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Ouvrage récompensé par l' Académie des sciences morales et politiques. ; Mode of access: Internet.

Sixty juvenile offenders placed on probation in three provincial centers surrounding the city of Melbourne, Australia were studied over a 15 month period. A comparison of the recidivist half of this group with those who committed no further offenses revealed some striking differences in the social functioning of their respective families as well as in the latter's attitude toward their child, their acceptance or rejection of a resocialization role, and the degree of their cooperation with the probation agency. The implications for correctional policy lead to a suggestion for an intervention strategy which, depending on a family's level of functioning, utilizes degrees of family-agency partnership.

IntroductionICES is an entity in Ontario, Canada that collects and uses the personal health information (PHI) of individuals for evaluation, planning and monitoring of the provincial health system. It currently does not have legal authority to collect PHI from, or disclose PHI to, municipalities for the purpose of supporting evidence-based policymaking and enabling "Smarter Cities".
Objectives and ApproachTo assess how ICES could allow municipalities to access PHI, while maintaining strong privacy and security data protection, we first: (i) explored the legal data trust model as a vehicle for broader collection and use of municipal data, and (ii) analyzed the regulatory changes and type of framework that would enable broader access and use of PHI by municipalities. Following this and to demonstrate the value of access to ICES data for municipal planning, we identified a case project involving a municipal health stakeholder. Leveraging ICES' remote access model, two local public health analysts performed analytics on de-sensitized, individual-level data in a secure analytic environment.
ResultsWe determined that a legal data trust is not the appropriate model for the type of data sharing envisioned, but rather, a data governance and ethical use framework complimentary to a new legal regime for Smart Cities would be optimal. In Phase II the local municipal partner was able to identify several use cases for the ICES data that would support local policy making; access to these data was considered a critical enabler to improved evidence-based decision making.
Conclusion / ImplicationsAllowing municipal policy makers to use data under a complimentary framework to a new legal regime, may improve policy and produce direct economic impact for municipalities where evidence needed for decision-making is lacking; representing a practical step forward towards Smart Cities.

ABSTRACTObjectivesPrior to the launch of ICES Data & Analytic Services (DAS) in March 2014, only ICES scientists and analysts could access ICES data, and data could only be accessed at physical ICES locations. The DAS infrastructure, which allows public sector researchers to work with coded record level data remotely through a secure virtual environment, together with broader trends including high profile reports that call for increased access to data and the Ontario government's Open Data initiative, prompted ICES to launch a pilot project to explore potential DAS work with the private sector.
ApproachThree mandatory principles were established for all work with the private sector: (i) alignment with ICES' mission, vision and values; (ii) transparency; (iii) private sector work must not detract from ICES' research institute work. The pilot included: a jurisdictional scan; informal conversations with private sector organizations to determine potential services/studies of interest; extensive discussions with data partners; the selection and conduct of two pilot studies; focus groups with members of the general public and scientists; external advice on business model options; and an external evaluation of the pilot. No changes to data sharing agreements or ICES processes were required as work with the private sector and public sector are equally allowed under Ontario law.
ResultsThe two pilot studies were successfully completed. The first study "The disease burden of gout in Ontario: A real world data retrospective study" was performed by researchers at IMS Brogan (a healthcare analytic services provider) who were provided with access to coded record-level data using the DAS iDAVE environment and performed their own analyses. In the second pilot study, "The impact of adherence to biologics on healthcare resource utilization in rheumatoid arthritis", Janssen researchers established the research question and study design, and DAS staff and scientists provided advice about data holdings, performed the analyses, and provided Janssen and three government-funded decision making bodies with results tables. Research Ethics Board approval was required for both studies, and both private sector organizations are in the process of publishing findings.
ConclusionsICES was able to work with private sector organizations without compromising the three principles. Based on the evaluation of the private sector pilot, and the findings from the focus groups, ICES will begin offering limited analytic services to private sector researchers beginning June 2016 under ICES' existing corporate structure, and bring recommendations regarding ongoing operations to the ICES Board in June 2017.

