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Our study aimed to describe patient experience of information coordination between their primary care physician and specialists and to examine the associations between their experience and their personal and primary care characteristics. We conducted a cross-sectional study of Ontario residents rostered to a primary care physician and visited a specialist physician in the previous 12 months by linking population-based health administrative data to the Health Care Experience Survey collected between 2013 and 2020. We described respondents' sociodemographic and health care utilization characteristics and their experience of information coordination between their primary care physician and specialists. We measured the adjusted association between patient-reported measures of information coordination before and after respondents received care from a specialist physician and their type of primary care model. 1,460 out 20,422 (weighted 7.5%) of the respondents reported that their specialist physician did not have basic medical information about their visit from their primary care physician in the previous 12 months. 2,298 out of 16,442 (weighted 14.9%) of the respondents reported that their primary care physician seemed uninformed about the care they received from the specialist. Females, younger individuals, those with a college or undergraduate level of education, and users of walk-in clinics had a higher likelihood of reporting a lack of information coordination between the primary care and specialist physicians. Only respondents rostered to an enhanced fee-for-service model had a higher odds of reporting that the specialist physician did not have basic medical information about their visit compared to those rostered to a Family Health Team (OR 1.22, 95% Cl 1.12–1.40). We found no significant association between respondent's type of primary care model and that their primary care physician was uninformed about the care received from the specialist physician. In this population-based health study, respondents reported high information coordination between their primary care physician and specialists. Except for respondents rostered to an enhanced fee-for-service model of care, we did not find any difference in information coordination across other primary care models. [ABSTRACT FROM AUTHOR]

Objective: Current scores for predicting sepsis outcomes are limited by generalizability, complexity, and electronic medical record (EMR) integration. Here, we validate a simple EMR-based score for sepsis outcomes in a large multi-centre cohort. Design: A simple electronic medical record-based predictor of illness severity in sepsis (SEPSIS) score was developed (4 additive lab-based predictors) using a population-based retrospective cohort study. Setting: Internal medicine services across four academic teaching hospitals in Toronto, Canada from April 2010—March 2015 (primary cohort) and 2015–2019 (secondary cohort). Patients: We identified patients admitted with sepsis based upon receipt of antibiotics and positive cultures. Measurements and main results: The primary outcome was in-hospital mortality and secondary outcomes were ICU admission at 72 hours, and hospital length of stay (LOS). We calculated the area under the receiver operating curve (AUROC) for the SEPSIS score, qSOFA, and NEWS2. We then evaluated the SEPSIS score in a secondary cohort (2015–2019) of hospitalized patients receiving antibiotics. Our primary cohort included 1,890 patients with a median age of 72 years (IQR: 56–83). 9% died during hospitalization, 18.6% were admitted to ICU, and mean LOS was 12.7 days (SD: 21.5). In the primary and secondary (2015–2019, 4811 patients) cohorts, the AUROCs of the SEPSIS score for predicting in-hospital mortality were 0.63 and 0.64 respectively, which were similar to NEWS2 (0.62 and 0.67) and qSOFA (0.62 and 0.68). AUROCs for predicting ICU admission at 72 hours, and length of stay > 14 days, were similar between scores, in the primary and secondary cohorts. All scores had comparable calibration for predicting mortality. Conclusions: An EMR-based SEPSIS score shows a similar ability to predict important clinical outcomes compared with other validated scores (qSOFA and NEWS2). Because of the SEPSIS score's simplicity, it may prove a useful tool for clinical and research applications. [ABSTRACT FROM AUTHOR]

Background: High-quality primary care is associated with better health outcomes and more efficient and equitable health system performance. However, the rate of primary care attachment is falling, and timely access to primary care is worsening, driving many patients to use walk-in clinics for their comprehensive primary care needs. This study sought to explore the experiences and perceived roles and responsibilities of walk-in physicians in this current climate. Methods: Qualitative interviews were conducted with nineteen physicians currently providing walk-in care in Ontario, Canada between May and December 2022. Results: Limited capacity for continuity and comprehensiveness of care were identified as major sources of professional tension for walk-in physicians. Divergent perspectives on their roles were anchored in how physicians viewed their professional identity. Some saw providing continuous and comprehensive care as an infringement on their professional role; others saw their professional role as more flexible and responsive to population needs. Regardless of their professional identity, participants reported feeling ill-equipped to manage the swell of unattached patients, citing a lack of time, resources, connectivity to the system, and remuneration flexibility. Conclusions: As practice demands of walk-in clinics change, an evolution in the professional roles and responsibilities of walk-in physicians follows. However, the resources, structure, and incentives of walk-in care have not evolved to reflect this, leaving physicians to set their own professional boundaries with patients. This results in increasing variations in care and confusion across the primary care sector around who is responsible for what, when, and how. [ABSTRACT FROM AUTHOR]

Background: Delirium is a major cause of preventable mortality and morbidity in hospitalized adults, but accurately determining rates of delirium remains a challenge. Objective: To characterize and compare medical inpatients identified as having delirium using two common methods, administrative data and retrospective chart review. Methods: We conducted a retrospective study of 3881 randomly selected internal medicine hospital admissions from six acute care hospitals in Toronto and Mississauga, Ontario, Canada. Delirium status was determined using ICD-10-CA codes from hospital administrative data and through a previously validated chart review method. Baseline sociodemographic and clinical characteristics, processes of care and outcomes were compared across those without delirium in hospital and those with delirium as determined by administrative data and chart review. Results: Delirium was identified in 6.3% of admissions by ICD-10-CA codes compared to 25.7% by chart review. Using chart review as the reference standard, ICD-10-CA codes for delirium had sensitivity 24.1% (95%CI: 21.5–26.8%), specificity 99.8% (95%CI: 99.5–99.9%), positive predictive value 97.6% (95%CI: 94.6–98.9%), and negative predictive value 79.2% (95%CI: 78.6–79.7%). Age over 80, male gender, and Charlson comorbidity index greater than 2 were associated with misclassification of delirium. Inpatient mortality and median costs of care were greater in patients determined to have delirium by ICD-10-CA codes (5.8% greater mortality, 95% CI: 2.0–9.5 and $6824 greater cost, 95%CI: 4713–9264) and by chart review (11.9% greater mortality, 95%CI: 9.5–14.2% and $4967 greater cost, 95%CI: 4415–5701), compared to patients without delirium. Conclusions: Administrative data are specific but highly insensitive, missing most cases of delirium in hospital. Mortality and costs of care were greater for both the delirium cases that were detected and missed by administrative data. Better methods of routinely measuring delirium in hospital are needed. [ABSTRACT FROM AUTHOR]

