Housing and income are important social determinants of health (SDoH). Primary care providers often do not have information about these determinants, which could be used to support equitable health system planning and care delivery. The aim of this study was to use primary care electronic medical record (EMR) data to test two approaches (machine learning and regular expression searches) to obtain information about patients' housing instability and low income status. We used de-identified EMR data from the St. Michael's Hospital Academic Family Health Team (Toronto, Ontario, Canada). A Health Equity Questionnaire is also routinely distributed to patients and includes questions about income and housing status; this formed the reference standard. First, a regular expression (REGEX) classifier was created using key text terms and codes; the second approach used supervised machine learning models (XGBoost). Discrimination and calibration metrics were calculated as compared to the patient-reported responses. 11,794 eligible patients were included in the housing cohort and 10,454 were in the income cohort. Overall, both approaches had poor sensitivity for determining both housing instability (XGBoost: 3.1%, REGEX: 29.0%) and low income status (XGBoost: 41.7%, REGEX: 17.6%). Positive predictive value (PPV) was satisfactory for the machine learning approach (83.3% for housing, 72.9% for income). While the machine learning approach demonstrated reasonable PPV, the overall metrics were poor and unlikely to be useful in a clinical setting for identifying patients with housing or economic needs. More robust analysis could be explored, but continued patient-captured SDoH information is necessary.

BackgroundAntibiotic use during the coronavirus disease 2019 (Covid-19) pandemic was common in the outpatient setting, but was not supported by guidelines. We sought to evaluate the role of this antibiotic use on downstream antibiotic resistance.MethodsWe performed a population-wide cohort study of all nonhospitalized adults 66 years of age or older in Ontario, Canada, from January 1, 2020, to June 30, 2021, with a first identification of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We evaluated the relationship between outpatient peri–Covid-19 antibiotic exposure (within a period of 7 days before or after index SARS-CoV-2 reporting) and downstream isolation of an antibiotic-resistant organism from clinical culture within 6 months. We calculated adjusted odds ratios of the association between peri–Covid-19 prescribing and antibiotic-resistant organism detection, as well as the adjusted attributable fractions of downstream antibiotic-resistant organisms.ResultsOf the 53,533 eligible individuals included, 8228 (15%) were prescribed a peri–Covid-19 antibiotic, and 1477 (3%) had a downstream antibiotic-resistant organism identified. The adjusted odds ratio for the presence of any antibiotic-resistant organism with peri–Covid-19 antibiotic use was 1.24 (95% confidence interval [CI], 1.09 to 1.41), while the adjusted odds ratio for the presence of gram-negative antibiotic-resistant organisms was 1.27 (95% CI, 1.11 to 1.46) and for gram-positive antibiotic-resistant organisms it was 1.02 (95% CI, 0.70 to 1.48). Among all individuals who received an antibiotic within 7 days of SARS-CoV-2 diagnosis, the attributable fraction of downstream antimicrobial resistance related to peri–Covid-19 antibiotic use was 17% (95% CI, 7 to 26%). Among all individuals with a SARS-CoV-2 diagnosis, the population-attributable fraction of downstream antimicrobial resistance related to peri–Covid-19 antibiotic use was 4% (95% CI, 2 to 7%).ConclusionsPeri–Covid-19 antibiotic use was associated with downstream antimicrobial resistance, and particularly the presence of gram-negative antibiotic-resistant organisms. (Funded by the Canadian Institutes of Health Research Operating Grant [grant number 179461] and others).

We aimed to evaluate an innovative strategy to collect family history (FH) and explore patients' views of this strategy. We conducted a matched-pair effectiveness-implementation trial in family practices affiliated with the University of Toronto Practice-Based Research Network (UTOPIAN). The intervention group included family physicians (FPs) from randomly selected practices using electronic health records (EHRs) and an e-mailing platform, and randomly selected patients aged 30-69 years (4/FP/week) seen in clinic over a 6-month period. The matched control group included FPs (1:1) and patients (up to 5:1) from the UTOPIAN database. The intervention included patient and FP education, an e-mailed patient invitation to complete an FH questionnaire, automatic FH EHR upload, FP notification of completed FH questionnaire, and links to clinical support tools. Intervention patients were e-mailed a postvisit follow-up questionnaire. The assessed outcome was new documentation of FH in the EHR using mixed effects logistic regression and descriptive statistics for patient feedback. Fifteen FPs and 576 patients were recruited from 3 multidisciplinary team practices to the intervention group, matched to 15 FPs and 2,203 patients in the control group. Within 30 days of visit, a new FH was documented in the EHR for 93/576 (16.1%) of intervention patients compared with 5/2,203 (0.2%) control patients (adjusted OR = 94.2; 95% CI, 36.8-240.8). New cancer FH documentation was greater in the intervention group compared with the control group (7.8% vs 0.1%; P < .01). Of patients who reported discussing FH (n = 296), 24.5% reported screening test recommended, 7.5% referral to a nongenetics specialist, and 2.4% referral to a genetics specialist. Most patients (60.5%) found this FH strategy helpful. This study showed improved collection/documentation of FH. Contributors to success of the intervention included being patient completed and seamless EHR integration with a reminder. This FH strategy needs tailoring to different contexts.

