Health trends in Canada 1990-2019: An analysis for the Global Burden of Disease Study.

OBJECTIVE: Monitoring trends in key population health indicators is important for informing health policies. The aim of this study was to examine population health trends in Canada over the past 30 years in relation to other countries. METHODS: We used data on disability-adjusted life years (DALYs), years of life lost (YLL), years lived with disability, life expectancy (LE), and child mortality for Canada and other countries between 1990 and 2019 provided by the Global Burden of Disease Study. RESULTS: Life expectancy, age-standardized YLL, and age-standardized DALYs all improved in Canada between 1990 and 2019, although the rate of improvement has leveled off since 2011. The top five causes of all-age DALYs in Canada in 2019 were neoplasms, cardiovascular diseases, musculoskeletal disorders, neurological disorders, and mental disorders. The greatest increases in all-age DALYs since 1990 were observed for substance use, diabetes and chronic kidney disease, and sense organ disorders. Age-standardized DALYs declined for most conditions, except for substance use, diabetes and chronic kidney disease, and musculoskeletal disorders, which increased by 94.6%, 14.6%, and 7.3% respectively since 1990. Canada's world ranking for age-standardized DALYs declined from 9th place in 1990 to 24th in 2019. CONCLUSION: Canadians are healthier today than in 1990, but progress has slowed in Canada in recent years in comparison with other high-income countries. The growing burden of substance abuse, diabetes/chronic kidney disease, and musculoskeletal diseases will require continued action to improve population health.

RéSUMé: OBJECTIF: La surveillance des tendances des indicateurs clés de la santé de la population est importante pour éclairer les politiques de santé. Dans cette étude, nous avons examiné les tendances de la santé de la population au Canada au cours des 30 dernières années par rapport à d'autres pays. MéTHODES: Nous avons utilisé des données sur les années de vie ajustées en fonction de l'incapacité (DALY), les années de vie perdues (YLL), les années vécues avec un handicap, l'espérance de vie (LE) et la mortalité infantile pour le Canada et d'autres pays entre 1990 et 2019, fournies par l'Étude mondiale sur le fardeau de la maladie. RéSULTATS: L'espérance de vie, les YLL ajustées selon l'âge et les DALY ajustées selon l'âge ont tous connu une amélioration au Canada entre 1990 et 2019, bien que le taux d'amélioration se soit stabilisé depuis 2011. Les cinq principales causes des DALY pour tous les âges au Canada en 2019 étaient les néoplasmes, les maladies cardiovasculaires, les affections musculosquelettiques, les affections neurologiques et les troubles mentaux. Les plus fortes augmentations des DALY pour tous les âges depuis 1990 ont été observées pour l'usage de substances, le diabète et les maladies rénales chroniques, ainsi que les troubles des organes sensoriels. Les DALY ajustées selon l'âge ont diminué pour la plupart des conditions, à l'exception de l'usage de substances, du diabète et des maladies rénales chroniques, ainsi que des troubles musculosquelettiques, qui ont augmenté de 94,6 %, 14,6 % et 7,3 % respectivement depuis 1990. Le classement mondial du Canada pour les DALY ajustées selon l'âge est diminué de la 9ième place en 1990 à la 24ième place en 2019. CONCLUSION: Les Canadiens sont en meilleure santé aujourd'hui qu'en 1990, mais les progrès se sont ralentis ces dernières années par rapport à d'autres pays à revenu élevé. La croissance du fardeau lié à l'abus de substances, au diabète/maladies rénales chroniques et aux affections musculosquelettiques exigera des actions continues pour améliorer la santé de la population.

High-Efficiency Particulate Air Filters for Preventing Wildfire-related Asthma Complications: A Cost-Effectiveness Study.

