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Introduction In Ontario, Canada, parents have the responsibility to report their child’s routine infant and childhood vaccines to the provincial immunization registry (the Digital Health Immunization Repository; DHIR) without healthcare provider validation. Despite its use in routine immunization coverage monitoring, no study has previously examined the completeness of immunization data within the DHIR. Methods We assessed the completeness of DHIR immunizations, as compared to immunizations within the Electronic Medical Records—Primary Care (EMRPC) database, also known as EMRALD, a network of family physician electronic medical records (EMRs). We linked client records from the DHIR and EMRPC to a centralized population file. To create the study cohort, we examined children born during 2005–2008 and further defined the cohort based on those rostered to an EMRPC physician, visit criteria to ensure ongoing care by an EMRPC provider, and school attendance in Ontario at age 7. We calculated up-to-date (UTD) immunization coverage at age 7 for individual vaccines and overall using data from the DHIR and EMRPC separately, and compared the estimates. Results The analytic cohort to assess DHIR data completeness included 2,657 children. Overall UTD coverage (all vaccines assessed) was 82.0% in the DHIR and 67.6% in EMRPC. UTD coverage was higher in the DHIR for all vaccines assessed individually, with the exception of meningococcal C conjugate vaccine (difference = 0.3%). After excluding two EMRPC sites with irregularities in immunization data, the difference in overall UTD coverage between systems decreased from 14.4% to 6.6% Interpretation These results validate the use of DHIR for coverage assessment but also suggest that bidirectional exchange of immunization information has the potential to increase immunization data completeness in both systems.

BackgroundThe novel coronavirus disease 2019 (COVID-19) has infected 1.9% of the world population by May 2, 2021. Since most previous studies that examined risk factors for mortality and severity were based on hospitalized individuals, population-based cohort studies are called for to provide evidence that can be extrapolated to the general population. Therefore, we aimed to examine the associations of comorbidities with mortality and disease severity in individuals with COVID-19 diagnosed in 2020 in Ontario, Canada.Methods and findingsWe conducted a retrospective cohort study of all individuals with COVID-19 in Ontario, Canada diagnosed between January 15 and December 31, 2020. Cases were linked to health administrative databases maintained in the ICES which covers all residents in Ontario. The primary outcome is all-cause 30-day mortality after the first COVID-19 diagnosis, and the secondary outcome is a composite severity index containing death and hospitalization. To examine the risk factors for the outcomes, we employed Cox proportional hazards regression models and logistic regression models to adjust for demographic, socio-economic variables and comorbidities. Results were also stratified by age groups. A total of 167,500 individuals were diagnosed of COVID-19 in 2020 and included in the study. About half (43.8%, n = 73,378) had at least one comorbidity. The median follow-up period were 30 days. The most common comorbidities were hypertension (24%, n = 40,154), asthma (16%, n = 26,814), and diabetes (14.7%, n = 24,662). Individuals with comorbidity had higher risk of mortality compared to those without (HR = 2.80, 95%CI 2.35–3.34; pConclusionWe found that solid organ transplant, dementia, chronic kidney disease, severe mental illness, CVD, hypertension, COPD, cancer, diabetes, rheumatoid arthritis, HIV, and asthma were associated with mortality or severity. Our study highlights that the number of comorbidities was a strong risk factor for deaths and severe outcomes among younger individuals with COVID-19. Our findings suggest that in addition of prioritizing by age, vaccination priority groups should also include younger population with multiple comorbidities.