ObjectiveTo identify views and establish agreements of key stakeholders on the features of an effective system for declaring and managing conflicts of interest in healthcare.DesignA modified Delphi study consisting of two surveys and semi-structured interviews. Surveys included closed and free-text questions.Setting and participantsUK, purposefully and generally invited participants including academics, researchers, healthcare professionals, regulators, patients and citizens from 10 countries, during 25 August 2024 and 20 January 2025.Main outcome measuresQuantitative and qualitative analysis of two surveys and 21 interviews. Descriptive statistics were used to describe the sample and analyse closed survey questions. Thematic analysis was used to analyse free-text survey responses and interview data. Results were synthesised to describe the perceived importance and purposes of declaration of interest systems.ResultsIn the first survey round, 616 invitations were sent, along with social media advertisements. 237 questionnaires were returned and 200 full responses were analysable. 129 respondents consented to recontact on the online form. In the interview round, 37 invitations were sent and 21 interviews completed (response rate 59.5%). Invitations for the second survey were sent to all 129 participants who consented to recontact. 91 responses were received and 89 questionnaires were analysable (response rate 82%). Features of ideal systems to declare and manage the interests of healthcare professionals identified by participants were categorised under seven themes: regulatory issues, the healthcare environment, human vices, professional virtues, the use of judgement, features of a better system and patients and public. There was broad agreement on the need for transparency and clarity in declaration systems. The most agreed features were: clarity on what information was needed; it should be a centralised ‘deposit’ for all declarations; it should be publicly accessible, educating and informing people accessing and using the register. Having a lifelong personal identifier, some flexibility in declarations and some privacy features were also rated highly. Respondents were less concerned about scrutiny or a loss of trust. Small numbers of participants raised concerns about serious adverse effects, including loss of privacy, personal safety and the potential of information to contribute to conspiracy theories. There were also major disagreements between participants concerning whether or not healthcare professionals should work with industry, and whether conflicts of interest from working with industry can be safely managed. Individuals with each perspective felt they were acting ethically.ConclusionsWhile many agreements were identified, disagreements were also found. If improved declaration systems are to be accepted by professionals and useful to regulators, patients and citizens, the potential for benefit and harm from new declaration systems must be addressed.Registration detailsPrepublished, Open Science Framework https://osf.io/fbj5n.

BackgroundForeign-born children may face greater barriers to accessing routine immunizations in Canada or their country of birth, but provincial surveillance data on immigration status are lacking. Using our provincial immunization repository linked to administrative data, we assessed immunization coverage among immigrant and refugee children in Ontario, Canada, compared with Ontario-born children and identified factors associated with being up-to-date (UTD).MethodsWe conducted a retrospective cohort study of children entering school during the 2012/13–2014/15 school years. We calculated UTD coverage for measles (2 doses), diphtheria (4 doses), and polio (3 doses) vaccines at school entry and two years after school attendance. We compared UTD coverage between immigrant/refugee children and Ontario-born children using standardized differences (SD).ResultsIn a cohort of 363,662 children, 15,114 (4.2%) were immigrants/refugees (82.1% immigrants, 17.9% refugees). UTD coverage for all antigens combined was 59.2% among immigrant/refugee children compared with 87.9% among Ontario-born children at school entry (SD = 0.69), increasing to 84.9% and 94.3%, respectively, two years after school entry (SD = 0.31). Coverage was lower with greater disparities between immigrant/refugee and Ontario-born children for measles (87.9% vs. 94.8%, SD = 0.25) and diphtheria (94.6% vs. 97.4%, SD = 0.15) after two years than polio (97.1% vs. 98.4%, SD = 0.09). Among immigrant/refugee children, coverage was lowest in refugees (vs. immigrants), recent immigrants, and those born in certain regions.ConclusionsImmunization coverage among foreign-born children lagged behind their Ontario-born peers, even after two years of school attendance. Findings varied by vaccine, immigration category, time spent in Ontario, and country of birth.