ABSTRACTObjectivesThere is a growing need to broaden access to administrative health data in order to support decision making and planning by health system stakeholders. An initiative funded by the Ontario Ministry of Health and Long-Term Care, the Applied Health Research Question (AHRQ) portfolio leverages the linked administrative health data holdings and the scientific and clinical expertise at ICES to answer questions generated by stakeholders that will have a direct impact on health care policy, planning or practice.
ApproachEligible requesters include government ministries, health care providers and planners. Requests detail the purpose of the research question, the related scientific literature, and the planned use and intended impact of the research findings. An internal review team meets monthly to adjudicate; requests demonstrably needing research findings rapidly are adjudicated on an ad hoc basis. Eligible requests are those that aim to inform evidence-based decision making, do not advocate for a particular answer and are feasible in terms of data availability. All projects are reviewed by the internal privacy office to ensure that use of the administrative health data is in accordance with both data sharing agreements and legislation governing use of personal health information. At no cost to the requesting organization, ICES scientists and research staff formulate the analysis plan, conduct the analysis and prepare the research product (data tables, a slide deck and/or a written report); and, may opt to publish noteworthy findings. All research products must be cleared for risk of re-identification prior to being shared externally.
ResultsRequests have steadily increased from 43 submissions in fiscal year 2012/13, to 59 in 2014/15 and 74 to date in 2015/16. In fiscal year 2014/15, provincial government and government agencies were the most frequent requesters (39%), followed by hospitals and other health care providers (19%), disease advocacy groups (12%) and professional associations (10%). Requests include assessment of health care utilization; health system performance and evaluation; and chronic disease prevalence and treatment. Time to complete reports varies from 5 days to 24 months, depending on project complexity and requirements. Requesters report that AHRQ research findings have influenced decision-making, policy development and health care practice; and have inspired future research.
ConclusionThis initiative demonstrates the value and feasibility of using the linked administrative health data to answer questions to meet the unique needs of health planners and policymakers, and presents an opportunity for collaboration beyond the academic research community.

BackgroundIn December 2017 the Canadian Institutes of Health Research (CIHR) issued a request for proposals to develop a pan-Canadian health data platform. This platform will enable cross-jurisdictional research by facilitating the use of rich provincial and national data and ensure engagement with patients and specific populations including Indigenous partners. Academics and policy makers from across Canada operating under the banner of the Pan-Canadian Real-World Health Data Network (PRHDN) have joined forces to address this call.
ObjectivesCreate national infrastructure that is built once then made available for research, benchmarking, performance monitoring, multi-jurisdictional evaluations and inter-jurisdictional comparisons to address pressing health and social policy problems in Canada.
MethodsOur approach will address several issues including creating significant efficiencies in data access, streamlining cross provincial/ territorial ethics and access approvals, establishing standards for data and methods harmonization and providing innovative and privacy-conscious solutions to data access and use. The presentation will focus on the plan to create harmonized common data, algorithms and analytic protocols, and link administrative data to electronic medical records and clinical trials to create an integrated and documented infrastructure for pan-Canadian studies. Comparisons to PopMedNet and the Sentinel Initiative in the US will be made.
ConclusionProvincial centres across Canada hold rich sources of health and social data that are linkable at the person-level. With the exception of standardized data managed by the Canadian Institute for Health Information (CIHI), these data are often not comparable from one province to another, thereby limiting use to single-province studies. There is growing interest in Canada in creating an environment that would enable cross-jurisdictional data sharing and analysis' and in sharing experiences to make effective use of linkable administrative data.

Background and rationale There is widespread enthusiasm to improve health through the application of artificial intelligence and machine learning (AI/ML) methods to large population-level health datasets. Achieving this may require successful collaboration between institutions as well as between computer scientists (CS), machine learning researchers (MLR) and health service researchers (HSR).
Main Aim Describe lessons learned in creating the Health Artificial Data and Analysis Platform (HAIDAP) in Ontario, Canada.
Methods/Approach A partnership between a HSR institute (ICES), an AI/ML institute (Vector) and a high-performance computing center (HPC4H) was initiated in 2017 to enable the application of AI/ML methods to population-level health data for the province of Ontario (population 14M). We describe lessons learned (and being learned) following the HAIDAP's launch.
Results The HAIDAP was launched in 2019. Major learnings include: 1) importance of institutional partnerships and alignment with institutional strategies; 2) potential of joint institutional risk-sharing models; 3) need for scientific collaborations bridging disciplines around joint research projects; 4) sensitivity to different scientific cultures (e.g., academic prestige of conference proceedings for MLR vs journal publications for HSR; traditional statistical vs. ML model assumptions); 5) differences in research timeline expectations; 6) different experience with and expectations for access to de-identified routinely collected data (e.g., need for research ethics committee project approvals and privacy impact assessments); 7) developing data access models that enable greater flexibility (e.g., importing code or using open source tools); 8) broadening data access models to allow modern high-dimensional exploratory data analysis; 9) obtaining support of information/privacy regulator; 10) the hardware is the (relatively) easy part compared to other success factors.
Conclusion The HAIDAP has enabled multi-disciplinary collaborations and novel AI/ML research of Ontario's population-level health data. Collectively we have learned that additional effort is required to develop systems and processes enabling more efficient access to data and analytic tools for the analysis of administrative health data.

