COVID-19 Vaccine Uptake in Immigrant, Refugee, and Nonimmigrant Children and Adolescents in Ontario, Canada.

Importance: COVID-19 vaccinations are recommended for minors. Surveys indicate lower vaccine acceptance by some immigrant and refugee groups. Objective: To identify characteristics in immigrant, refugee, and nonimmigrant minors associated with vaccination. Design, Setting, and Participants: This retrospective cohort study used linked, population-based demographic and health care data from Ontario, Canada, including all children aged 4 to 17 years registered for universal health insurance on January 1, 2021, across 2 distinct campaigns: for adolescents (ages 12-17 years), starting May 23, 2021, and for children (ages 5-11 years), starting November 25, 2021, through April 24, 2022. Data were analyzed from May 9 to August 2, 2022. Exposures: Immigrant or refugee status and immigration characteristics (recency, category, region of origin, and generation). Main Outcomes and Measures: Outcomes of interest were crude rates of COVID-19 vaccination (defined as ≥1 vaccination for children and ≥2 vaccinations for adolescents) and adjusted odds ratios (aORs) with 95% CIs for vaccination, adjusted for clinical, sociodemographic, and health system factors. Results: The total cohort included 2.2 million children and adolescents, with 1 098 749 children (mean [SD] age, 7.06 [2.00] years; 563 388 [51.3%] males) and 1 142 429 adolescents (mean [SD] age, 14.00 [1.99] years; 586 617 [51.3%] males). Among children, 53 090 (4.8%) were first-generation and 256 886 (23.4%) were second-generation immigrants or refugees; among adolescents, 104 975 (9.2%) were first-generation and 221 981 (19.4%) were second-generation immigrants or refugees, most being economic or family-class immigrants. Immigrants, particularly refugees, were more likely to live in neighborhoods with highest material deprivation (first-generation immigrants: 18.6% of children and 20.2% of adolescents; first-generation refugees: 46.4% of children and 46.3% of adolescents; nonimmigrants: 18.5% of children and 17.2% of adolescents) and COVID-19 risk (first-generation immigrants; 20.0% of children and 20.5% of adolescents; first-generation refugees: 9.4% of children and 12.6% of adolescents; nonimmigrants: 6.9% of children and 6.8% of adolescents). Vaccination rates (53.1% in children and 79.2% in adolescents) were negatively associated with material deprivation. In both age groups, odds for vaccination were higher in immigrants (children: aOR, 1.30; 95% CI, 1.27-1.33; adolescents: aOR, 1.10; 95% CI, 1.08-1.12) but lower in refugees (children: aOR, 0.34; 95% CI, 0.33-0.36; adolescents: aOR, 0.88; 95% CI, 0.84-0.91) compared with nonimmigrants. In immigrant- and refugee-only models stratified by generation, region of origin was associated with uptake, compared with the overall rate, with the lowest odds observed in immigrants and refugees from Eastern Europe (children: aOR, 0.40; 95% CI, 0.35-0.46; adolescents: aOR, 0.41; 95% CI, 0.38-0.43) and Central Africa (children: aOR, 0.24; 95% CI, 0.16-0.35; adolescents: aOR, 0.51,CI: 0.45-0.59) and the highest odds observed in immigrants and refugees from Southeast Asia (children: aOR, 2.68; 95% CI, 2.47-2.92; adolescents aOR, 4.42; 95% CI, 4.10-4.77). Adjusted odds of vaccination among immigrants and refugees from regions with lowest vaccine coverage were similar across generations. Conclusions and Relevance: In this cohort study using a population-based sample in Canada, nonrefugee immigrants had higher vaccine coverage than nonimmigrants. Substantial heterogeneity by region of origin and lower vaccination coverage in refugees persisted across generations. These findings suggest that vaccine campaigns need precision public health approaches targeting specific barriers in identified, undervaccinated subgroups.

Identification of Early Onset Dementia in Population-Based Health Administrative Data: A Validation Study Using Primary Care Electronic Medical Records.

