Suchergebnisse

Background with rationaleThe diversity of Canada's health systems and policies offers fertile ground for natural experiments, comparative analysis, and sharing of best practices. Investments over the last 25 years, measured in hundreds of millions of dollars, have created provincial centres with rich health and social data, national health surveys and more recently, clinical and other data. While much progress has been made within individual provinces and territories, challenges with comparability and timely access to data between jurisdictions remain.
Main AimOur aim is to develop a distributed network that facilitates and accelerates multi-jurisdictional research.
Methods/ApproachOur team includes data stewards, clinicians, decision-makers, patients, and researchers who are recognized as international leaders in data systems, access governance and engagement. The objectives for the Canadian Data Platform are to: create a data access support system that helps navigate multi-jurisdiction requests; to harmonize and validate definitions for important chronic diseases and other key variables to facilitate multi-jurisdictional research; to continue to expand the sources and types of data and linkages available; to develop the technology infrastructure required to improve the data access request process, data documentation, and re-use of algorithms; to create supports for advanced analytics and infrastructure for data collection and analysis; to establish strong partnerships with patients and the public and with Indigenous communities; and to build strong governance and enable national coordination.
ResultsOur Data Access Support Hub will open in the fall of 2019, at which time we will have an inventory of data available across our network, and the beginnings of a catalog of algorithms and harmonized data.
ConclusionBuilding cross-national resources to support multi-jurisdictional research can be challenging in places where there are multiple levels of governance of health and social services. Our network is one example of an approach to addressing these challenges.

Health expenditures in most OECD countries have increased at a slower rate since 2008/2009. Potential drivers of this bending of the cost curve include: (1) changes in pharmaceuticals and technology innovations; (2) healthcare reforms, and specifically those focusing on care for complex and high-user patients and (3) government expenditure controls resulting from general economic conditions. We use publicly available National Health Expenditure data from the Canadian Institute for Health Information to assess the merits of each of these drivers, with a focus on British Columbia. We find some evidence for the effects of changes in pharmaceuticals and technology, but the dominant effect is government spending controls, which are greatest for non-Medicare-covered services. These changes suggest potential unintended consequences on access and equity that should be understood before declaring victory for healthcare expenditure control.

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.

IntroductionNotwithstanding Canada's exceptional longitudinal health data and research centres with extensive experience transforming data into knowledge, many Canadian studies based on linked administrative data have focused on a single province or territory. Health Data Research Network Canada (HDRN Canada), a new not-for-profit corporation, will bring together major national, provincial and territorial health data stewards from across Canada. HDRN Canada's first initiative is the $81 million SPOR Canadian Data Platform funded under the Canadian Institutes of Health Research Strategy for Patient-Oriented Research (SPOR).
Objectives and ApproachHDRN Canada is a distributed network through which individual data-holding centres work together to (i) create a single portal and support system for researchers requesting multi-jurisdictional data, (ii) harmonize and validate case definitions and key analytic variables across jurisdictions, (iii) expand the sources and types of data linkages, (iv) develop technological infrastructure to improve data access and collection, (v) create supports for advanced analytics and (vi) establish strong partnerships with patients, the public and with Indigenous communities. We will share our experiences and gather international feedback on our network and its goals from symposium participants.
ResultsIn January 2020, HDRN Canada launched its Data Access Support Hub (DASH) which includes an inventory listing over 380 datasets, information about more than 120 algorithms and a repository of requirements and processes for accessing data. HDRN Canada is receiving requests for multi-province research studies that would be challenging to conduct without HDRN Canada.
Conclusion / ImplicationsThus far, HDRN Canada services and tools have been developed primarily for Canadian researchers but HDRN Canada can also serve as a prompt for an international discussion about what has/has not worked in terms of multi-jurisdictional research data infrastructure. It can also present an opportunity for the development of metadata, standards and common approaches that support more multi-country research.

