Suchergebnisse

IntroductionCurrent cost estimates for dementia in Canada are lacking and no studies have yet to examine the incremental healthcare costs associated with both dementia and frailty, despite evidence of increasing prevalence of both conditions and their bidirectional association. These data are essential for informed clinical and public policy programs.
Objectives and ApproachUsing linked clinical and health administrative databases in Ontario, we conducted a cohort study of all long-stay home care clients aged 50+ years with a clinical assessment between April 2014 and March 2015 (n=160,209). We defined dementia using a validated algorithm, and frailty categories (robust, pre-frail, frail) using a modified frailty index from clinical assessment data. Clients were followed prospectively for 1-year, for which we obtained total- and sector-specific healthcare costs for all encounters. We calculated cost differences (in $2015CAD) between dementia-frailty groups using a survival- and covariate-adjusted cost estimator described by Manning and Basu (2010) that included dementia-frailty interactions.
ResultsIn this population-based cohort of long-stay home care recipients, the prevalence of dementia was 26.8% and 33.3% of these clients were frail (vs. 26.9% among clients without dementia). Approximately 15% of the cohort died over the 1-year follow-up. The average 1-year estimated total health system cost was $26,965. On average, home care clients with dementia categorized as frail incurred $14,291 (SE=$139) more in charges than similar robust clients ($35,381 vs. $21,091, respectively). In contrast, frail persons without dementia incurred $12,796 (SE=$95) more in charges that similar robust clients ($33,659 vs. $20,864, respectively). Among frail persons, those with dementia incurred $1,722 (SE=$149) more in expenditures, on average. Wide variation in sector-specific costs were also observed by dementia and frailty strata.
Conclusion/ImplicationsDementia and frailty pose significant challenges to healthcare systems. Our findings illustrate large incremental costs associated with frailty, regardless of dementia status. Further research using the linked clinical assessment and administrative data is needed to inform variations in, and to delineate key drivers of, formal healthcare and informal care costs associated with dementia and frailty.

ABSTRACTObjectiveThere is limited evidence from randomized trials and observational studies to guide clinical practice regarding the use of statins in long-term care (LTC); the effectiveness of statins among those with limited life expectancy is not clear and there is concern that the risk of drug-related adverse events might outweigh any benefit. We examined the impact of initiating statin therapy on mortality for patients newly admitted to LTC.
ApproachPopulation-based health administrative data from Ontario, Canada were used to conduct a retrospective cohort study of newly admitted LTC residents, aged 66+ years and no statin use in the previous year, between January 1 2011 and December 31 2014. This cohort was linked to Resident Assessment Instrument (interRAI) data to capture clinical and functional characteristics (including frailty, activities of daily living, and cognitive function). The primary exposure was statin use within 30 days following LTC entry; residents who died or did not receive an interRAI assessment within 30 days were excluded. A propensity score for receiving statins was computed using resident demographic, clinical and functional characteristics. We matched exposed to unexposed patients on the basis of age (±1 year), sex, prior myocardial infarction(MI)/stroke hospitalization, frailty and propensity score (±0.2 standard deviations). Patients were followed in an intention-to-treat manner from the end of the exposure window until the earliest of death or March 31 2015. Cox regression was used to compare mortality between the study groups.
ResultsWe identified 39,560 newly admitted LTC residents aged 66+ years with no statin use in the previous year, of which 1,953 (4.9%) were prescribed a statin within 30 days of LTC entry. Propensity score matching resulted in 1,710 pairs of exposed and unexposed patients. In the matched cohort, those receiving statins had a lower rate of mortality compared with those not receiving statins (Hazard Ratio 0.77; 95% Confidence Interval [CI] 0.70-0.85). In pre-specified subgroup analyses, the association between statin use and reduced mortality persisted among those with and without a prior MI/stroke hospitalization and among those categorized as frail and not frail.
ConclusionOur data suggest initiating statins may be beneficial in reducing mortality risk among LTC residents, despite the complexity and advanced age of the patients. By linking rich resident-level health and functional assessment data with health administrative data we were able to characterize the association between demographic and clinical characteristics (including frailty) and exposure to statins more fully than with administrative data alone.