ObjectiveThe emergency department (ED) often serves as a crucial pathway for cancer diagnosis. However, little is known about the management of patients with new suspected cancer diagnoses in the ED. The objective of this study was to explore emergency physicians’ experiences in managing patients with a newly suspected cancer diagnosis in the ED.DesignBetween January and April 2024, we conducted a qualitative descriptive study. Interviews were conducted by trained research personnel using a semistructured interview guide. Interviews were conducted until thematic saturation was achieved. The interview transcripts were coded and thematic analysis was used to uncover key themes.Setting and participantsEmergency physicians practising in Ontario, Canada.Results20 emergency physicians were interviewed. Four themes around the management of patients with new suspected cancer diagnoses in the ED were identified: (1) healthcare system-level factors that impact suspected cancer diagnosis through the ED, (2) institutional and provider-level challenges associated with managing patients with a suspected cancer diagnosis in the ED, (3) patient-level characteristics and experiences of receiving a cancer diagnosis in the ED and (4) the need for care coordination for patients with suspected cancer in the ED.ConclusionsPhysicians experienced several unique challenges in managing patients with a suspected cancer diagnosis in the ED. Overall, the findings of this study suggest these challenges often make the ED a difficult environment in which to deliver a suspected cancer diagnosis.

Black-White disparities in maternal and neonatal morbidity and mortality highlight health inequities in several settings, yet such racial disparities in Canada are not well defined. Our objective was to conduct a scoping review to identify the extent of epidemiologic evidence assessing Black-White disparities in maternal and neonatal health in Canada. We included peer-reviewed epidemiologic studies which measured maternal or neonatal outcomes in Black versus White individuals in Canada. We searched OVID platforms (MEDLINE, Embase, Emcare) from inception to May 9, 2024, using keywords and controlled vocabulary terms related to race and maternal and neonatal morbidity and mortality. Results synthesis was carried out using descriptive analysis. After exclusions, six retrospective cohort studies were included in the scoping review. The majority of the included studies used data obtained from provincial datasets (n = 5), defined maternal race using self-reported race (n = 5), and were set in Ontario (n = 4). All studies reported one or more significant associations between race and adverse maternal or neonatal outcomes, with Black individuals experiencing higher rates of spontaneous fetal loss (n = 1), perinatal mortality (n = 1), preterm birth (n = 3), small for gestational age infants (n = 1), low Apgar scores (n = 2), congenital heart disease (n = 1), neonatal intensive care unit admission (n = 1), preeclampsia (n = 2), gestational diabetes (n = 1), and inadequate gestational weight gain (n = 1). Although literature on the topic is sparse, Black-White disparities in maternal and neonatal health in Canada are apparent. National, population-based data are needed to provide a comprehensive understanding of racial disparities in maternal and neonatal health and the factors driving these differences.

Due to a lack of safeguards, controlled substances (CS) can be diverted (stolen) from healthcare facilities. While it is known that healthcare workers (HCWs) can use their social networks within the medication use process (MUP) to facilitate diversion, the specific connections between HCWs and the MUP tasks most vulnerable to diversion remain poorly understood. Social network analysis (SNA) was used to analyze social connections to identify influential relationships between HCWs and tasks susceptible to diversion.To map the social network structures of MUP tasks vulnerable to CS diversion in two Emergency Departments (EDs), identify influential tasks and HCWs, and report HCW perceptions of in-hospital diversion.This study used a mixed methods approach in the ED of two large hospitals in Toronto, Canada. Previously collected clinical observation data was used to identify tasks at risk of diversion, and cross-sectional surveys were conducted to assess HCW’s involvement in the identified vulnerable tasks. A two-mode SNA was conducted to identify connections between HCWs and tasks susceptible to drug diversion.SNA identified a circular structure across both sites, highlighting the network’s redundancy and capacity to efficiently disseminate information. Nurses were central to tasks with a higher risk of diversion. Physicians and Pharmacists had limited direct involvement in these tasks. Tasks with frequent interprofessional interactions, such as creating, following, or reviewing orders for non-admitted patients, are vulnerable to diversion due to HCWs acting on decisions made by other professionals without closely scrutinizing the details. No significant differences were observed between sites, suggesting a shared perception of diversion. The SNA results highlight the critical role of network structure in shaping vulnerability to diversion. The similarities across both sites suggest a systemic challenge across ED settings that require targeted interventions. By uncovering critical points of influence, we can better understand how diversion occurs and develop targeted interventions to prevent it.