Aims: Certain combinations of medications can be harmful and may lead to serious adverse drug events (ADEs). Identifying potentially problematic medication clusters could help guide prescribing and/or deprescribing decisions in hospital. The aim of this study is to characterize medication prescribing patterns at hospital discharge and determine which medication clusters were associated with an increased risk of ADEs in the 30‐day posthospital discharge. Methods: All residents of the province of Ontario in Canada aged 66 years or older admitted to hospital between March 2016 and February 2017 were included. Identification of medication clusters prescribed at hospital discharge was conducted using latent class analysis. Cluster identification and categorization were based on medications dispensed up to 30‐day posthospitalization. Multivariable logistic regression was used to assess the potential association between membership to a particular medication cluster and ADEs postdischarge, while also evaluating other patient characteristics. Results: In total, 188 354 patients were included in the study cohort. Median age (interquartile range) was 77 (71–84) years, and patients had a median (IQR) (interquartile range [IQR]) of 9 (6–13) medications dispensed prior to admission. Within the study population, 6 separate clusters of dispensing patterns were identified: cardiovascular (14%), respiratory (26%), complex care needs (12%), cardiovascular and metabolic (15%), infection (10%), and surgical (24%). Overall, 12 680 (7%) patients had an ADE in the 30 days following discharge. After considering other patient characteristics, those belonging to the respiratory cluster had the highest risk of ADEs (adjusted odds ratio: 1.12, 95% confidence interval: 1.08–1.17) compared with all the other clusters, while those in the complex care needs cluster had the lowest risk (adjusted odds ratio: 0.82, 95% confidence interval: 0.77–0.87). Conclusion: This study suggests that ADEs post hospital discharge can be linked with identifiable medication clusters. This information may help clinicians and researchers better understand patient populations that are more or less likely to benefit from peri‐hospital discharge interventions aimed at reducing ADEs. PLAIN LANGUAGE SUMMARY: Certain combinations of medications prescribed to patients when they are being discharged from hospital can increase the risk of adverse events after hospital discharge. [ABSTRACT FROM AUTHOR]

Background: Prognostic information at the time of hospital discharge can help guide goals-of-care discussions for future care. We sought to assess the association between the Hospital Frailty Risk Score (HFRS), which may highlight patients' risk of adverse outcomes at the time of hospital discharge, and in-hospital death among patients admitted to the intensive care unit (ICU) within 12 months of a previous hospital discharge. Methods: We conducted a multicentre retrospective cohort study that included patients aged 75 years or older admitted at least twice over a 12-month period to the general medicine service at 7 academic centres and large community-based teaching hospitals in Toronto and Mississauga, Ontario, Canada, from Apr. 1, 2010, to Dec. 31, 2019. The HFRS (categorized as low, moderate or high frailty risk) was calculated at the time of discharge from the first hospital admission. Outcomes included ICU admission and death during the second hospital admission. Results: The cohort included 22 178 patients, of whom 1767 (8.0%) were categorized as having high frailty risk, 9464 (42.7%) as having moderate frailty risk, and 10 947 (49.4%) as having low frailty risk. One hundred patients (5.7%) with high frailty risk were admitted to the ICU, compared to 566 (6.0%) of those with moderate risk and 790 (7.2%) of those with low risk. After adjustment for age, sex, hospital, day of admission, time of admission and Laboratory-based Acute Physiology Score, the odds of ICU admission were not significantly different for patients with high (adjusted odds ratio [OR] 0.99, 95% confidence interval [CI] 0.78 to 1.23) or moderate (adjusted OR 0.97, 95% CI 0.86 to 1.09) frailty risk compared to those with low frailty risk. Among patients admitted to the ICU, 75 (75.0%) of those with high frailty risk died, compared to 317 (56.0%) of those with moderate risk and 416 (52.7%) of those with low risk. After multivariable adjustment, the risk of death after ICU admission was higher for patients with high frailty risk than for those with low frailty risk (adjusted OR 2.86, 95% CI 1.77 to 4.77). Interpretation: Among patients readmitted to hospital within 12 months, patients with high frailty risk were similarly likely as those with lower frailty risk to be admitted to the ICU but were more likely to die if admitted to ICU. The HFRS at hospital discharge can inform prognosis, which can help guide discussions for preferences for ICU care during future hospital stays. [ABSTRACT FROM AUTHOR]

Background: Functional decline is common following acute hospitalization and is associated with hospital readmission, institutionalization, and mortality. People with functional decline may have difficulty accessing post-discharge medical care, even though early physician follow-up has the potential to prevent poor outcomes and is integral to high-quality transitional care. We sought to determine whether recent functional decline was associated with lower rates of post-discharge physician follow-up, and whether this association changed during the COVID-19 pandemic, given that both functional decline and COVID-19 may affect access to post-discharge care. Method: We conducted a retrospective cohort study using health administrative data from Ontario, Canada. We included patients over 65 who were discharged from an acute care facility during March 1st, 2019 – January 31st, 2020 (pre-COVID-19 period), and March 1st, 2020 – January 31st, 2021 (COVID-19 period), and who were assessed for home care while in hospital. Patients with and without functional decline were compared. Our primary outcome was any physician follow-up visit within 7 days of discharge. We used propensity score weighting to compare outcomes between those with and without functional decline. Results: Our study included 21,771 (pre-COVID) and 17,248 (COVID) hospitalized patients, of whom 15,637 (71.8%) and 12,965 (75.2%) had recent functional decline. Pre-COVID, there was no difference in physician follow-up within 7 days of discharge (Functional decline 45.0% vs. No functional decline 44.0%; RR = 1.02, 95% CI 0.98–1.06). These results did not change in the COVID-19 period (Functional decline 51.1% vs. No functional decline 49.4%; RR = 1.03, 95% CI 0.99–1.08, Z-test for interaction p = 0.72). In the COVID-19 cohort, functional decline was associated with having a 7-day physician virtual visit (RR 1.15; 95% CI 1.08–1.24) and a 7-day physician home visit (RR 1.64; 95% CI 1.10–2.43). Conclusions: Functional decline was not associated with reduced 7-day post-discharge physician follow-up in either the pre-COVID-19 or COVID-19 periods. In the COVID-19 period, functional decline was positively associated with 7-day virtual and home-visit follow-up. [ABSTRACT FROM AUTHOR]