Rationale: Air pollution caused by wildfire smoke is linked to adverse health outcomes, especially for people living with asthma. Objectives: To evaluate whether government rebates for high-efficiency particulate air (HEPA) filters, which reduce concentrations of smoke particles indoors, are cost effective in managing asthma and preventing exacerbations in British Columbia (BC), Canada. Methods: We used a Markov model to analyze health states for asthma control, exacerbation severity, and death over a retrospective time horizon of 5 years (2018-2022). Concentrations of wildfire smoke-derived particulate matter with an aerodynamic diameter ⩽2.5 µm (PM2.5) from the Canadian Optimized Statistical Smoke Exposure Model and relevant literature informed the model. The base-case analysis assumed continuous use of a HEPA filter. Costs and quality-adjusted life-years (QALYs) resulting from varying rebates were computed for each Health Service Delivery Area (HSDA). Measurements and Main Results: In the base-case analysis, HEPA filter use resulted in increased costs of $83.34 (SE, $1.03) and increased QALYs of 0.0011 (SE, 0.0001) per person. The average incremental cost-effectiveness ratio among BC HSDAs was $74,652/QALY (SE, $3,517), with incremental cost-effectiveness ratios ranging from $40,509 to $89,206 per QALY in HSDAs. Across the province, the intervention was projected to prevent 4,418 exacerbations requiring systemic corticosteroids, 643 emergency department visits, and 425 hospitalizations during the 5-year time horizon. A full rebate was cost effective in 1 of the 16 HSDAs across BC. The probability of cost-effectiveness ranged from 0.1% to 74.8% across HSDAs. A $100 rebate was cost effective in most HSDAs. Conclusions: The cost-effectiveness of HEPA filters in managing wildfire smoke-related asthma issues in BC varies by region. Government rebates up to two-thirds of the filter cost are generally cost effective, with a full rebate being cost effective only in Kootenay Boundary.

Generalizability of Risk Stratification Algorithms for Exacerbations in COPD.

BACKGROUND: Contemporary management of COPD relies on exacerbation history to risk-stratify patients for future exacerbations. Multivariable prediction models can improve the performance of risk stratification. However, the clinical utility of risk stratification can vary from one population to another. RESEARCH QUESTION: How do two validated exacerbation risk prediction models (Acute COPD Exacerbation Prediction Tool [ACCEPT] and the Bertens model) compared with exacerbation history alone perform in different patient populations? STUDY DESIGN AND METHODS: We used data from three clinical studies representing populations at different levels of moderate to severe exacerbation risk: the Study to Understand Mortality and Morbidity in COPD (SUMMIT; N = 2,421; annual risk, 0.22), the Long-term Oxygen Treatment Trial (LOTT; N = 595; annual risk, 0.38), and Towards a Revolution in COPD Health (TORCH; N = 1,091; annual risk, 0.52). We compared the area under the receiver operating characteristic curve (AUC) and net benefit (measure of clinical utility) among three risk stratification algorithms for predicting exacerbations in the next 12 months. We also evaluated the effect of model recalibration on clinical utility. RESULTS: Compared with exacerbation history, ACCEPT showed better performance in all three samples (change in AUC, 0.08, 0.07, and 0.10, in SUMMIT, LOTT, and TORCH, respectively; P ≤ .001 for all). The Bertens model showed better performance compared with exacerbation history in SUMMIT and TORCH (change in AUC, 0.10 and 0.05, respectively; P < .001 for both), but not in LOTT. No algorithm was superior in clinical utility across all samples. Before recalibration, the Bertens model generally outperformed the other algorithms in low-risk settings, whereas ACCEPT outperformed others in high-risk settings. All three algorithms showed the risk of harm (providing lower net benefit than not using any risk stratification). After recalibration, risk of harm was mitigated substantially for both prediction models. INTERPRETATION: Exacerbation history alone is unlikely to provide clinical utility for predicting COPD exacerbations in all settings and could be associated with a risk of harm. Prediction models have superior predictive performance, but require setting-specific recalibration to confer higher clinical utility.

ACCEPT 2·0: Recalibrating and externally validating the Acute COPD exacerbation prediction tool (ACCEPT).