ABSTRACTObjectiveEfforts to enable persons with dementia to remain at home longer, and to reduce use of costly acute care resources, are at the forefront of policy agendas internationally. Foundational to planning appropriate health system supports is the ongoing, comparable and accurate estimation of the prevalence and incidence of dementia across regions, as well as associated patterns of health services use and cost. Our objective was to explore emerging approaches to using population data in dementia research and demonstrate the policy contribution of the resulting new knowledge.
ApproachUsing population-based health administrative data and an algorithm that was validated using electronic medical records, we developed a series of repeated, cross-sectional cohort studies to examine trends in dementia prevalence, incidence and publicly-funded health service use and costs between 2004/05 and 2013/14 among adults aged 65 years and older in Ontario, Canada. Trends in yearly rates of health service use were assessed using regression models for serially correlated data and compared to a 1:1 matched control group based on age, sex, geographic region and comorbidity level.
ResultsOver time, age- and sex-adjusted prevalence of dementia increased by 18.2% (from 63.0 to 74.5 per 1,000 persons; p-value < 0.001) and age- and sex-adjusted incidence decreased slightly (from 18.2 to 17.0 per 1,000 persons; p-value = 0.05). Community-dwelling persons with dementia were more likely than matched controls to be placed in long-term care (11.8% vs. 1.5% in 2013; p<0.001) and use home care (45.8% vs 23.2%; p<0.001) but equally likely to visit family physicians (93.9% vs. 94.8% in 2013) and specialists (87.1% vs. 89.4%). Median costs associated with one year of health system use were $19,468 (interquartile range (IQR) $4,490 to $47,726) for prevalent cases in 2012/13 and $16,549 (IQR $5,070 to $47,899) for incident cases. Long-term care and hospital care accounted for the largest portion of total costs in both groups.
ConclusionThe prevalence of dementia has increased in Ontario, Canada over time and, given slightly declining incidence rates, is likely attributable to improved survival. Surveillance of dementia with health administrative data is a cost-effective tool for describing and monitoring trends in incidence and prevalence over time, and for supporting health system capacity planning. This comparative information is critical to understanding the impact of policy decisions designed to address dementia-related health care needs at a population level.

IntroductionAutism Spectrum Disorder (ASD) is a neurodevelopmental disorder (NDD) that presents with a high degree of heterogeneity (e.g., co-occurrence of other NDDs and other co-morbid conditions), contributing to differential health system needs. Genetics are known to play an important role in ASD and may be associated with different disease trajectories.
Objectives and ApproachIn this proof of principle project, our objective is to link >2,200 children with a confirmed diagnosis of a NDD from the Province of Ontario Neurodevelopmental (POND) Study to administrative health data and electronic medical record (EMR) data in order to identify subgroups of ASD with unique health system trajectories. POND includes detailed phenotype and whole genome sequencing (WGS) data. Identified subgroups will be characterized based on clinical phenotype and genetics. To meet this goal, consideration of WGS-specific privacy and data issues is needed to implement processes which are above and beyond traditional requirements for analyzing individual-level administrative health data.
ResultsLinkage of WGS data with administrative health data is an emerging area of research. As such it has presented a number of initial challenges for our study of ASD. Privacy concerns surrounding the use of WGS data and rare-variant analysis are of particular importance. Practical issues required the need for analysts with expertise in administrative data, EMR data and genetic analyses, and specialized software and sufficient processing power to analyze WGS data. Transdisciplinary discussions of the scope and significance of research questions addressed through this linkage were crucial. The identification of genetic determinants of phenotypes and trajectories in ASD could support targeted early interventions; EMR linkage may inform algorithms to identify ASD in broader populations. These approaches could improve both patient outcome and family experience.
Conclusion/ImplicationsAs the cost of genetic sequencing decreases, WGS data will become part of the routine clinical management of patients. Linkage of WGS, EMR and administrative data has tremendous potential that has largely not been realized; including population-level ASD research to improve our ability to predict long-term outcomes associated with ASD.

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.