Introduction: The aim of our study was to assess the initial impact of COVID-19 on total publicly-funded direct healthcare costs and health services use in two Canadian provinces, Ontario and British Columbia (BC). Methods: This retrospective repeated cross-sectional study used population-based administrative datasets, linked within each province, from January 1, 2018 to December 27, 2020. Interrupted time series analysis was used to estimate changes in the level and trends of weekly resource use and costs, with March 16–22, 2020 as the first pandemic week. Also, in each week of 2020, we identified cases with their first positive SARS-CoV-2 test and estimated their healthcare costs until death or December 27, 2020. Results: The resources with the largest level declines (95% confidence interval) in use in the first pandemic week compared to the previous week were physician services [Ontario: -43% (-49%,-37%); BC: -24% (-30%,-19%) (both p<0.001)] and emergency department visits [Ontario: -41% (-47%,-35%); BC: -29% (-35%,-23%) (both p<0.001)]. Hospital admissions declined by 27% (-32%,-23%) in Ontario and 21% (-26%,-16%) in BC (both p<0.001). Resource use subsequently rose but did not return to pre-pandemic levels. Only home care and dialysis clinic visits did not significantly decrease compared to pre-pandemic. Costs for COVID-19 cases represented 1.3% and 0.7% of total direct healthcare costs in 2020 in Ontario and BC, respectively. Conclusions: Reduced utilization of healthcare services in the overall population outweighed utilization by COVID-19 patients in 2020. Meeting the needs of all patients across all services is essential to maintain resilient healthcare systems. [ABSTRACT FROM AUTHOR]

Background: Variability in antimicrobial prescribing may indicate an opportunity for improvement in antimicrobial use. We sought to measure physician-level antimicrobial prescribing in adult general medical wards, assess the contribution of patient-level factors to antimicrobial prescribing and evaluate the association between antimicrobial prescribing and clinical outcomes. Methods: Using the General Medicine Inpatient Initiative (GEMINI) database, we conducted a retrospective cohort study of physician-level volume and spectrum of antimicrobial prescribing in adult general medical wards in 4 academic teaching hospitals in Toronto, Ontario, between April 2010 and December 2019. We stratified physicians into quartiles by hospital site based on volume of antimicrobial prescribing (days of therapy per 100 patient-days and antimicrobial-free days) and antibacterial spectrum (modified spectrum score). The modified spectrum score assigns a value to each antibacterial agent based on the breadth of coverage. We assessed patient-level differences among physician quartiles using age, sex, Laboratory-based Acute Physiology Score, discharge diagnosis and Charlson Comorbidity Index. We evaluated the association of clinical outcomes (in-hospital 30-day mortality, length of stay, intensive care unit [ICU] transfer and hospital readmission) with antimicrobial volume and spectrum using multilevel modelling. Results: The cohort consisted of 124 physicians responsible for 124 158 hospital admissions. The median physician-level volume of antimicrobial prescribing was 56.1 (interquartile range 51.7–67.5) days of therapy per 100 patient-days. We did not find any differences in baseline patient characteristics by physician prescribing quartile. The difference in mean prescribing between quartile 4 and quartile 1 was 15.8 days of therapy per 100 patient-days (95% confidence interval [CI] 9.6–22.0), representing 30% higher antimicrobial prescribing in the fourth quartile than the first quartile. Patient in-hospital deaths, length of stay, ICU transfer and hospital readmission did not differ by physician quartile. In-hospital mortality was higher among patients cared for by prescribers with higher modified spectrum scores (odds ratio 1.13, 95% CI 1.04–1.24). Interpretation: We found that physician-level variability in antimicrobial prescribing was not associated with differences in patient characteristics or outcomes in academic general medicine wards. These findings provide support for considering the lowest quartile of physician antimicrobial prescribing within each hospital as a target for antimicrobial stewardship. [ABSTRACT FROM AUTHOR]

Background: Little is known about the association between the COVID-19 pandemic and early survival among newly diagnosed cancer patients. Methods: This retrospective population-based cohort study used linked administrative datasets from Ontario, Canada. Adults (=18 years) who received a cancer diagnosis between March 15 and December 31, 2020, were included in a pandemic cohort, while those diagnosed during the same dates in 2018/2019 were included in a pre-pandemic cohort. All patients were followed for one full year after the date of diagnosis. Cox proportional hazards regression models were used to assess survival in relation to the pandemic, patient characteristics at diagnosis, and the modality of first cancer treatment as a time-varying covariate. Interaction terms were explored to measure the pandemic association with survival for each cancer type. Results: Among 179,746 patients, 53,387 (29.7%) were in the pandemic cohort and 37,741 (21.0%) died over the first post-diagnosis year. No association between the pandemic and survival was found when adjusting for patient characteristics at diagnosis (HR 0.99 [95% CI 0.96-1.01]), while marginally better survival was found for the pandemic cohort when the modality of treatment was additionally considered (HR 0.97 [95% CI 0.95-0.99]). When examining each cancer type, only a new melanoma diagnosis was associated with a worse survival in the pandemic cohort (HR 1.25 [95% CI 1.05-1.49]). Conclusions: Among patients able to receive a cancer diagnosis during the pandemic, one-year overall survival was not different than those diagnosed in the previous 2 years. This study highlights the complex nature of the COVID-19 pandemic impact on cancer care. [ABSTRACT FROM AUTHOR]

Background: Physician home visits are essential for populations who cannot easily access office-based primary care. The objective of this study was to describe the characteristics, practice patterns and physician-level patient characteristics of Ontario physicians who provide home visits. Methods: This was a retrospective cross-sectional study, based on health administrative data, of Ontario physicians who provided home visits and their patients, between Jan. 1, 2019, and Dec. 31, 2019. We selected family physicians who had at least 1 home visit in 2019. Physician demographic characteristics, practice patterns and aggregated patient characteristics were compared between high-volume home visit physicians (the top 5%) and low-volume home visit physicians (bottom 95%). Results: A total of 6572 family physicians had at least 1 home visit in 2019. The top 5% of home visit physicians (n = 330) performed 58.6% of all home visits (n = 227 321 out of 387 139). Compared with low-volume home visit physicians (n = 6242), the top 5% were more likely to be male and practise in large urban areas, and rarely saw patients who were enrolled to them (median 4% v. 87.5%, standardized mean difference 1.12). High-volume physicians' home visit patients were younger, had greater levels of health care resource utilization, resided in lower-income and large urban neighbourhoods, and were less likely to have a medical home. Interpretation: A small subset of home visit physicians provided a large proportion of home visits in Ontario. These home visits may be addressing a gap in access to primary care for certain patients, but could be contributing to lower continuity of care. [ABSTRACT FROM AUTHOR]

The article presents the discussion on COVID-19 illness and hospitalization being more common among older adults. Topics include CDC by jurisdictions, pharmacies, and federal entities through immunization information systems (IISs); and tests for statistical significance being notconducted due to the data reflecting the U.S. population not based on population samples.