Background: The Acute Chronic Obstructive Pulmonary Disease (COPD) Exacerbation Prediction Tool (ACCEPT) was developed for individualised prediction of COPD exacerbations. ACCEPT was well calibrated overall and had a high discriminatory power, but overestimated risk among individuals without recent exacerbations. The objectives of this study were to 1) fine-tune ACCEPT to make better predictions for individuals with a negative exacerbation history, 2) develop more parsimonious models, and 3) externally validate the models in a new dataset. Methods: We recalibrated ACCEPT using data from the Evaluation of COPD Longitudinally to Identify Predictive Surrogate End-points (ECLIPSE, a three-year observational study, 1,803 patients, 2,117 exacerbations) study by applying non-parametric regression splines to the predicted rates. We developed three reduced versions of ACCEPT by removing symptom score and/or baseline medications as predictors. We examined the discrimination, calibration, and net benefit of ACCEPT 2·0 in the placebo arm of the Towards a Revolution in COPD Health (TORCH, a three-year randomised clinical trial of inhaled therapies in COPD, 1,091 patients, 1,064 exacerbations) study. The primary outcome for prediction was the occurrence of ≥2 moderate or ≥1 severe exacerbation in the next 12 months; the secondary outcomes were prediction of the occurrence of any moderate/severe exacerbation or any severe exacerbation. Findings: ACCEPT 2·0 had an area-under-the-curve (AUC) of 0·76 for predicting the primary outcome. Exacerbation history alone (current standard of care) had an AUC of 0·68. The model was well calibrated in patients with positive or negative exacerbation histories. Changes in AUC in reduced versions were minimal for the primary outcome as well as for predicting the occurrence of any moderate/severe exacerbations (ΔAUC<0·011), but more substantial for predicting the occurrence of any severe exacerbations (ΔAUC<0·020). All versions of ACCEPT 2·0 provided positive net benefit over the use of exacerbation history alone for some range of thresholds. Interpretation: ACCEPT 2·0 showed good calibration regardless of exacerbation history, and predicts exacerbation risk better than current standard of care for a range of thresholds. Future studies need to investigate the utility of exacerbation prediction in various subgroups of patients. Funding: This study was funded by a team grant from the Canadian Institutes of Health Research (PHT 178432).

Development of a conceptual model of childhood asthma to inform asthma prevention policies.

BACKGROUND: There is no definitive cure for asthma, as prevention remains a major goal. Decision analytic models are routinely used to evaluate the value-for-money proposition of interventions. Following best practice standards in decision-analytic modelling, the objective of this study was to solicit expert opinion to develop a concept map for a policy model for primary prevention of asthma. METHODS: We reviewed currently available decision analytic models for asthma prevention. A steering committee of economic modellers, allergists and respirologists was then convened to draft a conceptual model of paediatric asthma. A modified Delphi method was followed to define the context of the problem at hand (evaluation of asthma prevention strategies) and develop the concept map of the model. RESULTS: Consensus was achieved after three rounds of discussions, followed by concealed voting. In the final conceptual model, asthma diagnosis was based on three domains of lung function, atopy and their symptoms. The panel recommended several markers for each domain. These domains were in turn affected by several risk factors. The panel clustered all risk factors under three groups of 'patient characteristic', 'family history' and 'environmental factors'. To be capable of modelling the interplay among risk factors, the panel recommended the use of microsimulation, with an open-population approach that would enable modelling phased implementation and gradual and incomplete uptake of the intervention. CONCLUSIONS: Economic evaluation of childhood interventions for preventing asthma will require modelling of several codependent risk factors and multiple domains that affect the diagnosis. The conceptual model can inform the development and validation of a policy model for childhood asthma prevention.

Innovation in unruptured intracranial aneurysm coiling: At which price or efficacy are new technologies cost-effective?

BACKGROUND: Unruptured intracranial aneurysms (UIA) are increasingly being treated by endovascular coiling as opposed to open surgical clipping. Unfortunately, endovascular coiling imparts an approximate 25% recanalization rate, leading to additional procedures and increased rupture risk. While a new health technology innovation (HTI) that reduces this recanalization rate would benefit patients, few advancements have been made. We aim to determine whether cost-effectiveness has been a barrier to HTI. METHODS: A probabilistic Markov model was constructed from the healthcare payer perspective to compare standard endovascular treatment of UIA to standard treatment plus the addition of a HTI adjunct. Costs were measured in 2018 USD and health outcomes were measured in quality-adjusted life-years (QALY). In the base case, the HTI was a theoretical mesenchymal stem cell therapy which reduced the aneurysm recanalization rate by 50% and cost $10,000 per procedure. All other model inputs were derived from the published scientific literature. RESULTS: Based on the model results, we found that for a given HTI price (y) and relative risk reduction of aneurysm recanalization (x), the HTI was always cost-effective if the following equation was satisfied: y ≤ 20268 ∙ x, using a willingness-to-pay threshold of $50,000 per QALY. The uncertainty surrounding whether an aneurysm would recanalize was a significant driver within the model. When the uncertainty around the risk of aneurysm recanalization was eliminated, the 10-year projected additional benefit to the United States healthcare system was calculated to be $113,336,994. CONCLUSION: Cost-effectiveness does not appear to be a barrier to innovation in reducing the recanalization rate of UIA treated by endovascular coil embolization. Our model can now be utilized by academia and industry to accentuate economically feasible HTI and by healthcare payers to calculate their maximum willingness-to-pay for a new technology. Our results also indicate that predicting a patient's baseline risk of aneurysm recanalization is a critical area of future research.

