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Liu et al discuss the COVID-19 in long-term care homes in Ontario and British Columbia. Many more residents living in Ontario long-term care homes have died from coronavirus disease 2019 (COVID-19) than in British Columbia. Before the pandemic, the long-term care system in British Columbia exhibited a number of potential strengths relevant to pandemic preparedness compared with Ontario: there was better coordination between long-term care, public health and hospitals; greater funding of long-term care; more care hours for residents; fewer shared rooms; more nonprofit facility ownership; and more comprehensive inspections. During the first wave of the pandemic, British Columbia was faster than Ontario in responding to COVID-19, with actions to address public health support, staffing, and infection prevention and control.

The use of opioids for noncancer pain is widespread, and more than 16,000 die of opioid-related causes in the United States annually. The patients at greatest risk of death are those receiving high doses of opioids. Whether sex influences the risk of dose escalation or opioid-related mortality is unknown. We conducted a cohort study using healthcare records of 32,499 individuals aged 15 to 64 who commenced chronic opioid therapy for noncancer pain between April 1, 1997 and December 31, 2010 in Ontario, Canada. Patients were followed from their first opioid prescription until discontinuation of therapy, death from any cause or the end of the study period. Among patients receiving chronic opioid therapy, 589 (1.8%) escalated to high dose therapy and n = 59 (0.2%) died of opioid-related causes while on treatment. After multivariable adjustment, men were more likely than women to escalate to high-dose opioid therapy (adjusted hazard ratio 1.44; 95% confidence interval 1.21 to 1.70) and twice as likely to die of opioid-related causes (adjusted hazard ratio 2.04; 95% confidence interval 1.18 to 3.53). These associations were maintained in a secondary analysis of 285,520 individuals receiving any opioid regardless of the duration of therapy. Men are at higher risk than women for escalation to high-dose opioid therapy and death from opioid-related causes. Both outcomes were more common than anticipated.

Dhalla and Tepper cite that Canadians are healthier than ever before, but there are still large gaps between what we know to be high-quality health care and the care that many Canadians receive. High-quality care is safe, timely, effective, efficient, equitable and patient centered. There is opportunity for improvement in all of these dimensions. Ways to improve the quality of care include expanding public funding for proven treatments, investing in primary care and embedding tools of improvement into practice. Improving care is more likely with the involvement of both front-line clinicians and patients.

There is increasing interest in collecting sociodemographic and social needs data in hospital settings to inform patient care and health equity. However, few studies have examined inpatients' views on this data collection and what should be done to address social needs. This study describes internal medicine inpatients' perspectives on the collection and use of sociodemographic and social needs information. A qualitative interpretive description methodology was used. Semi-structured interviews were conducted with 18 patients admitted to a large academic hospital in Toronto, Canada. Participants were recruited using maximum variation sampling for diverse genders, races, and those with and without social needs. Interviews were coded using a predominantly inductive approach and a thematic analysis was conducted. Patients expressed that sociodemographic and social needs data collection is important to offer actionable solutions to address their needs. Patients described a gap between their ideal care which would attend to social needs, versus the reality that hospital-based teams are faced with competing priorities and pressures that make it unfeasible to provide such care. They also believed that this data collection could facilitate more holistic, integrated care. Patients conveyed a need to have a trusting and transparent relationship with their provider to alleviate concerns surrounding bias, discrimination, and confidentiality. Lastly, they indicated that sociodemographic and social needs data could be useful to inform care, support research to inspire social change, and assist them with navigating community resources or creating in-hospital programs to address unmet social needs. While the collection of sociodemographic and social needs information in hospital settings is generally acceptable, there were varied views on whether hospital staff should intervene, as their priority is medical care. The results can inform the implementation of social data collection and interventions in hospital settings.

