymized personal identifiers, resulted in high true positive and high true negative rates. Agreement between human judges and the linkage software was strong. Results of this exercise and other linkage validation examinations provided confidence in the accuracy of the linkage process. With false matches occurring approximately only 3% of the time and virtually no missed-matches occurring, no adjustments were deemed necessary. Although linkage rates were reassuring, the sample sizes used for comparison were small, so it is expected that there would be significant variation associated with this 3% estimate; caution is advised in its use. Conclusion/ImplicationsProportions of false-matches and missed-matches determine linkage quality which is the base for research when linkages are performed anonymously. A low proportion of false-matches and an absence of missed-matches was an indication of robust linkages.

IntroductionThe cultural revolution of data sharing is becoming a global movement. It allows for scientific replication and verification of research results, avoiding research duplication, and enabling greater transparency and knowledge mobilization with a relatively low cost. However, privacy protection and data security are critical concerns for human-subject related data sharing. Objectives and ApproachIn order to facilitate data sharing and engage various stakeholders to better inform policy and practice while protecting privacy, SAGE (Secondary Analysis to Generate Evidence) was established by PolicyWise for Children and Families. It is a collaborative data repository platform that connects stakeholders through secondary use of data. SAGE was built to link, manage, and share research data, community service data, and administrative data related to health and social well-being. Governance and technical processes are in place to ensure that data depositors are involved in decision-making, and data accessed by collaborators are secured and re-identification risks assessed. ResultsSAGE has been in operation for over a year. Through engagement with the research and non-profit communities, SAGE now offers ten data assets. Discovery is facilitated through well-documented metadata through NADA and Dataverse. Six new collaborative projects have been initiated through SAGE. SAGE is working actively with local non-profits to liberate data to generate evidence and collaborate with each other on common goals. SAGE has helped these organizations understand the legal and legislative barriers to data sharing, and build the technical capacity to further this goal. Discussions are underway with Alberta public entities on how SAGE can support the linkage and governance processes in the use of administrative data. Conclusion/ImplicationsSAGE is putting the governance processes and security practices in place to fill a need for a facilitated data sharing model for sensitive data. SAGE is supporting the cultural shift towards data sharing and reuse by fostering trust and collaboration among researchers, non-profit and government ministries.

IntroductionYouth with complex-needs are vulnerable as a consequence of exposure to social adversity and/or chronic health conditions, and are at a high risk of school failure and justice involvement. Information about the patterns of service use across government sectors that influence the life outcomes of complex-needs youth is unknown. Objectives and ApproachYouth with complex needs often engage with multiple services across multiple government sectors for extended periods of time. Understanding the patterns and trajectory of their service use may inform programs, decision makers and government in the optimal allocation of resources to increase their life outcomes. It may reveal where and when interventions would be most effective to improve the life course for vulnerable youth. In this study, through a unique approach to link over 20 administrative longitudinal datasets and a novel trajectory clustering technique, the patterns of service use among complex-needs young Albertans is revealed and visualized. ResultsA trajectory clustering technique was applied to reveal patterns of service use among complex-needs individuals. Compared to the general population, higher proportions of youth with complex needs lived in low socio-economic neighborhoods, suffered from mental health issues, were high cost health service users, and had lower rates of high school completion. Furthermore, youth having complex needs for a longer period of time and who required multiple complex services in a given year had the poorest outcomes, in terms of high school completion, mental health issues, and other health problems. The majority of complex-needs youth came in contact with services via the education system, followed by child services/welfare. Conclusion/ImplicationsThe trajectories of service use among complex-needs youth reveals that these individuals are primarily identified through education. Consequently, educational supports would best address the development of effective programs including mental health supports and other needs.

IntroductionData collected by myriad not-for-profit (NFPs) agencies while providing social services represent a significant untapped source of intelligence. While much research has been conducted on the governance and capacity to share administrative and research data, little work has been done in the area of NFP data sources. Objectives and ApproachSix NFP agencies in Calgary participated in a data sharing project to measure various aspects of poverty. This collaboration required understanding the legal, ethical, policy and data challenges to working with data collected in the NFP sector. This case study will expose (a) the legal analysis on legal and governance issues for, and obligations of, NFPs when aiming to share and re-use information beyond service delivery in Alberta, Canada; and (b) the practical and policy challenges faced by the NFPs and repository. The legal analysis involved a systematic search of academic and grey literature; relevant legislation and case-law (especially privacy law). ResultsThe legal analysis demonstrated three key things. First, in many circumstances an NFP is not held to any information-handling legal obligations. This does not absolve NFPs from social privacy expectations, especially involving vulnerable populations. Second, privacy best practices are available to NFPs from other more-regulated sectors and from NFP sector standards. The trifecta of purpose, reasonableness and minimal extent are critical. Third, adhering to privacy best practices would not be overly costly, more efficient, and less risky of negative publicity and lost public trust from privacy complaints. These findings informed the NFP data sharing project. The six participant NFPs varied greatly in their approach to consent, governance and information-handling, which affected their data-readiness for cross-organizational data linkage and analysis. Conclusion/ImplicationsUnlike government, most NFPs have limited experience with data linkage. This paper informs ethical approaches to include NFP data in broad cross-sector data linkage. Appropriate data governance is imperative for data sharing amongst NFPs, researchers and public organizations, which promotes community service delivery, evaluation and improvements to benefit vulnerable families.