Background: Imaging procedures are commonly performed on hospitalized patients and waiting for these could increase length-of-stay. The study objective was to quantify delays for imaging procedures in General Internal Medicine and identify contributing patient, physician, and system factors. Methods: This was a retrospective cohort study of medical inpatients admitted to 5 hospitals in Toronto, Ontario (2010–2019), with at least one imaging procedure (CT, MRI, ultrasound, or peripherally-inserted central catheter [PICC] insertion). The primary outcome was time-to-test, and the secondary outcome was acute length-of-stay after test ordering. Results: The study cohort included 73,107 hospitalizations. Time-to-test was longest for MRI (median 22 hours) and shortest for CT (median 7 hours). The greatest contributors to time-to-test were system factors such as hospital site (up to 22 additional hours), location of test ordering (up to 10 additional hours), the timing of test ordering relative to admission (up to 13 additional hours), and ordering during weekends (up to 21 additional hours). Older patient age, having more comorbidities, and residence in a low-income neighborhood were also associated with testing delays. Each additional hour spent waiting for a test was associated with increased acute length-of-stay after test ordering, ranging from 0.4 additional hours for CT to 1.2 hours for MRI. Conclusions: The greatest contributors to testing delays relate to when and where a test was ordered. Wait times affect length-of-stay and the quality of patient care. Hospitals can apply our novel approach to explore opportunities to decrease testing delays locally. [ABSTRACT FROM AUTHOR]

Approximately 20% of patients who are discharged from hospital for an acute exacerbation of COPD (AECOPD) are readmitted within 30 days. To reduce this, it is important both to identify all individuals admitted with AECOPD and to predict those who are at higher risk for readmission. To develop two clinical prediction models using data available in electronic medical records: 1) identifying patients admitted with AECOPD and 2) predicting 30-day readmission in patients discharged after AECOPD. Two datasets were created using all admissions to General Internal Medicine from 2012 to 2018 at two hospitals: one cohort to identify AECOPD and a second cohort to predict 30-day readmissions. We fit and internally validated models with four algorithms. Of the 64,609 admissions, 3,620 (5.6%) were diagnosed with an AECOPD. Of those discharged, 518 (15.4%) had a readmission to hospital within 30 days. For identification of patients with a diagnosis of an AECOPD, the top-performing models were LASSO and a four-variable regression model that consisted of specific medications ordered within the first 72 hours of admission. For 30-day readmission prediction, a two-variable regression model was the top performing model consisting of number of COPD admissions in the previous year and the number of non-COPD admissions in the previous year. We generated clinical prediction models to identify AECOPDs during hospitalization and to predict 30-day readmissions after an acute exacerbation from a dataset derived from available EMR data. Further work is needed to improve and externally validate these models. [ABSTRACT FROM AUTHOR]

In this narrative review, we describe what is known about non-pharmacological and pharmacological treatments for insomnia in medical inpatients, with a focus on melatonin. Hospital-acquired insomnia is common, resulting in shortened total sleep time and more nighttime awakenings. Sleep disturbance has been shown to increase systemic inflammation, pain, and the likelihood of developing delirium in hospital. Treatment for insomnia includes both non-pharmacological and pharmacological interventions, the latter of which requires careful consideration of risks and benefits given the known adverse effects. Though benzodiazepines and non-benzodiazepine benzodiazepine receptor agonists are commonly prescribed (i.e., sedative-hypnotics), they are relatively contraindicated for patients over the age of 65 due to the risk of increased falls, cognitive decline, and potential for withdrawal symptoms after long-term use. Exogenous melatonin has a comparatively low likelihood of adverse effects and drug–drug interactions and is at least as effective as other sedative-hypnotics. Though more research is needed on both its effectiveness and relative safety for inpatients, small doses of melatonin before bedtime may be an appropriate choice for inpatients when insomnia persists despite non-pharmacological interventions. [ABSTRACT FROM AUTHOR]

Objectives: In summer 2021, the number of COVID-19–associated hospitalizations in the United States increased with the surge of the SARS-CoV-2 Delta variant. We assessed how COVID-19 vaccine initiation and dose completion changed during the Delta variant surge, based on jurisdictional vaccination coverage before the surge. Methods: We analyzed COVID-19 vaccination data reported to the Centers for Disease Control and Prevention. We classified jurisdictions (50 states and the District of Columbia) into quartiles ranging from high to low first-dose vaccination coverage among people aged ≥12 years as of June 30, 2021. We calculated first-dose vaccination coverage as of June 30 and October 31, 2021, and stratified coverage by quartile, age (12-17, 18-64, ≥65 years), and sex. We assessed dose completion among those who initiated a 2-dose vaccine series. Results: Of 51 jurisdictions, 15 reached at least 70% vaccination coverage before the Delta variant surge (ie, as of June 30, 2021), while 35 reached that goal as of October 31, 2021. Jurisdictions in the lowest quartile of vaccination coverage (44.9%-54.9%) had the greatest absolute (9.7%-17.9%) and relative (18.1%-39.8%) percentage increase in vaccination coverage during July 1–October 31, 2021. Of those who received the first dose during this period across all jurisdictions, nearly 1 in 5 missed the second dose. Conclusions: Although COVID-19 vaccination initiation increased during July 1–October 31, 2021, in jurisdictions in the lowest quartile of vaccination coverage, coverage remained below that of jurisdictions in the highest quartile of vaccination coverage before the Delta variant surge. Efforts are needed to improve access to and increase confidence in COVID-19 vaccines, especially in low-coverage areas. [ABSTRACT FROM AUTHOR]

Due to the ramping down of cancer surgery in early pandemic, many newly diagnosed patients received other treatments first. We aimed to quantify the pandemic-related shift in rate of surgery following chemotherapy. This is a retrospective population-based cohort study involving adults diagnosed with cancer between 3 January 2016 and 7 November 2020 in Ontario, Canada who received chemotherapy as first treatment within 6-months of diagnosis. Competing-risks regression models with interaction effects were used to quantify the association between COVID-19 period (receiving a cancer diagnosis before or on/after 15 March 2020) and receipt of surgical reSection 9-months after first chemotherapy. Among 51,653 patients, 8.5% (n = 19,558) of them ultimately underwent surgery 9-months after chemotherapy initiation. Receipt of surgery was higher during the pandemic than before (sHR 1.07, 95% CI 1.02–1.13). Material deprivation was independently associated with lower receipt of surgery (least vs. most deprived quintile: sHR 1.11, 95% CI 1.04–1.17), but did not change with the pandemic. The surgical rate increase was most pronounced for breast cancer (sHR 1.13, 95% CI 1.06–1.20). These pandemic-related shifts in cancer treatment requires further evaluations to understand the long-term consequences. Persistent material deprivation-related inequity in cancer surgical access needs to be addressed. [ABSTRACT FROM AUTHOR]