Readmissions to hospital are common, costly and often preventable. An easy-to-use index to quantify the risk of readmission or death after discharge from hospital would help clinicians identify patients who might benefit from more intensive post-discharge care. We sought to derive and validate an index to predict the risk of death or unplanned readmission within 30 days after discharge from hospital to the community. In a prospective cohort study, 48 patient-level and admission-level variables were collected for 4812 medical and surgical patients who were discharged to the community from 11 hospitals in Ontario. We used a split-sample design to derive and validate an index to predict the risk of death or nonelective readmission within 30 days after discharge. This index was externally validated using administrative data in a random selection of 1 000 000 Ontarians discharged from hospital between 2004 and 2008. Of the 4812 participating patients, 385 (8.0%) died or were readmitted on an unplanned basis within 30 days after discharge. Variables independently associated with this outcome (from which we derived the nmemonic “LACE”) included length of stay (“L”); acuity of the admission (“A”); comorbidity of the patient (measured with the Charlson comorbidity index score) (“C”); and emergency department use (measured as the number of visits in the six months before admission) (“E”). Scores using the LACE index ranged from 0 (2.0% expected risk of death or urgent readmission within 30 days) to 19 (43.7% expected risk). The LACE index was discriminative (C statistic 0.684) and very accurate (Hosmer–Lemeshow goodness-of-fit statistic 14.1, p = 0.59) at predicting outcome risk. The LACE index can be used to quantify risk of death or unplanned readmission within 30 days after discharge from hospital. This index can be used with both primary and administrative data. Further research is required to determine whether such quantification changes patient care or outcomes.

Acute infection with hepatitis C virus (HCV) is a cause of severe acute hepatitis. Sexual transmission of acute HCV is uncommon, but risk is accentuated in individuals who engage in receptive anal sex. In acute HCV infection, testing by polymerase chain reaction (PCR) returns positive results, but results from tests of anti-HCV antibodies are typically negative for several weeks after exposure. Some public health laboratories allow for HCV PCR testing only if the anti-HCV antibody test result is positive, which can make diagnosing acute HCV infection challenging.

Medication non-adherence frequently leads to suboptimal patient outcomes. Primary non-adherence, which occurs when a patient does not fill an initial prescription, is particularly important at the time of hospital discharge because new medications are often being prescribed to treat an illness rather than for prevention. We studied older adults consecutively discharged from a general internal medicine service at a large urban teaching hospital to determine the prevalence of primary non-adherence and identify characteristics associated with primary non-adherence. We reviewed electronic prescriptions, electronic discharge summaries and pharmacy dispensing data from April to August 2010 for drugs listed on the public formulary. Primary non-adherence was defined as failure to fill one or more new prescriptions after hospital discharge. In addition to descriptive analyses, we developed a logistical regression model to identify patient characteristics associated with primary non-adherence. There were 493 patients eligible for inclusion in our study, 232 of whom were prescribed new medications. In total, 66 (28%) exhibited primary non-adherence at 7 days after discharge and 55 (24%) at 30 days after discharge. Examples of medications to which patients were non-adherent included antibiotics, drugs for the management of coronary artery disease (e.g. beta-blockers, statins), heart failure (e.g. beta-blockers, angiotensin converting enzyme inhibitors, furosemide), stroke (e.g. statins, clopidogrel), diabetes (e.g. insulin), and chronic obstructive pulmonary disease (e.g. long-acting bronchodilators, prednisone). Discharge to a nursing home was associated with an increased risk of primary non-adherence (OR 2.25, 95% CI 1.01-4.95). Primary non-adherence after medications are newly prescribed during a hospitalization is common, and was more likely to occur in patients discharged to a nursing home.

Many patients do not adhere to treatment because they cannot afford their prescription medications, putting them at increased risk of adverse health outcomes. We determined the prevalence of cost-related nonadherence and investigated its associated characteristics, including whether a person has drug insurance. Using data from the 2007 Canada Community Health Survey, we analyzed the responses of 5732 people who answered questions about cost-related nonadherence to treatment. We determined the national prevalence of cost-related nonadherence and used logistic regression to evaluate the association between cost-related nonadherence and a series of demographic and socioeconomic variables, including province of residence, age, sex, household income, health status and having drug insurance. Cost-related nonadherence was reported by 9.6% (95% confidence interval [CI] 8.5%–10.6%) of Canadians who had received a prescription in the past year. In our adjusted model, we found that people in poor health (odds ratio [OR] 2.64, 95% CI 1.77–3.94), those with lower income (OR 3.29, 95% CI 2.03–5.33), those without drug insurance (OR 4.52, 95% CI 3.29–6.20) and those who live in British Columbia (OR 2.56, 95%CI 1.49–4.42) were more likely to report cost-related nonadherence. Predicted rates of cost-related nonadherence ranged from 3.6% (95% CI 2.4–4.5) among people with insurance and high household incomes to 35.6% (95% CI 26.1%–44.9%) among people with no insurance and low household incomes. About 1 in 10 Canadians who receive a prescription report cost-related nonadherence. The variability in insurance coverage for prescription medications appears to be a key reason behind this phenomenon.

