Suchergebnisse

EDITORIAL
The beginning of 2017 triggered a change in leadership at the International Population Data Linkage Network (IPDLN), as Professor David Ford's two year term as director of the network wound down, and the baton was handed on to new Canadian co-leadership, from the Institute for Clinical Evaluative Sciences in Ontario, and the O'Brien Institute for Public Health at the University of Calgary. David Ford's success and energy during his term were such that our two organizations decided we needed to team up to jointly direct the IPDLN for the next two years. This was endorsed by the IPDLN membership in the lead up to the August 2016 IPDLN conference in Wales, and we are delighted to co-direct this growing network.
First off, we want to thank David for his outstanding leadership of the IPDLN over the last two years. He and his team put on an excellent conference in Swansea, with record breaking attendance, excellent presentations, thought provoking plenaries and wonderful facilities and social events that made the conference a huge success. Even the weather cooperated, as the sun shone most of the time (well done David!). In addition, membership of the IPDLN has grown substantially in the last two years, both in number of members and number of different countries represented. David played a key role in the launch of a new journal for our network, the International Journal of Population Data Science (IJPDS), with an editorial board comprised of several IPDLN members, and with Associate Professor Kerina Jones (Swansea University) as founding editor-in-chief.
The IPDLN remains a young organization, having had its inaugural conference only in 2008, and we have come a long way in that time. Each subsequent biennial conference has grown in size, sophistication and quality of content, and our membership has steadily increased. In addition, new collaborations between IPDLN researchers and member organizations are continuing to develop. External trends, such as widespread interest in the possibilities of "Big Data" make the work and expertise of IPDLN members more relevant than ever. Common challenges across our countries, such as the perpetual concerns around quality and sustainability of our health and social care systems, make the IPDLN's ability to foster cross-jurisdiction research and evidence more important than ever.
We are committed to building on David's work and that of the directors before him to further the aims of the IPDLN. As a first step, we have established an interim executive committee, consisting of the current IPDLN co-directors and leaders of the organizations that have previously led the network (James Semmens, Curtin University, Kim McGrail, University of British Columbia, David Ford, Swansea University). Its purpose is to provide strategic advice on the overall direction and deliverables of the IPDLN. The interim executive committee will serve until the next conference in 2018, at which time a new director and a new executive committee will be elected by the membership.
One key deliverable will be another outstanding IPDLN conference, and we are pleased to announce it will take place in Banff, Alberta, from September 12-14, 2018. Please mark your calendars now and plan to attend. Dr Hude Quan and Dr Astrid Guttmann have agreed to lead the Scientific Programme Committee, and we will be providing more information on opportunities to participate in the work of that committee in due course. In addition, we aim to continue to increase IPDLN membership in terms of number and geography, especially among countries that are not (or only modestly) represented. We will also help IPDLN member institutions to create more opportunities for collaboration, cross-jurisdictional studies, and shared tools and learning.
The scientific focus of our young network is evolving, reflected in the recent decision to substitute "population data" for "health data" in the network's name. This was welcome in that it reflected the fact that many of our members study more than health data or health outcomes, but it might make it harder to describe the mission of the network. Similarly, how the IPDLN can better contribute to shaping a conversation around our collective mission, advance science between conferences, and ensure that the network and its members are collectively seen as leaders internationally, are questions being explored and will inform the network development plan.
The IPDLN is well-positioned to shape the global scientific agenda in emerging areas such as 'population data science' and/or 'Big Data'. Such terms, describing domains of scientific inquiry, mean different things to different people. Our network and its broad and interdisciplinary international membership can help to define what these areas are, by identifying high priority population data science questions and opportunities for ambitious collaborative efforts on a global scale.
These are exciting times for the IPDLN and its members, as in this digital health information age the potential for our network is limitless. In our early days as co-directors, we welcome your input in response to these ideas on the role of the IPDLN (please email us with your ideas and thoughts). We are honoured to have the opportunity to co-lead the IPDLN for the next two years, and recognize that our efforts will be made easier because we are building on the existing strengths of the network and its members.Please email us your ideas and thoughts on the role of IPDLN to:Michael Schull at Michael.Schull@ices.on.caWilliam Ghali at wghali@ucalgary.ca