IntroductionLinking administrative data provides valuable information about individuals using government services and can be very useful for policy-makers in improving and developing services and policies. The Child and Youth Data Laboratory (CYDL) links and analyses administrative data from Alberta Government ministries to provide evidence for policy and program development. Objectives and ApproachData from 20 programs of six Government of Alberta ministries (Advanced Education, Education, Health, Children’s Services, Community and Social Services, and Justice and Solicitor General) were linked anonymously. The data spans six years from 2005/06 to 2010/11 and consists of almost 50 million records corresponding to over 2 million unique Albertans aged 0 to 25 years. A data visualization tool called the Program Overlap Matrix summarises the overlap rates among the programs. It is comprised of a matrix of squares, where each cell represents the overlap between two programs. ResultsThe Program Overlap Matrix is publically available at https://visualization.policywise.com/P2matrix/. It consists of overlap rates between programs in any study year (2005/06 to 2010/11), individual years, the first year vs. future years, and the last year vs. previous years which can be used to answer many policy-related questions such as: other service use (e.g., what other services do ESL students use?), over-represented programs (e.g., in what programs are Child Care Subsidy clients over-represented?), resilience (e.g., what is the proportion of Child Intervention clients in post-secondary institutions?), transitions (e.g., what types of services do students with special needs receive as they transition to adulthood?), and time trend (e.g., what types of services did Income Support clients receive in the past?) Conclusion/ImplicationsThe program overlap matrix is a powerful tool to discover relationships between programs. It is a useful instrument to inform public and policy-makers about the overlap rates between government programs. It can be used to answer a variety of policy-related questions.

Information is increasingly digital, creating opportunities to respond to pressing issues about human populations in near real time using linked datasets that are large, complex, and diverse. The potential social and individual benefits that can come from data-intensive science are large, but raise challenges of balancing individual privacy and the public good, building appropriate socio-technical systems to support data-intensive science, and determining whether defining a new field of inquiry might help move those collective interests and activities forward. A combination of expert engagement, literature review, and iterative conversations led to our conclusion that defining the field of Population Data Science (challenge 3) will help address the other two challenges as well. We define Population Data Science succinctly as the science of data about people and note that it is related to but distinct from the fields of data science and informatics. A broader definition names four characteristics of: data use for positive impact on citizens and society; bringing together and analyzing data from multiple sources; finding population-level insights; and developing safe, privacy-sensitive and ethical infrastructure to support research. One implication of these characteristics is that few people possess all of the requisite knowledge and skills of Population Data Science, so this is by nature a multi-disciplinary field. Other implications include the need to advance various aspects of science, such as data linkage technology, various forms of analytics, and methods of public engagement. These implications are the beginnings of a research agenda for Population Data Science, which if approached as a collective field, can catalyze significant advances in our understanding of trends in society, health, and human behavior.

ObjectivesUsing existing data for research can generate new knowledge and evidence for policy with relatively little cost. Privacy concerns are paramount in such secondary usage of data collected on human subjects. Information privacy protection and data security are critical considerations in reuse and repurposing of data especially linked data, longitudinal data, and large amounts of data. Data sharing and privacy protection are both in the public interest and we need to assess the risk of “doing” (sharing) as well as the risk of “not doing” (not sharing or not protecting). ApproachThe Alberta Centre for Child Family and Community Research (the Centre) establishes the Child Youth Data Lab that links and analyzes administrative data from multiple provincial ministries and the Child Data Centre of Alberta that repurposes research data and manages its access for reuse. The Centre partners with provincial Office of the Information Privacy Commissioner, Research Ethics Boards and leaders in the research communities and technology industry to design and develop measures to enable secondary use while safeguarding the data, and to explore and adopt best practices on data sharing processes, governance, and technologies. ResultsIn principle current privacy laws and regulations provide good guidance in collection, use, and disclosure of data, however there is a lack of consistency in the interpretation of these laws at the operational level with regard to secondary data use. The experiences of establishing different data sharing models at the Centre through multiple initiatives are discussed. Cross-sectoral broad partnership brings understanding and builds trusting relationships, which are crucial to establishing data sharing processes. The recognition of the significance of secondary data use to provide direction for policy and program development at the executive level provides commitment for data sharing initiatives. Strong governance structure consists multi-level ministry and multiple stakeholder involvement ensures ongoing support and engagement. The highest data security standards and anonymous solution for data linkage enables the sharing of data with good privacy protection. ConclusionSecondary use of data to improve system performance and contributing to scientific discovery has been broadly recognized. A balance between utility and privacy can be realized through broad partnership in building proper governance, technology, processes and policies.