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Multi-province epidemiological research using linked administrative data: a case study from Canada.

ABSTRACT: Background:Canada has a publicly-funded universal healthcare system with information systems managed by 13 different provinces and territories. This context creates inconsistencies in data collection and challenges for research or surveillance conducted at the national or multi-jurisdictional level. Objective:Using a recent Canadian research project as a case study, we document the strengths and challenges of using administrative health data in a multi-jurisdictional context. We discuss the implications of using different health information systems and the solutions we adopted to deal with variations. Our goal is to contribute to better understanding of these challenges and the development of a more integrated and harmonized approach to conducting multi-jurisdictional research using administrative data. Context and model:Using data from five separate provincial healthcare data systems, we sought to create and report on a set of provincially-comparable mental health and addiction services performance indicators. In this paper, we document the research process, challenges, and solutions. Finally, we conclude by making recommendations for investment in national infrastructure that could help cut costs, broaden scope, and increase use of administrative health data that exists in Canada. Conclusions:Canada has an incredible wealth of administrative data that resides in 13 territorial and provincial government systems. Navigating access and improving comparability across these systems has been an ongoing challenge for the past 20 years, but progress is being made. We believe that with some investment, a more harmonized and integrated information network could be developed that supports a broad range of surveillance and research activities with strong policy and program implications.

SUBMITTER: Butler AL

PROVIDER: S-EPMC7299461 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

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Multi-province epidemiological research using linked administrative data: a case study from Canada.

Butler Amanda Leanne AL Smith Mark M Jones Wayne W Adair Carol E CE Vigod Simone N SN Lesage Alain A Kurdyak Paul P

International journal of population data science 20180921 3

<h4>Background</h4>Canada has a publicly-funded universal healthcare system with information systems managed by 13 different provinces and territories. This context creates inconsistencies in data collection and challenges for research or surveillance conducted at the national or multi-jurisdictional level.<h4>Objective</h4>Using a recent Canadian research project as a case study, we document the strengths and challenges of using administrative health data in a multi-jurisdictional context. We d ...[more]

PMID: 32935019

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Project description:BACKGROUND: National screening programs have reduced cervical cancer mortality; however participation in these programs varies according to women's personal and social characteristics. Research into these inequalities has been limited by reliance on self-reported service use data that is potentially biased, or administrative data that lacks personal detail. We address these limitations and extend existing research by examining rates and correlates of cervical screening in a large epidemiological survey with linked administrative data. METHODS: The cross-sectional sample included 1685 women aged 44-48 and 64-68 years from the Australian Capital Territory and Queanbeyan, Australia. Relative risk was assessed by logistic regression models and summary Population Attributable Risk (PAR) was used to quantify the effect of inequalities on rates of cervical cancer screening. RESULTS: Overall, 60.5% of women participated in screening over the two-year period recommended by Australian guidelines. Screening participation was associated with having children, moderate or high use of health services, employment, reported lifetime history of drug use, and better physical functioning. Conversely, rates of cervical screening were lower amongst women who were older, reliant on welfare, obese, current smokers, reported childhood sexual abuse, and those with anxiety symptoms. A summary PAR showed that effective targeting of women with readily observable risk-factors (no children, no partner, receiving income support payments, not working, obese, current smoker, anxiety, poor physical health, and low overall health service use) could potentially reduce overall non-participation in screening by 74%. CONCLUSIONS: This study illustrates a valuable method for investigating the personal determinants of health service use by combining representative survey data with linked administrative records. Reliable knowledge about the characteristics that predict uptake of cervical cancer screening services will inform targeted health promotion efforts.

Project description:IntroductionIn Canada, most provinces have established administrative health data repositories to facilitate access to these data for research. Anecdotally, researchers have described delays and substantial inter-provincial variations in the timeliness of data access approvals and receipt of data. Currently, the reasons for these delays and variations in timeliness are not well understood. This paper provides a study protocol for (1) identifying the factors affecting access to administrative health data for research within select Canadian provinces, and (2) comparing factors across provinces to assess whether and how they contribute to inter-provincial variations in access to administrative health data for research.MethodsA qualitative, multiple-case study research design will be used. Three cases will be included, representing three different provinces. For each case, data will be collected from documents and interviews. Specifically, interviews will be carried out with (1) research stakeholders, and (2) regulatory stakeholders (10 individuals/group * 2 groups/province * 3 provinces = 60). During within-case analysis, interview data for each stakeholder group will be analyzed separately using constant comparative analysis. Document analysis will occur iteratively, and will inform interview guide adaptation, and supplement interview data. Cross-case analysis will involve systematic comparison of findings across cases.DiscussionThis study represents the first in-depth examination of access to administrative health data in Canada. The main outcome will be an overarching mid-range theory explaining inter-provincial variations in access to administrative health data in Canada. This theory will be strengthened by the inclusion of the perspectives of both researchers and those involved in the regulation of data access. The findings from this study may be used to improve equitable and timely access to administrative health data across provinces, and may be transferable to other jurisdictions where barriers to access to administrative health data have been reported.