BACKGROUND: Early onset dementia (EOD) occurs when symptoms of dementia begin between 45 to 64 years of age. OBJECTIVE: We developed and validated health administrative data algorithms for EOD and compared demographic characteristics and presence of comorbid conditions amongst adults with EOD, late onset dementia (LOD) and adults with no dementia in Ontario, Canada. METHODS: Patients aged 45 to 64 years identified as having EOD in their primary care electronic medical records had their records linked to provincial health administrative data. We compared several combinations of physician's claims, hospitalizations, emergency department visits and prescriptions. Age-standardized incidence and prevalence rates of EOD were estimated from 1996 to 2016. RESULTS: The prevalence of EOD for adults aged 45 to 64 years in our primary care reference cohort was 0.12%. An algorithm of ≥1 hospitalization or ≥3 physician claims at least 30 days apart in a two-year period or ≥1 dementia medication had a sensitivity of 72.9% (64.5-81.3), specificity of 99.7% (99.7-99.8), positive predictive value (PPV) of 23.7% (19.1-28.3), and negative predictive value of 100.0%. Multivariate logistic regression found adults with EOD had increased odds ratios for several health conditions compared to LOD and no dementia populations. From 1996 to 2016, the age-adjusted incidence rate increased slightly (0.055 to 0.061 per 100 population) and the age-adjusted prevalence rate increased three-fold (0.11 to 0.32 per 100 population). CONCLUSION: While we developed a health administrative data algorithm for EOD with a reasonable sensitivity, its low PPV limits its ability to be used for population surveillance.

Development and validation of an ensemble machine learning framework for detection of all-cause advanced hepatic fibrosis: a retrospective cohort study.

BACKGROUND: Cirrhosis is the result of advanced scarring (or fibrosis) of the liver, and is often diagnosed once decompensation with associated complications has occurred. Current non-invasive tests to detect advanced liver fibrosis have limited performance, with many indeterminate classifications. We aimed to identify patients with advanced liver fibrosis of all-causes using machine learning algorithms (MLAs). METHODS: In this retrospective study of routinely collected laboratory, clinical, and demographic data, we trained six MLAs (support vector machine, random forest classifier, gradient boosting classifier, logistic regression, artificial neural network, and an ensemble of all these algorithms) to detect advanced fibrosis using 1703 liver biopsies from patients seen at the Toronto Liver Clinic (TLC) between Jan 1, 2000, and Dec 20, 2014. Performance was validated using five datasets derived from patient data provided by the TLC (n=104 patients with a biopsy sample taken between March 24, 2014, and Dec 31, 2017) and McGill University Health Centre (MUHC; n=404). Patients with decompensated cirrhosis were excluded. Performance was benchmarked against aspartate aminotransferase-to-platelet ratio index (APRI), fibrosis-4 index (FIB-4), non-alcoholic fatty liver disease fibrosis score (NFS), transient elastography, and an independent panel of five hepatology experts (MB, GS, HK, KP, and RSK). MLA performance was evaluated using the area under the receiver operating characteristic curve (AUROC) and the percentage of determinate classifications. FINDINGS: The best MLA was an ensemble algorithm of support vector machine, random forest classifier, gradient boosting classifier, logistic regression, and neural network algorithms, which achieved 100% determinate classifications (95% CI 100·0-100·0), an AUROC score of 0·870 (95% CI 0·797-0·931) on the TLC validation set (fibrosis stages F0 and F1 vs F4), and an AUROC of 0·716 (95% CI 0·664-0·766) on the MUHC validation set (fibrosis stages F0, F1, and F2 vs F3 and F4). The ensemble MLA outperformed all routinely used biomarkers and achieved comparable performance to hepatologists as measured by AUROC and percentage of indeterminate classifications in both the TLC validation dataset (APRI AUROC score 0·719 [95% CI 0·611-0·820], 83·7% determinate [95% CI 76·0-90·4]; FIB-4 AUROC score 0·825 [95% CI 0·730-0·912], 72·1% determinate [95% CI 63·5-80·8]) and the MUHC validation dataset (APRI AUROC score 0·618 [95% CI 0·548-0·691], 75·5% determinate [95% CI 71·5-79·2]; FIB-4 AUROC score 0·717 (95% CI 0·652-0·776), 75·5% determinate [95% CI 0·713-0·797]), and achieving only slightly lower AUROC than transient elastography (0·773 [95% CI 0·699-0·834] vs 0·826 [95% CI 0·758-0·889]). INTERPRETATION: We have shown that an ensemble MLA outperforms non-imaging-based methods in detecting advanced fibrosis across different causes of liver disease. Our MLA was superior to APRI, FIB-4, and NFS with no indeterminate classifications, while achieving performance comparable to an independent panel of experts. MLAs using routinely collected data could identify patients at high-risk of advanced hepatic fibrosis and cirrhosis among patients with chronic liver disease, allowing intervention before onset of decompensation. FUNDING: Toronto General Hospital Foundation.