A tree model identified adults age ≤34 years, Johnson & Johnson primary series recipients, people from racial/ethnic minority groups, residents of nonlarge metro areas, and those living in socially vulnerable communities in the South as less likely to be boosted. These findings can guide clinical/public health outreach toward specific subpopulations. [ABSTRACT FROM AUTHOR]

To identify demographic factors associated with delaying or not receiving a second dose of the 2-dose primary mRNA COVID-19 vaccine series, we matched 323 million single Pfizer-BioNTech (https://www.pfizer.com) and Moderna (https://www.modernatx.com) COVID-19 vaccine administration records from 2021 and determined whether second doses were delayed or missed. We used 2 sets of logistic regression models to examine associated factors. Overall, 87.3% of recipients received a timely second dose (≤42 days between first and second dose), 3.4% received a delayed second dose (>42 days between first and second dose), and 9.4% missed the second dose. Persons more likely to have delayed or missed the second dose belonged to several racial/ethnic minority groups, were 18-39 years of age, lived in more socially vulnerable areas, and lived in regions other than the northeastern United States. Logistic regression models identified specific subgroups for providing outreach and encouragement to receive subsequent doses on time. [ABSTRACT FROM AUTHOR]

Background: It is unknown how much of current physician home visit volume is driven by low-complexity or low-continuity visits. Our objectives were to measure physician home visit volumes and costs in Ontario from 2005/06 to 2018/19, and to compare patient characteristics and postvisit use of health care services across home visit types. Methods: This was a retrospective cross-sectional study using health administrative data. We examined annual physician home visit volumes and costs from 2005/06 to 2018/19 in Ontario, and characteristics and postvisit use of health care services of residents who received at least 1 home visit from any physician in 2014/15 to 2018/19. We categorized home visits as palliative, provided to a patient who also received home care services or "other," and compared characteristics and outcomes between groups. Results: A total of 4 418 334 physician home visits were performed between 2005/06 and 2018/19. More than half (2 256 667 [51.1%]) were classified as "other" and accounted for 39.1% ($22 million) of total annual physician billing costs. From 2014/15 to 2018/19, of the 413 057 home visit patients, 240 933 (58.3%) were adults aged 65 or more, and 323 283 (78.3%) lived in large urban areas. Compared to the palliative care and home care groups, the "other" group was younger, had fewer comorbidities, and had lower rates of emergency department visits and hospital admissions in the 30 days after the visit. Interpretation: About half of physician home visits in 2014/15 to 2018/19 were to patients who were receiving neither palliative care nor home care, a group that was younger and healthier, and had low use of health care services after the visit. There is an opportunity to refine policy tools to target patients most likely to benefit from physician home visits. [ABSTRACT FROM AUTHOR]

We analyzed first-dose Coronavirus disease vaccination coverage among US children 5-11 years of age during November-December 2021. Pediatric vaccination coverage varied widely by jurisdiction, age group, and race/ethnicity, and lagged behind vaccination coverage for adolescents aged 12-15 years during the first 2 months of vaccine rollout. [ABSTRACT FROM AUTHOR]

Higher COVID-19 incidence and mortality rates in rural than in urban areas are well documented (1). These disparities persisted during the B.1.617.2 (Delta) and B.1.1.529 (Omicron) variant surges during late 2021 and early 2022 (1,2). Rural populations tend to be older (aged ≥65 years) and uninsured and are more likely to have underlying medical conditions and live farther from facilities that provide tertiary medical care, placing them at higher risk for adverse COVID-19 outcomes (2). To better understand COVID-19 vaccination disparities between urban and rural populations, CDC analyzed county-level vaccine administration data among persons aged ≥5 years who received their first dose of either the BNT162b2 (Pfizer-BioNTech) or mRNA-1273 (Moderna) COVID-19 vaccine or a single dose of the Ad.26.COV2.S (Janssen [Johnson & Johnson]) COVID-19 vaccine during December 14, 2020-January 31, 2022, in 50 states and the District of Columbia (DC). COVID-19 vaccination coverage with ≥1 doses in rural areas (58.5%) was lower than that in urban counties (75.4%) overall, with similar patterns across age groups and sex. Coverage with ≥1 doses varied among states: 46 states had higher coverage in urban than in rural counties, one had higher coverage in rural than in urban counties. Three states and DC had no rural counties; thus, urban-rural differences could not be assessed. COVID-19 vaccine primary series completion was higher in urban than in rural counties. However, receipt of booster or additional doses among primary series recipients was similarly low between urban and rural counties. Compared with estimates from a previous study of vaccine coverage among adults aged ≥18 years during December 14, 2020-April 10, 2021, these urban-rural disparities among those now eligible for vaccination (aged ≥5 years) have increased more than twofold through January 2022, despite increased availability and access to COVID-19 vaccines. Addressing barriers to vaccination in rural areas is critical to achieving vaccine equity, reducing disparities, and decreasing COVID-19-related illness and death in the United States (2). [ABSTRACT FROM AUTHOR]

Emergency department (ED) use is a concern for surgery patients, physicians and health administrators particularly during a pandemic. The objective of this study was to assess the impact of the pandemic on ED use following cancer-directed surgeries. This is a retrospective cohort study of patients undergoing cancer-directed surgeries comparing ED use from 7 January 2018 to 14 March 2020 (pre-pandemic) and 15 March 2020 to 27 June 2020 (pandemic) in Ontario, Canada. Logistic regression models were used to (1) determine the association between pandemic vs. pre-pandemic periods and the odds of an ED visit within 30 days after discharge from hospital for surgery and (2) to assess the odds of an ED visit being of high acuity (level 1 and 2 as per the Canadian Triage and Acuity Scale). Of our cohort of 499,008 cancer-directed surgeries, 468,879 occurred during the pre-pandemic period and 30,129 occurred during the pandemic period. Even though there was a substantial decrease in the general population ED rates, after covariate adjustment, there was no significant decrease in ED use among surgical patients (OR 1.002, 95% CI 0.957–1.048). However, the adjusted odds of an ED visit being of high acuity was 23% higher among surgeries occurring during the pandemic (OR 1.23, 95% CI 1.14–1.33). Although ED visits in the general population decreased substantially during the pandemic, the rate of ED visits did not decrease among those receiving cancer-directed surgery. Moreover, those presenting in the ED post-operatively during the pandemic had significantly higher levels of acuity. [ABSTRACT FROM AUTHOR]