Value judgments in a COVID-19 vaccination model: A case study in the need for public involvement in health-oriented modelling.

Scientific modelling is a value-laden process: the decisions involved can seldom be made using 'scientific' criteria alone, but rather draw on social and ethical values. In this paper, we draw on a body of philosophical literature to analyze a COVID-19 vaccination model, presenting a case study of social and ethical value judgments in health-oriented modelling. This case study urges us to make value judgments in health-oriented models explicit and interpretable by non-experts and to invite public involvement in making them.

Cost Effectiveness of Case Detection Strategies for the Early Detection of COPD.

OBJECTIVES: The value of early detection and treatment of chronic obstructive pulmonary disease (COPD) is currently unknown. We assessed the cost effectiveness of primary care-based case detection strategies for COPD. METHODS: A previously validated discrete event simulation model of the general population of COPD patients in Canada was used to assess the cost effectiveness of 16 case detection strategies. In these strategies, eligible patients (based on age, smoking history, or symptoms) received the COPD Diagnostic Questionnaire (CDQ) or screening spirometry, at 3- or 5-year intervals, during routine visits to a primary care physician. Newly diagnosed patients received treatment for smoking cessation and guideline-based inhaler pharmacotherapy. Analyses were conducted over a 20-year time horizon from the healthcare payer perspective. Costs are in 2019 Canadian dollars ($). Key treatment parameters were varied in one-way sensitivity analysis. RESULTS: Compared to no case detection, all 16 case detection scenarios had an incremental cost-effectiveness ratio (ICER) below $50,000/QALY gained. In the most efficient scenario, all patients aged ≥ 40 years received the CDQ at 3-year intervals. This scenario was associated with an incremental cost of $287 and incremental effectiveness of 0.015 QALYs per eligible patient over the 20-year time horizon, resulting in an ICER of $19,632/QALY compared to no case detection. Results were most sensitive to the impact of treatment on the symptoms of newly diagnosed patients. CONCLUSIONS: Primary care-based case detection programs for COPD are likely to be cost effective if there is adherence to best-practice recommendations for treatment, which can alleviate symptoms in newly diagnosed patients.

The Acute COPD Exacerbation Prediction Tool (ACCEPT): a modelling study.

BACKGROUND: Accurate prediction of exacerbation risk enables personalised care for patients with chronic obstructive pulmonary disease (COPD). We developed and validated a generalisable model to predict individualised rate and severity of COPD exacerbations. METHODS: In this risk modelling study, we pooled data from three COPD trials on patients with a history of exacerbations. We developed a mixed-effect model to predict exacerbations over 1 year. Severe exacerbations were those requiring inpatient care. Predictors were history of exacerbations, age, sex, body-mass index, smoking status, domiciliary oxygen therapy, lung function, symptom burden, and current medication use. Evaluation of COPD Longitudinally to Identify Predictive Surrogate End-points (ECLIPSE), a multicentre cohort study, was used for external validation. RESULTS: The development dataset included 2380 patients, 1373 (58%) of whom were men. Mean age was 64·7 years (SD 8·8). Mean exacerbation rate was 1·42 events per year and 0·29 events per year were severe. When validated against all patients with COPD in ECLIPSE (mean exacerbation rate was 1·20 events per year, 0·27 events per year were severe), the area-under-curve (AUC) was 0·81 (95% CI 0·79-0·83) for at least two exacerbations and 0·77 (95% CI 0·74-0·80) for at least one severe exacerbation. Predicted exacerbation and observed exacerbation rates were similar (1·31 events per year for all exacerbations and 0·25 events per year for severe exacerbations vs 1·20 events per year and 0·27 events per year). In ECLIPSE, in patients with previous exacerbation history (mean exacerbation rate was 1·82 events per year, 0·40 events per year were severe), AUC was 0·73 (95% CI 0·70-0·76) for two or more exacerbations and 0·74 (95% CI 0·70-0·78) for at least one severe exacerbation. Calibration was accurate for severe exacerbations (predicted 0·37 events per year vs observed 0·40 events per year) and all exacerbations (predicted 1·80 events per year vs observed 1·82 events per year). INTERPRETATION: This model can be used as a decision tool to personalise COPD treatment and prevent exacerbations. FUNDING: Canadian Institutes of Health Research.

An Individualized Prediction Model for Long-term Lung Function Trajectory and Risk of COPD in the General Population.