We write to you, here in the pages of the International Journal of Population Data Science, for the second time in our capacity of co-directors of the International Population Data Linkage Network (IPDLN – www.ipdln.org). Time has certainly passed quickly since our first communication, where we introduced ourselves, and discussed planned initiatives for our tenure as leads of the IPDLN. Our network's scientific community is steadily growing and thriving in an era of heightened interest around all things 'data'. Indeed, there is great enthusiasm for all initiatives that explore ways of harnessing information systems and multisource data to enhance collective knowledge of health matters so that better decisions can be made by governments, system planners, providers, and patients. Never before have such initiatives attracted more attention.
It is in this context of heightened interest and relevance around IPDLN and its science that we prepare to convene in Banff, Alberta, Canada for the 5th biennial IPDLN Conference – September 11-14. The conference, to be held at the inspiring Banff Centre (www.banffcentre.ca), is almost sold out, with only limited space remaining for late registrants. A tremendous program has been created through the oversight of Scientific Program co-chairs, Drs. Astrid Guttman and Hude Quan. A compelling roster of plenary lectures from Drs. Diane Watson, Jennifer Walker, and Osmar Zaïane is eagerly anticipated, as are topical panel discussions, an entertaining Science Slam session, and a terrific social program. These sessions will be surrounded by rich scientific oral and poster presentations arising from the more than 450 scientific abstracts submitted for review. We are so pleased to see this vibrant scientific engagement from the IPDLN membership and students, and look forward to hosting all delegates in Banff.
The Banff conference will also be the venue at which we announce the new Directorship of the IPDLN for the next two years (2019 and 2020). As co-directors, we engaged with a number of individuals and organizations with interest in leading the IPDLN. In the end, two compelling Directorship applications were submitted – one a joint bid from Australia's Population Health Research Network and the South Australia Northern Territory DataLink, and the other from the US-based Actionable Intelligence for Social Policy. IPDLN members submitted votes on these strong leadership bids through an online voting process, and while the excellence and appeal of both bids was apparent in strong voter support for both, a winning bid has been confirmed, and it will (as mentioned) be announced at the upcoming September conference.
As we look forward to the Banff meeting with great anticipation, we are compelled to acknowledge the growing IPDLN legacy created by past directors. We are particularly indebted to our immediate predecessor, Dr. David Ford, and his team at Swansea University. Their work in hosting the 2016 IPDLN conference has been an inspiration to us in the planning of this year's conference, and their crucial and foundational work in creating an IT platform for the IPDLN website, the membership database, and the new International Journal for Population Data Science has brought the IPDLN to a new level of organizational sophistication. Over the last 18 months, our co-directorship teams from the Institute for Clinical Evaluative Sciences in Ontario and the O'Brien Institute for Public Health at the University of Calgary have built on the foundation established by prior directors to update/enhance the IPDLN website and membership database. The IPDLN has more members than ever before representing a greater number of countries, and we have a more formalized governance structure with the creation of an Executive Committee that will include immediate past-Directors in order to better ensure continuity. A new Executive Committee will be elected by the IPDLN membership following the Banff conference.
The waiting is almost over and IPDLN 2018 is upon us! Our scientific domain has never had the prominence or level of anticipation that we currently see. And the IPDLN has grown in its size, vibrancy and scientific scope. The opportunities for us are boundless, and the timing of our upcoming conference could not be better. We are honoured, with our respective organizations, to have had this opportunity to serve as co-directors over the past two years, and look forward to seeing many of you very soon. For those of you who are unable to travel to Canada's Rocky Mountains this year, we look forward to connecting with you at a later time in the IPDLN's continuing upward journey.