AbstractThere are growing a number of children with an intellectual disability (ID). There is also evidence of poor health in the non‐disabled siblings of these children; indicating a possible need for policies and services to address a complex health issue. This article describes a narrative review of the literature regarding the mental and physical health of siblings of children who have an intellectual disability. The review examined 46 articles. Twenty‐one different factors were identified which may have an effect on the health of these siblings. Social determinants, individual variables, characteristics of the child with the disability, family characteristics, and support factors can all affect health. These variables are inter‐related and illustrate the need to account for complexity when studying the health of siblings of children who have an ID.

AbstractThere are a growing number of children with an ID/developmental disability. As well, there is evidence of poor health in the caregivers of these children. This article describes a narrative review of the literature regarding the mental and physical health of caregivers of children with ID/developmental disability. The review examined 162 papers. Twenty‐three different factors were identified that may have an effect on the health of these caregivers. Social determinants, individual caregiver variables, characteristics of the child with the disability, family characteristics, and support factors can all affect caregiver health. These variables are inter‐related and illustrate the need to account for complexity when studying the health of caregivers of children with ID/developmental disability.

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].

ABSTRACT
ObjectivesAntibiotic resistance is a significant public health issue, driven in large part by selection pressure induced by antibiotic use. Despite knowledge that a reduction in inappropriate antibiotic use is important, significant and sustained behaviour change has remained difficult to achieve. Previous studies have suggested that prescribing decisions vary with patient comorbidities and age, as well as the physician's age, claim volume, specialty, and continuity of care with the particular patient. Regional level variation has also been reported. The goal of this study is to explore variations in antibiotic prescribing for respiratory tract infections (RTIs) at the levels of patients, physicians, and regions.
ApproachWe used data on fee-for-service physician visits from the universal Medical Services Plan (MSP) for all residents of British Columbia, Canada from 2002 to 2012. We identified a cohort of patient visits for RTI (ICD-9 codes 460-466, 480, or 487). We derived measures of healthcare use and comorbidities at the patient level, and measures of physician claim volume and frequency of respiratory tract infection management, at the level of the physician. We used data on antibiotics filled by individuals, the number of all medications filled by individuals each year, and counts of prescriptions written by physicians (and filled) by month, from the provincial drug insurance database. We linked antibiotic prescriptions to physician visits by patient and prescriber as antibiotics dispensed within 5 days after the RTI visit. We calculated measures of regional population distributions. We used data on meteorological temperature readings assigned to each region, for each day, and calculated 28-day moving averages. We linked data on patient demographics, physician demographics, and hospitalizations to our dataset. Our analysis will use hierarchical generalized linear mixed models (GLMMs) with logit link to account for the clustering effects of patients among physicians and regions, to model the odds of an antibiotic prescription being dispensed. Measures of variation will be discussed.
ResultsBetween April 1, 2005 and March 31, 2012, there were over 10.5 million visits by nearly 3 million individuals, served by over 8000 physicians in 88 regions. Antibiotics were prescribed in 37% of all visits.
ConclusionThese are preliminary results, with full analytic results available in the coming months. These results will have implications for better understanding the extent of variations in antibiotic prescribing, and some of the drivers of these variations, as well as the potential to inform ongoing efforts to improve the appropriateness of antibiotic use.

Population Data BC (PopData) is an innovative leader in facilitating access to linked data for population health research. Researchers from academic institutions across Canada work with PopData to submit data access requests for projects involving linked administrative data, with or without their own researcher-collected data. PopData and its predecessor—the British Columbia Linked Health Database—have facilitated over 350 research projects analyzing a broad spectrum of population health issues. PopData embeds privacy in every aspect of its operations. This case study focuses on how implementing the Privacy by Design model protects privacy while supporting access to individual-level data for research in the public interest. It explores challenges presented by legislation, stewardship, and public perception and demonstrates how PopData achieves both operational efficiencies and due diligence.

