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This report draws on data that is currently in place that was available for First Nations Populations on Reserve. There is a goal in moving beyond this current state and wherever possible by implementing new forms of data collection, drawing upon different data sources, and framing research questions that include Inuit and Metis populations and communities and First Nations residents off reserve.

Over the past year, Beirut has witnessed a civil revolution, the COVID-19 pandemic, its worst economic crisis in decades, and most recently one of the largest non-nuclear explosions in history.This explosion had devastating effects on the city’s social, economic, and health infrastructure.

With advancement in information technology, health data are collected at an unprecedented rate. Accurate understanding, analysis and interpretation of complex, multidimensional data is critical to understand wicked health problems to make timely decisions and interventions. Injury problems as classified as wicked health problems, they are associated with numerous individual, social, environmental and policy related factors. Wicked injury problems are multidimensional and require a multidisciplinary approach for effective solutions. We studied the integration of Visual Analytics (VA) methods to solve wicked injury problems. The science of VA leverages information visualization techniques and computational analysis methods to facilitate understanding of heterogeneous data and support decisions about dynamic injury situations. We designed a proof-of-concept prototype - interactive Analytical Injury Dashboard (iAID) and demonstrated its application with injury stakeholders, using Canadian CHIRPP injury data. We adopted the Paired Analytics (PA) methodology to assess the interface design, layout and functionality of the iAID. Inspired by the Delphi method, the study adapted (PA) methodology and introduced a novel methodology - Group Analytics (GA), which was pilot tested and refined for the final research study design. GA was used to evaluate the impact of collaborative VA on facilitating problem solving and supporting decision-making within the injury sector. We conducted seven PA sessions and two GA sessions. Data included stakeholders observations, audio and video recordings, questionnaires and follow up interviews, and were analyzed to gain in-depth understanding of the collaborative VA process and its impact on problem solving and decision-making. Results demonstrated that iAID helped injury stakeholders to convert data into useful information, facilitate task completion, and support problem solving and decision-making. Based on the Joint Activity Theory and distributed cognition framework, analysis revealed that GA triggered the emergence of Common Ground among stakeholders, which evolved throughout the GA sessions to enhance their interactions, communication, coordination of joint activities and ultimately their collaboration on problem solving and decision-making. These findings will help inform the design of innovative VA tools that assist health professionals in analyzing and interpreting complex health data, and will introduce new metrics to enhance group collaboration to support timely decisions and actions.

Child and youth injury prevention research in Canada has lagged behind other Organisation for Economic Co-operation and Development nations, despite existing surveillance systems and longitudinal data. A critical need to improve access to the available data, as well as need to tailor its display and interpretation, was identified by injury prevention stakeholders involved in research, policy, and practice. The Canadian Atlas of Child and Youth Injury Prevention ("the Atlas") was developed to address this need. Following a series of iterative consultation meetings and a pilot testing session, the Atlas was scaled up with national data. Two testing sessions were held to evaluate the tools. The Atlas is comprised of three main components: data, indicators, and visualizations. The accessibility of the dashboard is enhanced by customization of data visualizations and data outputs to suit the user's needs. Overall feedback indicated that the tools were easy to use, and that the interface was intuitive and visually appealing. The Canadian Atlas of Child and Youth Injury Prevention provides readily accessible information to injury prevention practitioners, policy makers and researchers, helping to chart pathways to success in improving the child and youth injury prevention system in Canada.

Background: Accurate understanding of complex health data is critical in order to deal with wicked health problems and make timely decisions. Wicked problems refer to ill-structured and dynamic problems that combine multidimensional elements, which often preclude the conventional problem solving approach. This pilot study introduces visual analytics (VA) methods to multi-stakeholder decision-making sessions about child injury prevention; Methods: Inspired by the Delphi method, we introduced a novel methodology���group analytics (GA). GA was pilot-tested to evaluate the impact of collaborative visual analytics on facilitating problem solving and supporting decision-making. We conducted two GA sessions. Collected data included stakeholders��� observations, audio and video recordings, questionnaires, and follow up interviews. The GA sessions were analyzed using the Joint Activity Theory protocol analysis methods; Results: The GA methodology triggered the emergence of ���common ground��� among stakeholders. This common ground evolved throughout the sessions to enhance stakeholders��� verbal and non-verbal communication, as well as coordination of joint activities and ultimately collaboration on problem solving and decision-making; Conclusions: Understanding complex health data is necessary for informed decisions. Equally important, in this case, is the use of the group analytics methodology to achieve ���common ground��� among diverse stakeholders about health data and their implications.