IntroductionCholinesterase inhibitors (ChEIs) are medications used to treat cognitive symptoms associated with Alzheimer's disease. Previous studies examining the determinants of continued use or withdrawal of ChEIs during the transition into a nursing home have lacked detailed clinical information needed to understand the range of factors associated with pharmacotherapeutic decision-making.
Objectives and ApproachPopulation-based clinical and administrative health databases were linked to examine patterns of ChEI use among 47,851 adults (aged 66+) with dementia newly admitted to nursing homes in Ontario between April 2011-March 2015. We examined whether resident frailty, among other factors, was associated with ChEI discontinuation in the following year. Frailty was calculated using a validated 72-item index derived from the Resident Assessment Instrument (RAI-MDS 2.0). Discontinuation was defined as a 30-day period when no dispensations occurred and no supply of ChEI was available. Subdistribution hazard models estimated the association between resident characteristics and discontinuation, accounting for competing risk of death.
ResultsOver one-third (36.7%) of residents were receiving a ChEI at admission and this proportion was lower among those defined as frail (33.6%) vs. non-frail (40.7%) at admission. Among those on a ChEI at admission, 82.3% continued use and 17.7% discontinued during the following year. After accounting for resident characteristics, ChEI type and previous use, the incidence of discontinuation was 15% higher in frail residents vs. non-frail residents (hazard ratio (HR)= 1.15, 95\% confidence interval (CI) [1.01,1.30]). Residents with severe aggressive behaviours (HR=1.82, 95% CI [1.60, 2.07]), and higher levels of cognitive impairment (HR=1.29, 95% CI [1.10, 1.51]) were more likely to discontinue. Residents aged 85+ (HR=0.69, 95% CI [0.61, 0.77]) and those who were widowed (HR=0.84, 95% CI [0.77, 0.91]) were less likely to discontinue.
Conclusion/ImplicationsMost residents who entered on a ChEI continued treatment during follow-up. The availability of linked clinical and administrative data allowed for a novel exploration of predictors of ChEI discontinuation. Frailty, severity of cognitive impairment and aggressive behaviours were associated with ChEI discontinuation; whereas selected sociodemographic factors predicted continued use.

IntroductionResearch data combined with administrative data provides a robust resource capable of answering unique research questions. However, in cases where personal health data are encrypted, due to ethics requirements or institutional restrictions, traditional methods of deterministic and probabilistic record linkages are not feasible. Instead, privacy-preserving record linkages must be used to protect patients' personal data during data linkage.
ObjectivesTo determine the feasibility and validity of a deterministic privacy preserving data linkage protocol using homomorphically encrypted data.
MethodsFeasibility was measured by the number of records that successfully matched via direct identifiers. Validity was measured by the number of records that matched with multiple indirect identifiers. The threshold for feasibility and validity were both set at 95%. The datasets shared a single, direct identifier (health card number) and multiple indirect identifiers (sex and date of birth). Direct identifiers were encrypted in both datasets and then transferred to a third-party server capable of linking the encrypted identifiers without decrypting individual records. Once linked, the study team used indirect identifiers to verify the accuracy of the linkage in the final dataset.
ResultsWith a combination of manual and automated data transfer in a sample of 8,128 individuals, the privacy-preserving data linkage took 36 days to match to a population sample of over 3.2 million records. 99.9% of the records were successfully matched with direct identifiers, and 99.8% successfully matched with multiple indirect identifiers. We deemed the linkage both feasible and valid.
ConclusionsAs combining administrative and research data becomes increasingly common, it is imperative to understand options for linking data when direct linkage is not feasible. The current linkage process ensured the privacy and security of patient data and improved data quality. While the initial implementations required significant computational and human resources, increased automation keeps the requirements within feasible bounds.

IntroductionHealth care systems have faced unprecedented challenges due to the COVID-19 pandemic. Access to timely population-based data has been vital to informing public health policy and practice.
MethodsWe describe how ICES, an independent not-for-profit research and analytic institute in Ontario, Canada, pivoted existing research infrastructure and engaged health system stakeholders to provide near real-time population-based data and analytics to support Ontario's COVID-19 pandemic response.
ResultsSince April 2020, ICES provided the Ontario COVID-19 Provincial Command Table and public health partners with regular and ad hoc reports on SARS-CoV-2 testing and COVID-19 vaccine coverage. These reports: 1) helped identify congregate care/shared living settings that needed testing and prevention efforts early in the pandemic; 2) provided early indications of inequities in testing and infection in marginalized neighbourhoods, including areas with higher proportions of immigrants and visible minorities; 3) identified areas with high test positivity, which helped Public Health Units target and evaluate prevention efforts; and 4) contributed to altering the province's COVID-19 vaccine roll-out strategy to target high-risk neighbourhoods and helping Public Health Units and community organizations plan local vaccination programs. In addition, ICES is a key component of the Ontario Health Data Platform, which provides scientists with data access to conduct COVID-19 research and analyses.
Discussion and ConclusionICES was well-positioned to provide rapid analyses for decision-makers to respond to the evolving public health emergency, and continues to contribute to Ontario's pandemic response by providing timely, relevant reports to health system stakeholders and facilitating data access for externally-funded COVID-19 research.