Dataset Information

Regional variation of premature mortality in Ontario, Canada: a spatial analysis.

ABSTRACT:

Background

Premature mortality is a meaningful indicator of both population health and health system performance, which varies by geography in Ontario. We used the Local Health Integration Network (LHIN) sub-regions to conduct a spatial analysis of premature mortality, adjusting for key population-level demographic and behavioural characteristics.

Methods

We used linked vital statistics data to identify 163,920 adult premature deaths (deaths between ages 18 and 74) registered in Ontario between 2011 and 2015. We compared premature mortality rates, population demographics, and prevalence of health-relevant behaviours across 76 LHIN sub-regions. We used Bayesian hierarchical spatial models to quantify the contribution of these population characteristics to geographic disparities in premature mortality.

Results

LHIN sub-region premature mortality rates ranged from 1.7 to 6.6 deaths per 1000 per year in males and 1.2 to 4.8 deaths per 1000 per year in females. Regions with higher premature mortality had fewer immigrants and higher prevalence of material deprivation, excess body weight, inadequate fruit and vegetable consumption, sedentary behaviour, and ever-smoked status. Adjusting for all variables eliminated close to 90% of geographic variation in premature mortality, but did not fully explain the spatial pattern of premature mortality in Ontario.

Conclusions

We conducted the first spatial analysis of mortality in Ontario, revealing large geographic variations. We demonstrate that well-known risk factors explain most of the observed variation in premature mortality. The result emphasizes the importance of population health efforts to reduce the burden of well-known risk factors to reduce variation in premature mortality.

SUBMITTER: Buajitti E

PROVIDER: S-EPMC6670187 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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Publications

Regional variation of premature mortality in Ontario, Canada: a spatial analysis.

Buajitti Emmalin E Watson Tristan T Norwood Todd T Kornas Kathy K Bornbaum Catherine C Henry David D Rosella Laura C LC

Population health metrics 20190731 1

<h4>Background</h4>Premature mortality is a meaningful indicator of both population health and health system performance, which varies by geography in Ontario. We used the Local Health Integration Network (LHIN) sub-regions to conduct a spatial analysis of premature mortality, adjusting for key population-level demographic and behavioural characteristics.<h4>Methods</h4>We used linked vital statistics data to identify 163,920 adult premature deaths (deaths between ages 18 and 74) registered in O ...[more]

PMID: 31366354

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Project description:ObjectivesHealth region differences in immigration patterns and premature mortality rates exist in Ontario, Canada. This study used linked population-based databases to describe the regional proportion of immigrants in the context of provincial health region variation in premature mortality.MethodsWe analyzed all adult premature deaths in Ontario from 1992 to 2012 using linked population files, Canadian census, and death registry databases. Geographic boundaries were analyzed according to 14 health service regions, known as Local Health Integration Networks (LHINs). We assessed the role of immigrant status and regional proportion of immigrants in the context of these health region variations and assessed the contribution using sex-specific multilevel negative binomial models, accounting for age, individual- and area-level immigration, and area-level material deprivation.ResultsWe observed significant premature mortality variation among health service regions in Ontario between 1992 and 2012. Average annual rates ranged across LHINs from 3.03 to 6.40 per 1000 among males and 2.04 to 3.98 per 1000 among females. The median rate ratio (RR) decreased for men from 1.14 (95% CI 1.06, 1.19) to 1.07 (95% CI 1.00, 1.11) after adjusting for year, age, area-based material deprivation, and individual- and area-level immigration, and among females reduced from 1.13 (95% CI 1.05, 1.18) to 1.04 (95% CI 1.00, 1.05). These adjustments explained 84.1% and 94.4% of the LHIN-level variation in males and females respectively. Reduced premature mortality rates were associated with immigrants compared with those for long-term residents in the fully adjusted models for both males 0.43 (95% CI 0.42, 0.44) and females 0.45 (0.44, 0.46).ConclusionThe findings demonstrate that health region differences in premature mortality in Ontario are in part explained by individual-level effects associated with the health advantage of immigrants, as well as contextual area-level effects that are associated with regional differences in the immigrant population. These factors should be considered in addition to health system factors when looking at health region variation in premature deaths.