ABSTRACTObjectivesHigh profile initiatives and reports highlight the potential benefits that could be realized by increasing access to health data, but do members of the general public share this view? The objective was to gain insight into the general public's attitudes toward users and uses of administrative health data.
ApproachIn fall 2015, four professionally-moderated focus groups with a total of 31 Ontario participants were conducted; two in Thunder Bay, two in Toronto. Participants were asked to review and comment on: general information about research based on linked administrative health data, a case study and models through which various users might use administrative health data.
ResultsSupport for research based on linked administrative health data was strongest when people agreed with the purposes for which studies were conducted. The main concerns related to the security of personal data generally (e.g., Canada Revenue Agency hacking incidents were noted) and potentially inappropriate uses of health data, particularly by the private sector (e.g., strong reservations about studies done solely or primarily with a profit motive). Participants were reassured when provided with information about the process for removing or coding identifying information from health data, and about the oversight provided by the Information and Privacy Commissioner of Ontario. However, even when fully informed of privacy and security safeguards, participants still felt that risks unavoidably increase when there are more people and organizations accessing data.
ConclusionsMembers of general public were generally supportive of research based on linked administrative health data but with conditions, particularly when the possibility of private sector research was discussed. Notably, and citing security concerns, focus group participants preferred models that had a limited number of individuals or organizations accessing data.

ObjectivesCOVID-19 accentuated the importance of breaking down data siloes and aligning incentives for data access, collection, and use. Health Data Research Network Canada (HDRN Canada) is responding to this challenge, bringing together people and organizations to transform health data use in Canada.
ApproachHDRN Canada's foundation is its partnership of 20 pan-Canadian, provincial and territorial data organizations that together are enabling multi-regional research. This is being enriched with HDRN Canada's development of the Canada Health Data Research Alliance (HDR Alliance). The HDR Alliance coordinates expansion of sources and types of data available while retaining organizational independence. A project-based pilot approach is underway with two large pan-Canadian, longitudinal, consented cohort studies being linked at HDRN Canada sites. In addition, a collaboration with a pan-Canadian COVID19 clinical trials network is ensuring that clinical data are collected in ways that enables linkage with population-based administrative data.
ResultsHDRN Canada has created a single data access portal for researchers with information on over 500 datasets and supported 72 research projects to date. Work on the HDR Alliance adds data from the Canadian Partnership for Tomorrow's Health and the Canadian Longitudinal Survey on Aging. The former includes 350,000 individuals, and survey data (including related to COVID-19), physical measures and genomics. The latter includes 50,000 individuals with survey data and physical measures. Four multi-region clinical trials are being planned with the support of HDRN Canada. Even with aligned incentives, challenges navigating data governance and access processes remain. Collaborations are necessary to address these complexities and enable access to richer data in an efficient and timely matter.
ConclusionStrong partnerships are critical to unlocking the potential of Canada's data assets and expertise. The HDR Alliance provides a collaboration mechanism to increase the "findability", accessibility and utility of data assets, while addressing complex issues in the data landscape. This increases research opportunities and the impact of population-based, linkable data.

ABSTRACT
ObjectiveCanada's large single payer health systems have created provincial centres with rich, population-wide health and social data holdings that are linkable at the person level. Complementary federal data include a subset of standardized and enriched administrative healthcare data at the Canadian Institute for Health Information, Statistics Canada's extensive array of survey- and census-based social and geography-based information, and large national datasets that are being created through pan-Canadian initiatives. Unfortunately, these data assets are rarely combined in multi-province or pan-Canadian studies, often because data are not directly comparable from one province to another, or cannot be shared due to legislative or other barriers. There is now growing interest in enabling multi-province studies — even when data are not directly comparable — and in sharing experiences to make more effective use of linked or linkable administrative data across Canada.
ApproachNine provincial and national organizations have created a detailed Implementation Plan for the new PRHDN distributed data network. Without requiring that record-level data leave provincial boundaries, the PRHDN will create shared core research data infrastructure: (i) validated algorithms that implement case definitions applicable across provinces, (ii) harmonized common data and (iii) common analytic protocols. The PRHDN will also establish complementary infrastructure including dedicated personnel to assist researchers and decision makers, joined-up training and capacity building sessions, opportunities to share learning and experience related to linking new datasets such as electronic medical records and omic datasets, and forums for knowledge translation and exchange with decision makers.
ResultsThe PRHDN is already bringing together expertise from across Canada as researchers, decision makers and data custodians begin to identify opportunities for enhanced use of health data in Canadian research, policy making and practice. A simple PRHDN website has been created (https://www.prhdn.ca/) and more than 200 researchers and policy/decision makers have become members of the PRHDN consortium. Surveys of consortium members are identifying priorities for the first algorithm validation work (to-date the top four priorities are mental health, cardiovascular disease, diabetes and respiratory disease) and the PRHDN Leads Team is functioning as a decision-making body, e.g., in discussions with Statistics Canada.
ConclusionsWorking together, provincial and national organizations across Canada have identified concrete steps that can be taken to enable multi-province and pan-Canadian studies based on administrative data within one year of the start of funding. The PRHDN Leads Team is currently discussing the PRHDN vision and Implementation Plan with potential funders.