The Role of a Resilient Information Infrastructure in COVID-19 Vaccine Uptake in Ontario.

The COVID-19 pandemic has highlighted the need for a robust and nimble public health data infrastructure. ICES - a government-sponsored, independent, non-profit research institute in Ontario, Canada - functions as a key component of a resilient information infrastructure and an enabler of data co-production, contributing to Ontario's response to the COVID-19 pandemic as part of a learning health system. Linked data on the cumulative incidence of infection and vaccination at the neighbourhood level revealed disparate uptake between areas with low versus high risk of COVID-19. These data were leveraged by the government, service providers, media and the public to inform a more efficient and equitable vaccination strategy.

Impact of the diabetes Canada guideline dissemination strategy on dispensed vascular protective medications for older patients in Ontario, Canada: a linked EMR and administrative data study.

BACKGROUND: The 2013 Diabetes Canada guidelines recommended routinely using vascular protective medications for most patients with diabetes. These medications included statins and angiotensin-converting enzyme inhibitors (ACEIs) or angiotensin receptor blockers (ARBs). Antiplatelet agents were only recommended for secondary prevention of cardiovascular disease. Using Electronic Medical Record (EMR) data, we previously found that guideline dissemination efforts were not associated with an increase in the rate of primary care prescriptions of these medications. However, this needs confirmation: patients can receive prescriptions from different sources including specialists and they may not always fill these prescriptions. Using both EMR and administrative health data, we examined whether guideline dissemination impacted the dispensing of vascular protective medications to patients. METHODS: The study population included patients with diabetes aged 66 or over in Ontario, Canada. We created two cohorts using two different approaches: an Electronic Medical Record (EMR) algorithm for diabetes using linked EMR-administrative data and an administrative algorithm using population level administrative data. We examined data from January 2010 to December 2016. Patients with diabetes were deemed to be likely taking a medication (or covered) during a quarter if the daily amount for a dispensed medication would last for at least 75% of days in any given quarter. An interrupted time series analysis was used to assess the proportion of patients covered by each medication class. Proton pump inhibitors (PPIs) were used as a reference. RESULTS: There was no increase in the rate of change for medication coverage following guideline release in either the EMR or the administrative diabetes cohorts. For statins, the change in trend was - 0.03, p = 0.7 (EMR) and - 0.12, p = 0.04(administrative). For ACEI/ARBs, this was 0.03, p = 0.6 (EMR) and 0, p = 1(administrative). For antiplatelets, this was 0.001, P = .97 (EMR) and - 0.03, p = 0.03 (administrative). The comparator PPI was - 0.07, p = 0.4 (EMR) and - 0.11, p = 0.002 (administrative). CONCLUSIONS: Using both EMR and administrative health data, we confirmed that the Diabetes Canada 2013 guideline dissemination strategy did not lead to an increased rate of coverage for vascular protective medications. Alternative strategies are needed to effect change in practice.

Identifying Transitional High Cost Users from Unstructured Patient Profiles Written by Primary Care Physicians.