Project description:BackgroundSenior high cost health care users (HCU) are a priority for many governments. Little research has addressed regional variation of HCU incidence and outcomes, especially among incident HCU. This study describes the regional variation in healthcare costs and mortality across Ontario's health planning districts [Local Health Integration Networks (LHIN)] among senior incident HCU and non-HCU and explores the relationship between healthcare spending and mortality.MethodsWe conducted a retrospective population-based matched cohort study of incident senior HCU defined as Ontarians aged ?66 years in the top 5% most costly healthcare users in fiscal year (FY) 2013. We matched HCU to non-HCU (1:3) based on age, sex and LHIN. Primary outcomes were LHIN-based variation in costs (total and 12 cost components) and mortality during FY2013 as measured by variance estimates derived from multi-level models. Outcomes were risk-adjusted for age, sex, ADGs, and low-income status. In a cost-mortality analysis by LHIN, risk-adjusted random effects for total costs and mortality were graphically presented together in a cost-mortality plane to identify low and high performers.ResultsWe studied 175,847 incident HCU and 527,541 matched non-HCU. On average, 94 out of 1000 seniors per LHIN were HCU (CV?=?4.6%). The mean total costs for HCU in FY2013 were 12 times higher that of non-HCU ($29,779 vs. $2472 respectively), whereas all-cause mortality was 13.6 times greater (103.9 vs. 7.5 per 1000 seniors). Regional variation in costs and mortality was lower in senior HCU compared with non-HCU. We identified greater variability in accessing the healthcare system, but, once the patient entered the system, variation in costs was low. The traditional drivers of costs and mortality that we adjusted for played little role in driving the observed variation in HCUs' outcomes. We identified LHINs that had high mortality rates despite elevated healthcare expenditures and those that achieved lower mortality at lower costs. Some LHINs achieved low mortality at excessively high costs.ConclusionsRisk-adjusted allocation of healthcare resources to seniors in Ontario is overall similar across health districts, more so for HCU than non-HCU. Identified important variation in the cost-mortality relationship across LHINs needs to be further explored.

Project description:ImportanceIdentifying conditions that could be prioritized for research based on health care system burden is important for developing a research agenda for the care of hospitalized children. However, existing prioritization studies are decades old or do not include data from both pediatric and general hospitals.ObjectiveTo assess the prevalence, cost, and variation in cost of pediatric hospitalizations at all general and pediatric hospitals in Ontario, Canada, with the aim of identifying conditions that could be prioritized for future research.Design, setting, and participantsThis population-based cross-sectional study used health administrative data from 165 general and pediatric hospitals in Ontario, Canada. Children younger than 18 years with an inpatient hospital encounter between April 1, 2014, and March 31, 2019, were included.Main outcomes and measuresCondition-specific prevalence, cost of pediatric hospitalizations, and condition-specific variation in cost per inpatient encounter across hospitals. Variation in cost was evaluated using (1) intraclass correlation coefficient (ICC) and (2) number of outlier hospitals. Costs were adjusted for inflation to 2018 US dollars.ResultsOverall, 627 314 inpatient hospital encounters (44.8% among children younger than 30 days and 53.0% among boys) at 165 hospitals (157 general and 8 pediatric) costing $3.3 billion were identified. A total of 408 003 hospitalizations (65.0%) and $1.4 billion (43.8%) in total costs occurred at general hospitals. Among the 50 most prevalent and 50 most costly conditions (of 68 total conditions), the top 10 highest-cost conditions accounted for 55.5% of all costs and 48.6% of all encounters. The conditions with highest prevalence and cost included low birth weight (86.2 per 1000 encounters; $676.3 million), preterm newborn (38.0 per 1000 encounters; $137.4 million), major depressive disorder (20.7 per 1000 encounters; $78.3 million), pneumonia (27.3 per 1000 encounters; $71.6 million), other perinatal conditions (68.0 per 1000 encounters; $65.8 million), bronchiolitis (25.4 per 1000 encounters; $54.6 million), and neonatal hyperbilirubinemia (47.9 per 1000 encounters; $46.7 million). The highest variation in cost per encounter among the most costly medical conditions was observed for 2 mental health conditions (other mental health disorders [ICC, 0.28] and anxiety disorders [ICC, 0.19]) and 3 newborn conditions (intrauterine hypoxia and birth asphyxia [ICC, 0.27], other perinatal conditions [ICC, 0.17], and surfactant deficiency disorder [ICC, 0.17]).Conclusions and relevanceThis population-based cross-sectional study of hospitalized children identified several newborn and mental health conditions as having the highest prevalence, cost, and variation in cost across hospitals. Findings of this study can be used to develop a research agenda for the care of hospitalized children that includes general hospitals and to ultimately build a more substantial evidence base and improve patient outcomes.

Dataset Information

Regional variation of premature mortality in Ontario, Canada: a spatial analysis.

Background

Methods

Results

Conclusions

Publications

Regional variation of premature mortality in Ontario, Canada: a spatial analysis.

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