ICES upholds a strong reputation for generating high-quality evidence to inform policy and practice through its collaborations with a broad range of health system stakeholders including government policymakers and healthcare providers including clinicians. Supported by the Ontario Ministry of Health and Ministry of Long-Term Care, the ICES Applied Health Research Question (AHRQ) Program leverages the data holdings and, scientific and clinical expertise to generate evidence tailored to the information needs of requestors. This paper outlines the approach, process, strengths, challenges and the resulting influence and impact to the healthcare landscape in Ontario.

ObjectiveThe James and Hudson Bay Region, consisting of six remote Indigenous communities, have experienced barriers accessing regional health data. To inform local health planning, the Minomathasowin Healthy Living department in the Weeneebayko Area Health Authority (WAHA), ICES and Laurentian University developed a Collaboration, to co-create enhanced Indigenous data stewardship.
ApproachThe Collaboration combines expertise in Indigenous knowledge with quantitative and qualitative analyses to develop relevant data intended for public dissemination. Through a community-driven and strength-based approach, local knowledge guides the direction of the research. Indigenous data governance principles are applied, supporting local data ownership, and supplementing local knowledge on population health issues. This ensures the development of research projects that have meaningful impacts. The Collaboration is part of a larger partnership and is continually engaging local Indigenous stakeholders. Protocols ensure research is done in a manner that respects and reflects community well-being and is undertaken in a good way.
ResultsThe Collaboration is an ongoing, living initiative and has enabled WAHA to become a local hub for Indigenous stakeholders to obtain health data for their respective communities. It adheres to the importance of following protocols within Indigenous communities, acknowledging qualitative research activities can be undertaken at the community-level. Projects from this Collaboration identify and prioritize the most pressing health issues impacting the Region including mental health and addictions, COVID-19 surveillance, hospitalization trends, and the prevalence of lupus. The success of the Collaboration is demonstrated through increased requests from the Region to WAHA for support on health planning and decision-making. Data access barriers in the Region are being addressed through the combined expertise of the Collaboration and local knowledge. This approach is enhancing Indigenous data stewardship.
ConclusionsThe Collaboration advocates for Indigenous-led and -driven research that recognizes the value of combining local knowledge with quantitative and qualitative data analyses to put communities first. The Collaboration supports equitable data access and the development of relevant research projects. This is leading to sustainable, impactful health planning for the Region.

IntroductionThe Ontario Brain Institute has developed Brain-CODE, an informatics platform designed to support the collection, storage, federation, sharing and analysis of different neuroscience research data types across several brain disorders. Linking such "deep" research data with "broad" health administrative data allows for improved characterization of disorders and supports the development of related health and social policies (Anderson et al., 2015). A privacy preserving record linkage protocol, developed through the Indoc Consortium, has been used to facilitate such linkages between Brain-CODE and administrative data holdings at the Institute for Clinical Evaluative Sciences (ICES; e.g., emergency department use, inpatient records, prescription drug utilization) (Gee et al., 2018).
Objectives and ApproachThree linkage pilots in the areas of neurodevelopmental disorders, epilepsy, and stroke research have been completed with >99% success match rates across all projects. However, each of these projects required a significant amount of human and computational resources to complete. With other similar data linkages being planned, it was determined that a more permanent solution was required rather than completing linkages on a project-by-project basis. The governance and technical elements to support the creation and maintenance of such a crosswalk between Brain-CODE and ICES were reviewed with an implementation plan subsequently developed.
Results:A methodology for creating a crosswalk between Brain-CODE and ICES has been established. The same privacy preserving record linkage protocol, as used in the previous linkage pilots, will support the creation of this crosswalk. A plan has been established to update this crosswalk annually to account for new study participants on Brain-CODE.
Conclusion / ImplicationsThe creation of this crosswalk will allow for a more streamlined approach of data linkage between Brain-CODE and ICES. Such an approach can significantly reduce overall resourcing requirements, enable more efficient data linkages, and contribute to the coupling of "broad" and "deep" data.