Population data science [1] researchers are not alone in recognizing the value of health and health-related data. In the era of big data, and with advent of machine learning and other artificial intelligence methods, organizations around the world are actively working to turn data into knowledge, and, in some cases, profit. The media and members of the public have taken notice, with high profile news stories about data breaches and privacy concerns [2-4] alongside some stories that call for increased use of data [5,6]. In response, public and private sector data-holding organizations and jurisdictions are turning their attention to policies, processes and regulations intended to ensure that personal data are used in ways that that the public supports. In some cases, these efforts include involving "publics" in decisions about data, such as using patient and lay person advice and other inputs to help shape policies [7-10].

IntroductionThe Applied Health Research Question (AHRQ) portfolio is an initiative funded by the Ontario Ministry of Health and Long-Term Care, leveraging the linked data and scientific expertise at ICES to answer questions that directly impact healthcare policy, planning or practice.
Objectives and ApproachThe objective of this project was to evaluate historical patterns of emergency department (ED) use to better plan for a new emergency Department in Kingston and to better understand the factors contributing to increasing ED utilization.
Emergency departments across Ontario continue to see consistent increases in volume at rates exceeding expected volume growth due to population growth alone. Some hospitals across the province observe significantly higher volume increases compared to the provincial average.
ResultsFrom 2006/07 to 2016/17, rate and volume of emergency department visits in Ontario increased 8.82% and 19.87% respectively. Throughout the same period, emergency department visit rate and volume at Kingston General Hospital increased 20.70%, and 27.2%. Using historical data and projected population growth by age and sex, we were able to estimate that emergency department volume would increase at least 11.94% by 2025 due to estimated shifts in population size and distribution (by age and sex) alone. From 2006/07 to 2016/17, the greatest rate of increase in reason for ED visits was mental/behavioral problems. Throughout this period the increase in volume and rate of ED visits due to mental/behavioural problems was 274.46% and 259.59% respectively.
Conclusion/ImplicationsPopulation-specific volume projections and historical trends in ED use can be utilized for planning ED operations to improve efficiency and patient care quality. This has been used to inform the redesign of the ED at the Kingston Health Sciences Centre to ensure it will meet the needs of the community.

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.