Background: Homebound status is associated with an increased risk of morbidity and mortality in older adults, yet little is known about homebound older adults in Canada. Our objectives were to describe time trends in the prevalence of homebound status among community‐dwelling long‐term home care recipients and the characteristics associated with homebound status. Methods: This was a retrospective cross‐sectional and cohort study using linked health administrative data in Canada's most populous province, Ontario. We included adults aged 65 years and older who received at least one long‐term home care assessment from 2006 to 2017 (N = 666,514). Homebound individuals were those who exited the home an average of 0–1 days/week over the previous 30 days; not homebound comparators exited the home 2–7 days per week. We compared baseline characteristics between groups and estimated the association between these characteristics and homebound status at baseline and over time. Results: From 2006 to 2017, the annual proportion of long‐term home care recipients who were homebound increased from 48% to 65%. At first assessment, 50% of the cohort (331,836 of 666,514) were homebound. Among those with a 4–12 month repeat assessment, homebound status persisted over time for 80%, and developed anew in 24%. Dependency on others for locomotion, use of an assistive device, poor access to dwelling, older age, and female sex were most strongly associated with homebound status at baseline, as well as its development and persistence over time. Conclusions: We found that half of Ontario older adult long‐stay home care clients were homebound at the time of their first assessment, and that the prevalence of homebound status among home care recipients rose steadily from 2006 to 2017. This informs further research and policy development to ensure the adequacy of supports for older homebound persons. [ABSTRACT FROM AUTHOR]

Background: Limitations in laboratory diagnostic capacity impact population surveillance of COVID-19. It is currently unknown whether participatory surveillance tools for COVID-19 correspond to government-reported case trends longitudinally and if it can be used as an adjunct to laboratory testing. The primary objective of this study was to determine whether self-reported COVID-19-like illness reflected laboratory-confirmed COVID-19 case trends in Ontario Canada. Methods: We retrospectively analyzed longitudinal self-reported symptoms data collected using an online tool–Outbreaks Near Me (ONM)–from April 20th, 2020, to March 7th, 2021 in Ontario, Canada. We measured the correlation between COVID-like illness among respondents and the weekly number of PCR-confirmed COVID-19 cases and provincial test positivity. We explored contemporaneous changes in other respiratory viruses, as well as the demographic characteristics of respondents to provide context for our findings. Results: Between 3,849–11,185 individuals responded to the symptom survey each week. No correlations were seen been self-reported CLI and either cases or test positivity. Strong positive correlations were seen between CLI and both cases and test positivity before a previously documented rise in rhinovirus/enterovirus in fall 2020. Compared to participatory surveillance respondents, a higher proportion of COVID-19 cases in Ontario consistently came from low-income, racialized and immigrant areas of the province- these groups were less well represented among survey respondents. Interpretation: Although digital surveillance systems are low-cost tools that have been useful to signal the onset of viral outbreaks, in this longitudinal comparison of self-reported COVID-like illness to Ontario COVID-19 case data we did not find this to be the case. Seasonal respiratory virus transmission and population coverage may explain this discrepancy. [ABSTRACT FROM AUTHOR]

Vaccination against SARS-CoV-2 (the virus that causes COVID-19) is highly effective at preventing hospitalization due to SARS-CoV-2 infection and booster and additional primary dose COVID-19 vaccinations increase protection (1-3). During August-November 2021, a series of Emergency Use Authorizations and recommendations, including those for an additional primary dose for immunocompromised persons and a booster dose for persons aged ≥18 years, were approved because of reduced immunogenicity in immunocompromised persons, waning vaccine effectiveness over time, and the introduction of the highly transmissible B.1.617.2 (Delta) variant (4,5). Adults aged ≥65 years are at increased risk for COVID-19-associated hospitalization and death and were one of the populations first recommended a booster dose in the U.S. (5,6). Data on COVID-19 vaccinations reported to CDC from 50 states, the District of Columbia (DC), and eight territories and freely associated states were analyzed to ascertain coverage with booster or additional primary doses among adults aged ≥65 years. During August 13-November 19, 2021, 18.7 million persons aged ≥65 years received a booster or additional primary dose of COVID-19 vaccine, constituting 44.1% of 42.5 million eligible* persons in this age group who previously completed a primary vaccination series.† Coverage was similar by sex and age group, but varied by primary series vaccine product and race and ethnicity, ranging from 30.3% among non-Hispanic American Indian or Alaska Native persons to 50.5% among non-Hispanic multiple/other race persons. Strategic efforts are needed to encourage eligible persons aged ≥18 years, especially those aged ≥65 years and those who are immunocompromised, to receive a booster and/or additional primary dose to ensure maximal protection against COVID-19. [ABSTRACT FROM AUTHOR]

Influenza causes considerable morbidity and mortality in the United States. Between 2010 and 2020, an estimated 9-41 million cases resulted in 140,000-710,000 hospitalizations and 12,000-52,000 deaths annually (1). As the United States enters the 2021-22 influenza season, the potential impact of influenza illnesses is of concern given that influenza season will again coincide with the ongoing COVID-19 pandemic, which could further strain overburdened health care systems. The Advisory Committee on Immunization Practices (ACIP) recommends routine annual influenza vaccination for the 2021-22 influenza season for all persons aged ≥6 months who have no contraindications (2). To assess the potential impact of the COVID-19 pandemic on influenza vaccination coverage, the percentage change between administration of at least 1 dose of influenza vaccine during September-December 2020 was compared with the average administered in the corresponding periods in 2018 and 2019. The data analyzed were reported from 11 U.S. jurisdictions with high-performing state immunization information systems.* Overall, influenza vaccine administration was 9.0% higher in 2020 compared with the average in 2018 and 2019, combined. However, in 2020, the number of influenza vaccine doses administered to children aged 6-23 months and children aged 2-4 years, was 13.9% and 11.9% lower, respectively than the average for each age group in 2018 and 2019. Strategic efforts are needed to ensure high influenza vaccination coverage among all age groups, especially children aged 6 months-4 years who are not yet eligible to receive a COVID-19 vaccine. Administration of influenza vaccine and a COVID-19 vaccine among eligible populations is especially important to reduce the potential strain that influenza and COVID-19 cases could place on health care systems already overburdened by COVID-19. [ABSTRACT FROM AUTHOR]