BACKGROUND: Prediction of future lung function will enable the identification of individuals at high risk of developing COPD, but the trajectory of lung function decline varies greatly among individuals. This study involved the development and validation of an individualized prediction model of lung function trajectory and risk of airflow limitation in the general population. METHODS: Data were obtained from the Framingham Offspring Cohort, which included 4,167 participants ≥ 20 years of age and who had ≥ 2 valid spirometry assessments. The primary outcome was prebronchodilator FEV1; the secondary outcome was the risk of airflow limitation (defined as FEV1/FVC less than the lower limit of normal). Mixed effects regression models were developed for individualized prediction, and a machine learning algorithm was used to determine essential predictors. The model was validated in two large, independent multicenter cohorts (N = 2,075 and 12,913, respectively). RESULTS: With 20 common predictors, the model explained 79% of the variation in FEV1 decline in the derivation cohort. In two validation datasets, the model had low error in predicting FEV1 decline (root mean square error range, 0.18-0.22 L) and high discriminative power in predicting risk of airflow limitation (C-statistic range, 0.86-0.87). This model was implemented in a freely accessible website-based application, which allows prediction based on flexible sets of predictors (http://resp.core.ubc.ca/ipress/FraminghamFEV1). CONCLUSIONS: The individualized predictor is an accurate tool to predict long-term lung function trajectories and risk of airflow limitation in the general population. This model enables identifying individuals at higher risk of COPD, who can then be targeted for preventive therapies.

Cost-effectiveness of implementing objective diagnostic verification of asthma in the United States.

BACKGROUND: Asthma diagnosis in the community is often made without objective testing. OBJECTIVE: The aim of this study was to evaluate the cost-effectiveness of implementing a stepwise objective diagnostic verification algorithm among patients with community-diagnosed asthma in the United States. METHODS: We developed a probabilistic time-in-state cohort model that compared a stepwise asthma verification algorithm on the basis of spirometry testing and a methacholine challenge test against the current standard of care over 20 years. Model input parameters were informed from the literature and with original data analyses when required. The target population was US adults (≥15 years old) with physician-diagnosed asthma. The final outcomes were costs (in 2018 dollars) and quality-adjusted life years (QALYs), discounted at 3% annually. Deterministic and probabilistic analyses were undertaken to examine the effect of alternative assumptions and uncertainty in model parameters on the results. RESULTS: In a simulated cohort of 10,000 adults with diagnosed asthma, the stepwise algorithm resulted in removal of the diagnosis of 3,366. This was projected to be associated with savings of $36.26 million in direct costs and a gain of 4,049.28 QALYs over 20 years. Extrapolating these results to the US population indicated an undiscounted potential savings of $56.48 billion over 20 years. The results were robust against alternative assumptions and plausible changes in values of input parameters. CONCLUSION: Implementation of a simple diagnostic testing algorithm to verify asthma diagnosis might result in substantial savings and improvement in patients' quality of life.

The Projected Economic and Health Burden of Uncontrolled Asthma in the United States.

Rationale: Despite effective treatments, a large proportion of patients with asthma do not achieve sustained asthma control. The "preventable" burden associated with lack of proper control is likely taking a high toll at the personal and population level.Objectives: We predicted the future excess health and economic burden associated with uncontrolled asthma among American adolescents and adults for the next 20 years.Methods: We built a probabilistic model that linked state-specific estimates of population growth, aging, asthma prevalence, and asthma control levels. We conducted several meta-analyses to estimate the adjusted differences in healthcare resource use, quality-adjusted life years (QALYs), and productivity loss across control levels. We projected, nationally and at the state level, total direct and indirect (due to productivity loss) costs (in 2018 dollars) and QALYs lost because of uncontrolled asthma from 2019 to 2038.Measurements and Main Results: Total 20-year direct costs associated with uncontrolled asthma are estimated to be $300.6 billion (95% confidence interval [CI], $190.1 billion-411.1 billion). When indirect costs are added, total economic burden will be $963.5 billion (95% CI, $664.1 billion-1,262.9 billion). American adolescents and adults will lose an estimated 15.46 million (95% CI, 12.77 million-18.14 million) QALYs over this period because of uncontrolled asthma. Across states, the average 20-year per capita costs due to uncontrolled asthma ranged from $2,209 (Arkansas) to $6,132 (Connecticut).Conclusions: The burden of uncontrolled asthma is substantial and will continue to grow. Given that a substantial fraction of this burden is preventable, better adherence to evidence-informed asthma management strategies by care providers and patients has the potential to substantially reduce costs and improve quality of life.