IntroductionThe Applied Health Research Question (AHRQ) portfolio is an initiative funded by the Ontario Ministry of Health. Knowledge users submit AHRQ requests to use administrative health data to inform their planning, policy and program development. Objectives and ApproachA request to estimate prevalence and incidence of blood-borne viral infections (BBVI) among individuals seeking fertility treatment services was approved by the ICES AHRQ team. To determine whether current BBVI testing guidelines are effective for timely identification of BBVI among individuals undergoing fertility treatment, this AHRQ sought to estimate: a) the testing prevalence for BBVI (using viral hepatitis as a proxy for all BBVI including HIV), and b) BBVI incidence over a five-year follow-up period. We used infertility codes billed by gynecologists and urologists to identify individuals seeking fertility treatment between April 1, 2002 and March 31, 2013. We looked forward five years from a first BBVI test billed by a physician and assessed annual and cumulative testing prevalence and incidence of viral hepatitis and HIV using rule-based administrative algorithms. ResultsIn total, 184,328 individuals (61.6% female) were included. The five-year BBVI testing prevalence was 45.5% and the median number of tests was 2 (interquartile range: 2-3). An estimated 949 new cases (48% diagnosed within 12 months of first BBVI test) of viral hepatitis were identified in the five-year follow-up with a cumulative incidence of 522 (95%CI 489-556) per 100,000 population. There were 57 new HIV cases (68% diagnosed within 12 months of first BBVI test) with a cumulative incidence of 31.4 (95%CI 23.7-40.6) per 100,000. The median times from first BBVI test to hepatitis and HIV diagnoses were 13.0 months (IQR 2.33-32.2) and 3.0 months (IQR 1.34-20.0), respectively. Conclusion / ImplicationsThese findings can be used to develop evidence-based BBVI testing guidelines for individuals seeking fertility treatment services.

Background Quantifying the potential cancer cases associated with environmental carcinogen exposure can help inform efforts to improve population health. This study developed an approach to estimate the environmental burden of cancer and applied it to Ontario, Canada. The purpose was to identify environmental carcinogens with the greatest impact on cancer burden to support evidence-based decision making. Methods We conducted a probabilistic assessment of the environmental burden of cancer in Ontario. We selected 23 carcinogens that we defined as “environmental” (e.g., pollutants) and were relevant to the province, based on select classifications provided by the International Agency for Research on Cancer. We evaluated population exposure to the carcinogens through inhalation of indoor/outdoor air; ingestion of food, water, and dust; and exposure to radiation. We obtained or calculated concentration-response functions relating carcinogen exposure and the risk of developing cancer. Using both human health risk assessment and population attributable fraction models in a Monte Carlo simulation, we estimated the annual cancer cases associated with each environmental carcinogen, reporting the simulation summary (e.g., mean and percentiles). Results We estimated between 3540 and 6510 annual cancer cases attributable to exposure to 23 environmental carcinogens in Ontario. Three carcinogens were responsible for over 90% of the environmental burden of cancer: solar ultraviolet (UV) radiation, radon in homes, and fine particulate matter (PM2.5) in outdoor air. Eight other carcinogens had an estimated mean burden of at least 10 annual cancer cases: acrylamide, arsenic, asbestos, chromium, diesel engine exhaust particulate matter, dioxins, formaldehyde, and second-hand smoke. The remaining 12 carcinogens had an estimated mean burden of less than 10 annual cancer cases in Ontario. Conclusions We found the environmental burden of cancer in Ontario to fall between previously estimated burdens of alcohol and tobacco use. These results allow for a comparative assessment across carcinogens and offer insights into strategies to reduce the environmental burden of cancer. Our analysis could be adopted by other jurisdictions and repeated in the future for Ontario to track progress in reducing cancer burden, assess newly classified environmental carcinogens, and identify top burden contributors.

Background: Cirrhosis is often diagnosed once complications such as ascites, encephalopathy and variceal bleeding have occurred. Current non-invasive tests to detect cirrhosis have limited performance, with many patients falling into the indeterminate category. Objectives: To identify patients with well-compensated liver cirrhosis of all-causes using machine learning algorithms (MLAs) trained on routinely measured clinical and laboratory parameters. Design, Setting, and Participants: Retrospective, cross-sectional study on patients with F0, F1, and F4 fibrosis staged via biopsy at the Toronto Liver Clinic, validated on 508 patients with F0 to F4 fibrosis staged via biopsy locally as well as at the McGill University Health Centre. Patients with decompensated cirrhosis were excluded. We trained 7 MLAs to identify patients with compensated cirrhosis. Performance was benchmarked against the Aspartate aminotransferase (AST)-to-Platelet Ratio Index (APRI), Fibrosis-4 index (FIB-4), nonalcoholic fatty liver disease (NAFLD) fibrosis score (NFS), Transient Elastography (TE), and an independent panel of 5 experts. Results: The best MLA achieved a cross-validation area under the receiver operating characteristic curve (AUROC) of 0.88 for identifying patients with well-compensated cirrhosis, with less than 8% indeterminate classifications. The MLA achieved higher or comparable AUROC to FIB-4 on both validation sets with 20% fewer indeterminate classifications. Additionally, we show that by altering cutoffs, the MLA outperformed expert hepatologists and the NFS score and achieved superior specificity to transient elastography. Conclusion: In this study, we have demonstrated that an MLA outperforms non-imaging based methods in detecting well-compensated cirrhosis across multiple etiologies of liver disease. Our MLA was superior to APRI, FIB-4, and NFS with significantly fewer indeterminate classifications, while achieving performance comparable to an independent panel of experts. MLAs using routinely collected data could flag patients with well-compensated liver cirrhosis among patients with chronic liver disease, allowing intervention prior to onset of decompensation and associated complications. Funding Statement: This study was supported by ICES, which is funded by an annual grant from the Ontario Ministry of Health and Long-Term Care (MOHLTC). Declaration of Interests: We have no competing interests to declare. Ethics Approval Statement: Ethics approval was obtained from the Research Ethics Boards at the University Health Network, SickKids Research Institute, and MUHC.