IntroductionIntegrating health and social services data is critical to understanding social determinants of health and responding to public expectations for evidence-based policies amidst changing demographics and fiscal constraint.
While academia has long understood the importance of social determinants of health, real and perceived obstacles have slowed their evaluation in Ontario.
Objectives and ApproachThis report describes how the Institute for Clinical Evaluative Sciences (ICES) and the Ministry and Community and Social Services (MCSS) have partnered to bring social services data and health data together to better understand the Ontario population and better support decision makers across various sectors.
We present how ICES and MCSS tackled barriers to data access and cultural challenges to data sharing in the Ontario context, provide an overview of their unique data and research partnership - including the new collaboration research and data access platforms created, highlight research findings to date, and identify key topics of interest moving forward.
ResultsOver the last decade, ICES and MCSS have led the way in Ontario linking health administrative and social services data. An initial single year linkage enabled the success of the Health Care Access Research and Developmental Disabilities project. This cross-sectoral initiative provided a clearer sense of how people with developmental disabilities experienced health care in Ontario.
Building on this work, ICES and MCSS recently expanded their partnership bringing together 15 years of social services and health data through a broader data sharing agreement. This agreement allows greater data access to researchers. In addition, ICES and MCSS have been successful in creating a new integrated research platform that will increase the depth and quality of health and social services research and policy evaluation in Ontario.
Conclusion/ImplicationsA broader collaborative research community will now be able to answer questions of interest, do self-directed integrated data analytics and leverage respective program data expertise to tackle joint research projects. Importantly, MCSS analytics teams will now also have access to linked data on this platform to conduct their own research.

ABSTRACT
IntroductionThere is little argument that integrated data can provide a valuable resource for improved health system management, planning, and accountability as well as discovery and commercial use, but policies to enable and support integrated data fall short of the potential represented by integrated data. To understand the current level of progress on policy for integrated data, we looked at two successful and two unsuccessful efforts to support the creation and use of integrated data in health systems.
Methods/ApproachWe used document and literature analysis to develop descriptions of the Icelandic Health Sector Database Act, the creation of the Institute for Clinical Evaluative Sciences in Ontario (Canada), the care.data initiative in the United Kingdom, and the Health Datapalooza initiative in the US and used an Ideas, Institutions and Actors framework to compare the experience with integrated data policy and politics.
Results and discussionOur analysis suggests that institutions around integrated data remain under-developed and largely focused on specific aspects of integrated data policy or use. There are at least two sets of dominant ideas around integrated data – data as a tool for economic development and health system performance and data as a threat to privacy and liberty – that are often diametrically opposed in different jurisdictions. To a great extent, powerful actors remain disengaged from integrated data discussions and leadership engaged in integrated data policy and politics remains isolated from larger policy and political discussions. The medical profession along with civil society groups can mount effective opposition to integrated data initiatives, although potentially for different reasons (accountability and privacy concerns respectively).
ConclusionsOur analysis suggests several key issues around successful integrated data policy and politics that support the importance of strong leadership, an incremental approach to institution building that focuses on public benefits, strongly alignment to missions that are congruent with societal values, and stronger attention to effective and rapid implementation of policy. In addition to the cases studied here, the success of smaller sub-national (e.g. state or provincial) efforts suggests that smaller efforts tend to work better although their success may not receive the attention that could support larger efforts to integrate data on the national level. Further work should focus chiefly on the extension of these arguments to non-health sectors to realize the full value of integrated data.

Many countries around the world are creating COVID-19 trial datasets and databases of COVID-19-related data such as test results that cover entire populations. It is our strong recommendation, and sincere hope, that these data assets will be brought together through record linkage so that their scientific value and impact for society can be amplified. We call on trialists, data stewards and research funders to work together so that prospective linkage of trial data to medical databases becomes the norm, starting with COVID-19 trials.

IntroductionIn Ontario, the top 5% of high-cost users account for 66% of health care costs. The heavy use of resources combined with perceived inefficiencies offer an imperative to target strategies to redesign care to better meet patient needs and increase value.
Objectives and ApproachAs part of a request submitted to the Applied Health Research Question (AHRQ) review team, the main objective of this study was to identify drivers of high health care use in Ontario in order to find better ways to improve the efficiency in healthcare delivery. Using data in fiscal year 2012/13, characteristics of the top 5% of high costs users were described, and further stratified by mental health status. Total spending by sector of care were also described. Data were linked including physician, hospital, medication and long term care databases for each patient.
ResultsIn the top 5% of high-cost users, there were 729,870 patients who accounted for $20,179,208,348 of total healthcare spending in 2012/13, with the highest percentage of spending observed among older adults aged 61-80 years old. Mental health high-cost patients accounted for 6.1% of these patients, of which 51.5% were female, had a low socio-economic status and an average age of 44 years. These patients had an average of 4.9 (SD=2.3) ICD chapters and used an average of 8.7 (SD=3.8) drugs. Using the health accounts methodology (ICHA), as described by the OECD and WHO, over 90% of healthcare costs among the top 5% of high-cost patients were from inpatient care, day surgery and clinic care, physician care, outpatients drugs and inpatient rehabilitation and complex/continuing care.
Conclusion/ImplicationsThis study provides a systematic description of the needs in a high cost patient group, and serves as a platform for international comparisons across healthcare systems to better understand gaps and identify targets for intervention. These cross-comparisons offer a tool to evaluate performance of healthcare systems and to prioritize policies.