Project description:IntroductionSuicide has a complex aetiology and is a result of the interaction among the risk and protective factors at the individual, healthcare system and population levels. Therefore, policy and decision makers and mental health service planners can play an important role in suicide prevention. Although a number of suicide risk predictive tools have been developed, these tools were designed to be used by clinicians for assessing individual risk of suicide. There have been no risk predictive models to be used by policy and decision makers for predicting population risk of suicide at the national, provincial and regional levels. This paper aimed to describe the rationale and methodology for developing risk predictive models for population risk of suicide.Methods and analysisA case-control study design will be used to develop sex-specific risk predictive models for population risk of suicide, using statistical regression and machine learning techniques. Routinely collected health administrative data in Quebec, Canada, and community-level social deprivation and marginalisation data will be used. The developed models will be transformed into the models that can be readily used by policy and decision makers. Two rounds of qualitative interviews with end-users and other stakeholders were proposed to understand their views about the developed models and potential systematic, social and ethical issues for implementation; the first round of qualitative interviews has been completed. We included 9440 suicide cases (7234 males and 2206 females) and 661 780 controls for model development. Three hundred and forty-seven variables at individual, healthcare system and community levels have been identified and will be included in least absolute shrinkage and selection operator regression for feature selection.Ethics and disseminationThis study is approved by the Health Research Ethnics Committee of Dalhousie University, Canada. This study takes an integrated knowledge translation approach, involving knowledge users from the beginning of the process.

Project description:BACKGROUND:The burden of multimorbidity is a growing clinical and health system problem that is known to be associated with socioeconomic status, yet our understanding of the underlying determinants of inequalities in multimorbidity and longitudinal trends in measured disparities remains limited. METHODS:We included all adult respondents from four cycles of the Canadian Community Health Survey (CCHS) (between 2005 to 2011/12), linked at the individual-level to health administrative data in Ontario, Canada (pooled n?=?113,627). Multimorbidity was defined at each survey response as having ?2 (of 17) high impact chronic conditions, based on claims data. Using a decomposition method of the Erreygers-corrected concentration index (CErreygers), we measured household income inequality and the contribution of the key determinants of multimorbidity (including socio-demographic, socio-economic, lifestyle and health system factors) to these disparities. Differences over time are described. We tested for statistically significant changes to measured inequality using the slope index (SII) and relative index of inequality (RII) with a 2-way interaction on pooled data. RESULTS:Multimorbidity prevalence in 2011/12 was 33.5% and the CErreygers was -?0.085 (CI: -0.108 to -?0.062), indicating a greater prevalence among lower income groups. In decomposition analyses, income itself accounted more than two-thirds (69%) of this inequality. Age (21.7%), marital status (15.2%) and physical inactivity (10.9%) followed, and the contribution of these factors increased from baseline (2005 CCHS survey) with the exception of age. Other lifestyle factors, including heavy smoking and obesity, had minimal contribution to measured inequality (1.8 and 0.4% respectively). Tests for trends (SII/RII) across pooled survey data were not statistically significant (p?=?0.443 and 0.405, respectively), indicating no change in inequalities in multimorbidity prevalence over the study period. CONCLUSIONS:A pro-rich income gap in multimorbidity has persisted in Ontario from 2005 to 2011/12. These empirical findings suggest that to advance equality in multimorbidity prevalence, policymakers should target chronic disease prevention and control strategies focused on older adults, non-married persons and those that are physically inactive, in addition to addressing income disparities directly.

Project description:BackgroundAboriginal people are under-reported on administrative health data in Australia. Various approaches have been used or proposed to improve reporting of Aboriginal people using linked records. This cross-sectional study used self-reported Aboriginality from the NSW Patient Survey Program (PSP) as a reference standard to assess the accuracy of reporting of Aboriginal people on NSW Admitted Patient (APDC) and Emergency Department Data Collections (EDDC), and compare the accuracy of selected approaches to enhance reporting Aboriginality using linked data.MethodsTen PSP surveys were linked to five administrative health data collections, including APDC, EDDC, perinatal, and birth and death registration records. Accuracy of reporting of Aboriginality was assessed using sensitivity, specificity, and positive and negative predictive values (PPVs and NPVs) and F score for the EDDC and APDC as baseline and four enhancement approaches using linked records: "Most recent linked record", "Ever reported as Aboriginal", and two approaches using a weight of evidence, "Enhanced Reporting of Aboriginality (ERA) algorithm" and "Multi-stage median (MSM)".ResultsThere was substantial under-reporting of Aboriginality on APDC and EDDC records (sensitivities 84 and 77% respectively) with PPVs of 95% on both data collections. Overall, specificities and NPVs were above 98%. Of people who were reported as Aboriginal on the PSP, 16% were not reported as Aboriginal on any of their linked records. Record linkage approaches generally increased sensitivity, accompanied by decrease in PPV with little change in overall F score for the APDC and an increase in F score for the EDDC. The "ERA algorithm" and "MSM" approaches provided the best overall accuracy.ConclusionsWeight of evidence approaches are preferred when record linkage is used to improve reporting of Aboriginality on administrative health data collections. However, as a substantial number of Aboriginal people are not reported as Aboriginal on any of their linked records, improvements in reporting are incomplete and should be taken into account when interpreting results of any analyses. Enhancement of reporting of Aboriginality using record linkage should not replace efforts to improve recording of Aboriginal people at the point of data collection and addressing barriers to self-identification for Aboriginal people.

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Multi-province epidemiological research using linked administrative data: a case study from Canada.

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Multi-province epidemiological research using linked administrative data: a case study from Canada.

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