Opioid-related mortality appears to be increasing in Canada. We examined the true extent of the problem and the impact of the introduction of long-acting oxycodone. We examined trends in the prescribing of opioid analgesics in the province of Ontario from 1991 to 2007. We reviewed all deaths related to opioid use between 1991 and 2004. We linked 3271 of these deaths to administrative data to examine the patients' use of health care services before death. Using time-series analysis, we determined whether the addition of long-acting oxycodone to the provincial drug formulary in January 2000 was associated with an increase in opioid-related mortality. From 1991 to 2007, annual prescriptions for opioids in creased from 458 to 591 per 1000 individuals. Opioid-related deaths doubled, from 13.7 per million in 1991 to 27.2 per million in 2004. Prescriptions of oxycodone increased by 850% between 1991 and 2007. The addition of long-acting oxycodone to the drug formulary was associated with a 5-fold increase in oxycodone-related mortality (p < 0.01) and a 41% increase in overall opioid-related mortality (p = 0.02). The manner of death was deemed unintentional by the coroner in 54.2% and undetermined in 21.9% of cases. Use of health care services in the month before death was common: for example, of the 3066 patients for whom data on physician visits were available, 66.4% had visited a physician in the month before death; of the 1095 patients for whom individual-level prescribing data were available, 56.1% had filled a prescription for an opioid in the month before death. Opioid-related deaths in Ontario have increased markedly since 1991. A significant portion of the increase was associated with the addition of long-acting oxycodone to the provincial drug formulary. Most of the deaths were deemed unintentional. The frequency of visits to a physician and prescriptions for opioids in the month before death suggests a missed opportunity for prevention.

Activity-based funding (ABF) of hospitals is a policy intervention intended to re-shape incentives across health systems through the use of diagnosis-related groups. Many countries are adopting or actively promoting ABF. We assessed the effect of ABF on key measures potentially affecting patients and health care systems: mortality (acute and post-acute care); readmission rates; discharge rate to post-acute care following hospitalization; severity of illness; volume of care. We undertook a systematic review and meta-analysis of the worldwide evidence produced since 1980. We included all studies reporting original quantitative data comparing the impact of ABF versus alternative funding systems in acute care settings, regardless of language. We searched 9 electronic databases (OVID MEDLINE, EMBASE, OVID Healthstar, CINAHL, Cochrane CENTRAL, Health Technology Assessment, NHS Economic Evaluation Database, Cochrane Database of Systematic Reviews, and Business Source), hand-searched reference lists, and consulted with experts. Paired reviewers independently screened for eligibility, abstracted data, and assessed study credibility according to a pre-defined scoring system, resolving conflicts by discussion or adjudication. Of 16,565 unique citations, 50 US studies and 15 studies from 9 other countries proved eligible (i.e. Australia, Austria, England, Germany, Israel, Italy, Scotland, Sweden, Switzerland). We found consistent and robust differences between ABF and no-ABF in discharge to post-acute care, showing a 24% increase with ABF (pooled relative risk  = 1.24, 95% CI 1.18-1.31). Results also suggested a possible increase in readmission with ABF, and an apparent increase in severity of illness, perhaps reflecting differences in diagnostic coding. Although we found no consistent, systematic differences in mortality rates and volume of care, results varied widely across studies, some suggesting appreciable benefits from ABF, and others suggesting deleterious consequences. Transitioning to ABF is associated with important policy- and clinically-relevant changes. Evidence suggests substantial increases in admissions to post-acute care following hospitalization, with implications for system capacity and equitable access to care. High variability in results of other outcomes leaves the impact in particular settings uncertain, and may not allow a jurisdiction to predict if ABF would be harmless. Decision-makers considering ABF should plan for likely increases in post-acute care admissions, and be aware of the large uncertainty around impacts on other critical outcomes.