Starting in June, 1997, the Workers' Compensation Board ofBC made available computerized records of all injured workers claims, from 1986 to 1996, to the UBC Centre for Health Services and Policy Research. These files gave information on each successful claim: short-term disability, long-term disability (pension), fatality, or health care only, as well as the fact and date of all unsuccessful or incomplete claims. Using "personal identifier fields" from these files, staff at the Centre managed to "link" 97.2% of these claims to the BC Linked Health Database. The BC Linked Health Data set (BCLHD), developed under contract with the BC Ministry of Health, makes 6 key transaction files in the province "linkable" to one another for the purposes of research. These currently include: the birth file, the death file, Medical Services Plan claims file, hospital discharge file, long-term care client file, and the Pharmacare A plan file (i. e. the provincial drug payment plan for those BC residents over 65 years of age). All records in each file, going back to fiscal year 1985/86, have been encrypted with a scrambled Personal Health Number (PHN) which matches the (scrambled) PHN of a unique individual in the Linkage Co-ordinating File of those enrolled in the Medical Services Plan of BC. ; Health Care and Epidemiology, Department of ; Medicine, Faculty of ; Population and Public Health (SPPH), School of ; Unreviewed ; Faculty ; Researcher

IntroductionResearch using linked data sets can lead to new insights and discoveries that positively impact society. However, the use of linked data raises concerns relating to illegitimate use, privacy, and security (e.g., identity theft, marginalization of some groups). It is increasingly recognized that the public needs to be consulted to develop data access systems that consider both the potential benefits and risks of research. Indeed, there are examples of data sharing projects being derailed because of backlash in the absence of adequate consultation. (e.g., care.data in the UK).
Objectives and methodsThis talk will describe the results of public deliberations held in Vancouver, British Columbia in April 2018 and the fall of 2019. The purpose of these events was to develop informed and civic-minded public advice regarding the use and the sharing of linked data for research in the context of rapidly evolving data availability and researcher aspirations.
ResultsIn the first deliberation, participants developed and voted on 19 policy-relevant statements. Taken together, these statements provide a broad view of public support and concerns regarding the use of linked data sets for research and offer guidance on measures that can be taken to improve the trustworthiness of policies and process around data sharing and use. The second deliberation will focus on the interplay between public and private sources of data, and role of individual and collective or community consent I the future.
ConclusionGenerally, participants were supportive of research using linked data because of the value such uses can provide to society. Participants expressed a desire to see the data access request process made more efficient to facilitate more research, as long as there are adequate protections in place around security and privacy of the data. These protections include both physical and process-related safeguards as well as a high degree of transparency.

IntroductionResearch using linked data sets can lead to new insights and discoveries that positively impact society. However, the use of linked data raises concerns relating to illegitimate use, privacy, and security (e.g., identity theft, marginalization of some groups). It is increasingly recognized that the public needs to be consulted to develop data access systems that consider both the potential benefits and risks of research. Indeed, there are examples of data sharing projects being derailed because of backlash in the absence of adequate consultation. (e.g., care.data in the UK).
Objectives and methodsThis paper describes the results of a public deliberation event held in April 2018 in Vancouver, British Columbia. The purpose of this event was to develop informed and civic-minded public advice regarding the use and the sharing of linked data for research with a focus on the processes and regulations employed to release data. The event brought together 23 members of the public over two weekends.
ResultsParticipants developed and voted on 19 policy-relevant statements. Voting results and the rationale behind any disagreements are reported here. Taken together, these statements provide a broad view of public support and concerns regarding the use of linked data sets for research and offer guidance on measures that can be taken to improve the trustworthiness of policies and process around data sharing and use.
ConclusionsGenerally, participants were supportive of research using linked data because of the value they provide to society. Participants expressed a desire to see the data access request process made more efficient to facilitate more research, as long as there are adequate protections in place around security and privacy of the 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.