This article explores the approach that ICES (formerly the Institute for Clinical Evaluative Sciences)uses to encourage public engagement at both the research study and corporate level. ICES is anindependent not-for-profit research institute in the province of Ontario, Canada. This article wasco-written by ICES' public engagement team and four members of the ICES Public AdvisoryCouncil (PAC). As part of the process of writing this article PAC members provided theirreflections on why they got involved, what worked well and the limitations and challenges of ICES'approach.
ICES described the development of its public engagement strategy to inform how the institutionwould capture and incorporate the values of Ontarians in ICES activities and research. ICES provideddetails on two key elements of its strategy: the formation of a PAC to advise its leadership, andthe creation of resources and supports to encourage researchers to incorporate public engagementin their projects.
PAC members and ICES provided perspectives on what impact they perceive as a result ofthe public engagement strategy. PAC members expressed that ICES has demonstrated listening toand using their input, but it is too early to evaluate if their feedback has changed the way ICESconducts its work. ICES discussed the challenges and successes in building and implementing thepublic engagement strategy, including recruiting a diverse council, aligning with public prioritiesand creating a culture of engagement. As a result of public input, ICES has restructured theway the institution explains its privacy and cybersecurity approach to build trust and confidence.ICES has also seen an increase in researchers using public engagement resources, and early datasuggests that in 2019 about 20% of scientists included some form of public engagement in theirprojects.
ICES' journey to public engagement resulted in important changes to processes and activitiesat the institution, but there is much more that needs to be done. PAC members advocate thatpublic members should be engaged in health data research and hope that public input will bea core element in health data research in the future. ICES will continue its efforts to addresspublic priorities and will seek to further evaluate the impact of public engagement across theorganisation.

IntroductionCanadian provincial health systems have a data advantage – longitudinal population-wide data for publicly funded health services, in many cases going back 20 years or more. With the addition of high performance computing (HPC), these data can serve as the foundation for leading-edge research using machine learning and artificial intelligence.
Objectives and ApproachThe Institute for Clinical Evaluative Sciences (ICES) and HPC4Health are creating the Ontario Data Safe Haven (ODSH) – a secure HPC cloud located within the HPC4Health physical environment at the Hospital for Sick Children in Toronto. The ODSH will allow research teams to post, access and analyze individual datasets over which they have authority, and enable linkage to Ontario administrative and other data. To start, the ODSH is focused on creating a private cloud meeting ICES' legislated privacy and security requirements to support HPC-intensive analyses of ICES data. The first ODSH projects are partnerships between ICES scientists and machine learning.
ResultsAs of March 2018, the technological build of the ODSH was tested and completed and the privacy and security policy framework and documentation were completed. We will present the structure of the ODSH, including the architectural choices made when designing the environment, and planned functionality in the future. We will describe the experience to-date for the very first analysis done using the ODSH: the automatic mining of clinical terminology in primary care electronic medical records using deep neural networks. We will also present the plans for a high-cost user Risk Dashboard program of research, co-designed by ICES scientists and health faculty from the Vector Institute for artificial intelligence, that will make use of the ODSH beginning May 2018.
Conclusion/ImplicationsThrough a partnership of ICES, HPC4Health and the Vector Institute, a secure private cloud ODSH has been created as is starting to be used in leading edge machine learning research studies that make use of Ontario's population-wide data assets.

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.