Identification and subsequent intervention of patients at risk of becoming High Cost Users (HCUs) presents the opportunity to improve outcomes while also providing significant savings for the healthcare system. In this paper, the 2016 HCU status of patients was predicted using free-form text data from the 2015 cumulative patient profiles within the electronic medical records of family care practices in Ontario. These unstructured notes make substantial use of domain-specific spellings and abbreviations; we show that word embeddings derived from the same context provide more informative features than pre-trained ones based on Wikipedia, MIMIC, and Pubmed. We further demonstrate that a model using features derived from aggregated word embeddings (EmbEncode) provides a significant performance improvement over the bag-of-words representation (82.48±0.35% versus 81.85±0.36% held-out AUROC, p = 3.2 × 10-4), using far fewer input features (5,492 versus 214,750) and fewer non-zero coefficients (1,177 versus 4,284). The future HCUs of greatest interest are the transitional ones who are not already HCUs, because they provide the greatest scope for interventions. Predicting these new HCU is challenging because most HCUs recur. We show that removing recurrent HCUs from the training set improves the ability of EmbEncode to predict new HCUs, while only slightly decreasing its ability to predict recurrent ones.

Diabetes quality of care and outcomes: Comparison of individuals with and without schizophrenia.

OBJECTIVE: Individuals with schizophrenia are more likely to develop diabetes than individuals without schizophrenia. The objective of this study was to determine the quality of diabetes care and diabetes-related health outcomes among individuals with and without schizophrenia. METHOD: We conducted a retrospective cohort study. As of April 1, 2011, we identified all individuals with diabetes in Ontario with and without a diagnosis of schizophrenia. The main outcomes were quality of diabetes care (guideline-concordant testing for HbA1c, lipid testing, eye exams) and diabetes-related Emergency Department (ED) visits and hospitalizations between April 1, 2011 and March 31, 2013. We compared quality of care and diabetes outcomes among those with and without schizophrenia, adjusting for demographic, illness severity, and health service utilization variables. RESULTS: We identified 1,131,375 individuals with diabetes, among whom 25,628 (2.3%) had schizophrenia. Schizophrenia was associated with reduced likelihood of optimal diabetes care (all 3 of HbA1c, lipid testing, and eye exams) (adjusted OR (95% CI): 0.64 (0.61-0.67)) and increased likelihood of diabetes-related ED visits (adjusted OR (95% CI): 1.34 (1.28-1.41)) and hospitalizations (adjusted OR (95% CI): 1.36 (1.28-1.43)). CONCLUSION: Individuals with diabetes and schizophrenia have lower rates of recommended testing and higher rates of diabetes-related hospital visits than those with diabetes but without schizophrenia. Research is needed to understand patient, provider, and system factors underlying these disparities and test related interventions to close the gaps in quality of care.

The Hidden Ethics Curriculum in Two Canadian Psychiatry Residency Programs: A Qualitative Study.

OBJECTIVE: The authors describe the hidden ethics curriculum in two postgraduate psychiatry programs. METHODS: Researchers investigated the formal, informal, and hidden ethics curricula at two demographically different postgraduate psychiatry programs in Canada. Using a case study design, they compared three sources: individual interviews with residents and with faculty and a semi-structured review of program documents. They identified the formal, informal, and hidden curricula at each program for six ethics topics and grouped the topics under two thematic areas. They tested the applicability of the themes against the specific examples under each topic. Results pertaining to one of the themes and its three topics are reported here. RESULTS: Divergences occurred between the curricula for each topic. The nature of these divergences differed according to local program characteristics. Yet, in both programs, choices for action in ethically challenging situations were mediated by a minimum standard of ethics that led individuals to avoid trouble even if this meant their behavior fell short of the accepted ideal. CONCLUSIONS: Effective ethics education in postgraduate psychiatry training will require addressing the hidden curriculum. In addition to profession-wide efforts to articulate high-level values, program-specific action on locally relevant issues constitutes a necessary mechanism for handling the impact of the hidden curriculum.