IntroductionCertain subject behaviours and characteristics increase the risk of some cancer types (e.g., obesity, alcohol intake) while others reduce cancer risk (e.g., physical activity). In 2007, the World Cancer Research Fund (WCRF) and American Institute for Cancer Research (AICR) published recommendations to reduce cancer risk related to these behaviours. Objectives and ApproachThe objective is to examine the association between self-reported behaviour consistent with WCRF/AICR recommendations for body fatness, physical activity, vegetable/fruit consumption, and alcohol intake and the risk of all cancers combined and specific cancer types. The study cohort, comprised of the Canadian Community Health Survey (CCHS) Ontario sample, will be linked with health administrative databases, including the Ontario Cancer Registry to determine cancer outcomes. Individuals will be assessed for behaviours consistent with WCRF/AICR recommendations based on their responses to CCHS questions and the association of these behaviours with cancer risk will be explored using multivariable Cox proportional hazard regression models. ResultsTo detect a log hazard ratio of 1.10 (where a=0.05, power=0.80, proportion of the sample assigned to the exposure group=0.25 and R2=0.20), a sample size of 4,538 is required. Based on the number of records in the CCHS data frame (159,474) and an assumption that the CCHS sample experiences cancer incidence at a similar rate to the rest of the Ontario population, we expect to have 5,000 cancer cases for these analyses. Upon completion of the analysis, we will report hazard ratios that estimate the difference in cancer risk between individuals reporting behaviour consistent with the WCRF/AICR recommendations and those reporting behaviour not consistent with the recommendations. Conclusion/ImplicationsWCRF/AICR recommendations were developed as the basis for primary cancer prevention, both for individuals and population-wide policies and programs. The current study will quantify the difference in overall cancer risk between individuals who do and do not adhere to selected WCRF/AICR recommendations for the first time in a Canadian population.

Background Available evidence has demonstrated survival benefits associated with multidisciplinary cardiovascular risk-reduction (CR) (ie, cardiac rehabilitation) programs. The degree to which program capacity meets eligible service demands in Ontario is unknown. We sought to estimate the supply-need care-gap associated with CR programs across regions (Local Health Integration Networks [LHINs]) in Ontario. Methods We conducted a cross-sectional, population-based study during 2006. Administrative data provided estimates of the population eligible for multidisciplinary CR services due to (1) recent cardiovascular hospitalizations and (2) incident diabetes. An Ontario-wide survey of CR programs provided service supply estimates. The coverage rate and the absolute supply-need mismatch were use to quantify the care-gap by LHIN. Results Based on cardiac hospitalizations alone, 53,270 patients in Ontario in 2006 (508.7 per 100,000) were eligible for CR services; 128,869 patients (1245 per 100,000) would have been eligible if newly diagnosed (incident cases) diabetic patients were included. Capacity for CR services was 18,087 patients, corresponding to 34% coverage of the eligible population (absolute unmet needs of 35,189 individuals) if capacity was entirely dedicated to recent hospitalizations and 14% coverage (absolute unmet needs of 110,782) if services were extended to include incident diabetes patients. Marked variation in disease burden, service capacity, and supply-need mismatch was observed across regions, in which supply was not correlated with need. Conclusion Despite proved benefits of multidisciplinary CR programs, unmet population needs remain high in Ontario and are unequally distributed across regions. The magnitude of unmet needs and the lack of correlation between supply and disease burden necessitate broader provincial strategies to plan, allocate, and subsidize CR programs.