Clinicians should be aware of the potential for the pharmacologic activity of SGLT2 inhibitors to persist long after the standard drug clearance period of five half‐lives, the typical duration used to guide pre‐operative medication recommendations. [ABSTRACT FROM AUTHOR]

Although severe COVID-19 illness and hospitalization are more common among adults, these outcomes can occur in adolescents (1). Nearly one third of adolescents aged 12-17 years hospitalized with COVID-19 during March 2020-April 2021 required intensive care, and 5% of those hospitalized required endotracheal intubation and mechanical ventilation (2). On December 11, 2020, the Food and Drug Administration (FDA) issued Emergency Use Authorization (EUA) of the Pfizer-BioNTech COVID-19 vaccine for adolescents aged 16-17 years; on May 10, 2021, the EUA was expanded to include adolescents aged 12-15 years; and on August 23, 2021, FDA granted approval of the vaccine for persons aged ≥16 years. To assess progress in adolescent COVID-19 vaccination in the United States, CDC assessed coverage with ≥1 dose* and completion of the 2-dose vaccination series† among adolescents aged 12-17 years using vaccine administration data for 49 U.S. states (all except Idaho) and the District of Columbia (DC) during December 14, 2020-July 31, 2021. As of July 31, 2021, COVID-19 vaccination coverage among U.S. adolescents aged 12-17 years was 42.4% for ≥1 dose and 31.9% for series completion. Vaccination coverage with ≥1 dose varied by state (range = 20.2% [Mississippi] to 70.1% [Vermont]) and for series completion (range = 10.7% [Mississippi] to 60.3% [Vermont]). By age group, 36.0%, 40.9%, and 50.6% of adolescents aged 12-13, 14-15, and 16-17 years, respectively, received ≥1 dose; 25.4%, 30.5%, and 40.3%, respectively, completed the vaccine series. Improving vaccination coverage and implementing COVID-19 prevention strategies are crucial to reduce COVID-19-associated morbidity and mortality among adolescents and to facilitate safer reopening of schools for in-person learning. [ABSTRACT FROM AUTHOR]

Summary: Background: Liver disease is an increasing burden on population health globally. Aims: To characterise burden of liver disease among general internal medicine inpatients at seven Toronto‐area hospitals and compare it to other common medical conditions. Methods: Data from April 2010 to October 2017 were obtained from hospitals participating in the GEMINI collaborative. Using these cohort data from hospital information systems linked to administrative data, we defined liver disease admissions using most responsible discharge diagnoses categorised according to international classification of diseases, 10th Revision—enhanced Canadian version (ICD‐10‐CA). We identified admissions for heart failure, chronic obstructive pulmonary disease (COPD) and pneumonia as comparators. We calculated standardised mortality ratios (SMRs) as the ratio of observed to expected deaths. Results: Among 239 018 discharges, liver disease accounted for 1.7% of most responsible discharge diagnoses. Liver disease was associated with marked premature mortality, with SMR of 8.84 (95% CI 8.06‐9.67) compared to 1.06 (95% CI 0.99‐1.12) for heart failure, 1.05 (95% CI 0.96‐1.15) for COPD and 1.28 (95% CI 1.20‐1.37) for pneumonia. The majority of deaths were among patients younger than 65 years (57.7%) compared to 3.3% in heart failure, 5.6% in COPD and 10.7% in pneumonia. Liver disease patients presented with worse Laboratory‐Based Acute Physiology Scores, were more frequently admitted to the intensive care unit (14.4%), incurred higher average total costs (median $6723 CAD), had higher in‐hospital mortality (11.4%), and were more likely to be a readmission from 30 days prior (19.8%). Non‐alcoholic fatty liver disease admissions increased from 120 in 2011‐2012 to 215 in 2016‐2017 (P < 0.01). Conclusion: In Canada's largest urban centre, liver disease admissions resulted in premature morbidity and mortality with higher resource use compared to common cardio‐respiratory conditions. Re‐evaluation of approaches to caring for inpatients with liver disease is timely and justified. [ABSTRACT FROM AUTHOR]

This prospective study of internal medicine inpatients treated at 2 hospitals in Toronto, Canada, between September 1, 2016, and September 1, 2017, compared patient-report, physician-report, and detailed medical record review to identify specific hospital-acquired complications. Six complications were assessed: delirium, catheter-associated urinary tract infection, acute kidney injury, deep vein thrombosis/pulmonary embolism, hospital-acquired pneumonia, or fall. The study included 207 patients and physician responses were obtained for 156 (75%). Complications were identified in 28 (14%) patients by medical record review, 30 (14%) patients by patient-report, and 11 (7%) patients by physician-report. Fifty-four (26%) patients experienced a complication as identified through at least one of the 3 methods. There was little agreement between the 3 methods (Fleiss' ĸ 0.15, P < 0.001). All 3 sources agreed on the occurrence of a specific complication in only 1 patient (1%). Multiple approaches likely are needed to adequately measure hospital-acquired complications. [ABSTRACT FROM AUTHOR]

Background & aims: Viral hepatitis C represents a major global burden, particularly among immigrant‐receiving countries such as Canada, where knowledge of disparities in hepatitis C virus among immigrant groups for micro‐elimination efforts is lacking. We quantify the hepatitis C cascades of care among immigrants and long‐term residents prior to the introduction of direct‐acting antiviral medications. Methods: Using laboratory and health administrative records, we described the hepatitis C virus cascades of care in terms of diagnosis, engagement with care, treatment initiation, and clearance in Ontario, Canada (1997‐2014). We stratified the cascade by immigrant and long‐term resident groups and identify drivers at each stage using multivariable Poisson regression. Results: We included 940 245 individuals in the study with an estimated hepatitis C prevalence of 167 923 (1.4%) overall, 23 759 (0.7%) among all immigrants, and 6019 (1.1%) among immigrants from hepatitis C endemic countries. Overall there were 104 616 individuals with reactive antibody results, 73 861 tested for viral RNA, 52 388 with viral RNA detected, 50 805 genotyped, 13 159 on treatment and 3919 with evidence of viral clearance. Compared to long‐term residents, immigrants showed increased nucleic‐acid testing (aRR: 1.09 [95%CI: 1.08, 1.10]), treatment initiation (aRR: 1.46 [95%CI: 1.38, 1.54]), and higher clearance rates (aRR: 1.07 [95%CI: 1.03, 1.11]). Conclusions: Hepatitis C virus is more prevalent among long‐term residents compared to immigrants overall, however, immigrants from endemic countries are an important subgroup to consider for future screening and linkage to care initiatives. These findings are prior to the introduction of newer medications and provide a population‐based benchmark for follow‐up studies and evaluation of treatment programs and surveillance activities. [ABSTRACT FROM AUTHOR]

Background: Health care funding reforms are being used worldwide to improve system performance but may invoke unintended consequences. We assessed the effects of introducing a targeted hospital funding model, based on fixed price and volume, for hip fractures. We hypothesized the policy change was associated with reduction in wait times for hip fracture surgery, increase in wait times for non-hip fracture surgery, and increase in the incidence of after-hours hip fracture surgery.Methods: This was a population-based, interrupted time series analysis of 49,097 surgeries for hip fractures, 10,474 for ankle fractures, 1,594 for tibial plateau fractures, and 40,898 for appendectomy at all hospitals in Ontario, Canada between April 2012 and March 2017. We used segmented regression analysis of interrupted monthly time series data to evaluate the impact of funding reform enacted April 1, 2014 on wait time for hip fracture repair (from hospital presentation to surgery) and after-hours provision of surgery (occurring between 1700 and 0700 h). To assess potential adverse consequences of the reform, we also evaluated two control procedures, ankle and tibial plateau fracture surgery. Appendectomy served as a non-orthopedic tracer for assessment of secular trends.Results: The difference (95 % confidence interval) between the actual mean wait time and the predicted rate had the policy change not occurred was - 0.46 h (-3.94 h, 3.03 h) for hip fractures, 1.46 h (-3.58 h, 6.50 h) for ankle fractures, -3.22 h (-39.39 h, 32.95 h) for tibial plateau fractures, and 0.33 h (-0.57 h, 1.24 h) for appendectomy (Figure 1; Table 3). The difference (95 % confidence interval) between the actual and predicted percentage of surgeries performed after-hours - 0.90 % (-3.91 %, 2.11 %) for hip fractures, -3.54 % (-11.25 %, 4.16 %) for ankle fractures, 7.09 % (-7.97 %, 22.14 %) for tibial plateau fractures, and 1.07 % (-2.45 %, 4.59 %) for appendectomy.Conclusions: We found no significant effects of a targeted hospital funding model based on fixed price and volume on wait times or the provision of after-hours surgery. Other approaches for improving hip fracture wait times may be worth pursuing instead of funding reform. [ABSTRACT FROM AUTHOR]

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Drug shortages during a pandemic can result from sudden increases in demand and disruptions in supply chains. Age-stratified hospital admissions in Canada were reported by the Government of Canada, based on cases reported to the Public Health Agency of Canada to Feb. 18, 2021.[18] Age-stratified hospital admissions in the United States were reported by the COVID-19-Associated Hospitalization Surveillance Network (COVID-NET)[17] to Feb. 13, 2021, which represents about 10% of the US population. Tocilizumab is a life-saving therapy for adults admitted to hospital with COVID-19; demand for this drug is likely to outstrip available supply in Canada. [Extracted from the article]

Approximately 60 million persons in the United States live in rural counties, representing almost one fifth (19.3%) of the population.* In September 2020, COVID-19 incidence (cases per 100,000 population) in rural counties surpassed that in urban counties (1). Rural communities often have a higher proportion of residents who lack health insurance, live with comorbidities or disabilities, are aged ≥65 years, and have limited access to health care facilities with intensive care capabilities, which places these residents at increased risk for COVID-19-associated morbidity and mortality (2,3). To better understand COVID-19 vaccination disparities across the urban-rural continuum, CDC analyzed county-level vaccine administration data among adults aged ≥18 years who received their first dose of either the Pfizer-BioNTech or Moderna COVID-19 vaccine, or a single dose of the Janssen COVID-19 vaccine (Johnson & Johnson) during December 14, 2020-April 10, 2021 in 50 U.S. jurisdictions (49 states and the District of Columbia [DC]). Adult COVID-19 vaccination coverage was lower in rural counties (38.9%) than in urban counties (45.7%) overall and among adults aged 18-64 years (29.1% rural, 37.7% urban), those aged ≥65 years (67.6% rural, 76.1% urban), women (41.7% rural, 48.4% urban), and men (35.3% rural, 41.9% urban). Vaccination coverage varied among jurisdictions: 36 jurisdictions had higher coverage in urban counties, five had higher coverage in rural counties, and five had similar coverage (i.e., within 1%) in urban and rural counties; in four jurisdictions with no rural counties, the urban-rural comparison could not be assessed. A larger proportion of persons in the most rural counties (14.6%) traveled for vaccination to nonadjacent counties (i.e., farther from their county of residence) compared with persons in the most urban counties (10.3%). As availability of COVID-19 vaccines expands, public health practitioners should continue collaborating with health care providers, pharmacies, employers, faith leaders, and other community partners to identify and address barriers to COVID-19 vaccination in rural areas (2). [ABSTRACT FROM AUTHOR]

Background: Acute inpatient hospital admissions account for more than half of all health care costs related to diabetes. We sought to identify the most common and costly conditions leading to hospital admission among patients with diabetes compared with patients without diabetes. Methods: We used data from the General Internal Medicine Inpatient Initiative (GEMINI) study, a retrospective cohort study, of all patients admitted to a general internal medicine service at 7 Toronto hospitals between 2010 and 2015. The Canadian Institute for Health Information (CIHI) Most Responsible Diagnosis code was used to identify the 10 most frequent reasons for admission in patients with diabetes. Cost of hospital admission was estimated using the CIHI Resource Intensity Weight. Comparisons were made between patients with or without diabetes using the Pearson χ2 test for frequency and distribution-free confidence intervals (CIs) for median cost. Results: Among the 150 499 hospital admissions in our study, 41 934 (27.8%) involved patients with diabetes. Compared with patients without diabetes, hospital admissions because of soft tissue and bone infections were most frequent (2.5% v. 1.9%; prevalence ratio [PR] 1.28, 95% CI 1.19–1.37) and costly (Can$8794 v. Can$5845; cost ratio [CR] 1.50, 95% CI 1.37–1.65) among patients with diabetes. This was followed by urinary tract infections (PR 1.16, 95% CI 1.11–1.22; CR 1.23, 95% CI 1.17–1.29), stroke (PR 1.13, 95% CI 1.07–1.19; CR 1.19, 95% CI 1.14–1.25) and electrolyte disorders (PR 1.11, 95% CI 1.03–1.20; CR 1.20, 95% CI 1.08–1.34). Interpretation: Soft tissue and bone infections, urinary tract infections, stroke and electrolyte disorders are associated with a greater frequency and cost of hospital admissions in patients with diabetes than in those without diabetes. Preventive strategies focused on reducing hospital admissions secondary to these disorders may be beneficial in patients with diabetes. [ABSTRACT FROM AUTHOR]