Project description:ObjectivesTo examine how the COVID-19 pandemic affected the demographic and clinical characteristics, in-hospital care, and outcomes of long-term care residents admitted to general medicine wards for non-COVID-19 reasons.MethodsWe conducted a retrospective cohort study of long-term care residents admitted to general medicine wards, for reasons other than COVID-19, in four hospitals in Toronto, Ontario between January 1, 2018 and December 31, 2020. We used an autoregressive linear model to estimate the change in monthly admission volumes during the pandemic period (March-December 2020) compared to the previous two years, adjusting for any secular trend. We summarized and compared differences in the demographics, comorbidities, interventions, diagnoses, imaging, psychoactive medications, and outcomes of residents before and during the pandemic.ResultsOur study included 2,654 long-term care residents who were hospitalized for non-COVID-19 reasons between January 2018 and December 2020. The crude rate of hospitalizations was 79.3 per month between March-December of 2018-2019 and 56.5 per month between March-December of 2020. The was an adjusted absolute difference of 27.0 (95% CI: 10.0, 43.9) fewer hospital admissions during the pandemic period, corresponding to a relative drop of 34%. Residents admitted during the pandemic period had similar demographics and clinical characteristics but were more likely to be admitted for delirium (pandemic: 7% pre-pandemic: 5%, p = 0.01) and were less likely to be admitted for pneumonia (pandemic: 3% pre-pandemic: 6%, p = 0.004). Residents admitted during the pandemic were more likely to be prescribed antipsychotics (pandemic: 37%, pre-pandemic: 29%, p <0.001) and more likely to die in-hospital (pandemic:14% pre-pandemic: 10%, p = 0.04).Conclusions and implicationsBetter integration between long-term care and hospitals systems, including programs to deliver urgent medical care services within long-term care homes, is needed to ensure that long-term care residents maintain equitable access to acute care during current and future public health emergencies.

Project description:ImportanceCOVID-19 has had devastating effects on the health and well-being of older adult residents and health care professionals in nursing homes. Uncertainty about the associated consequences of these adverse effects on the use of medications common to this care setting remains.ObjectiveTo examine the association between the COVID-19 pandemic and prescription medication changes among nursing home residents.Design, setting, and participantsThis population-based cohort study with an interrupted time-series analysis used linked health administrative data bases for residents of all nursing homes (N = 630) in Ontario, Canada. During the observation period, residents were divided into consecutive weekly cohorts. The first observation week was March 5 to 11, 2017; the last observation week was September 20 to 26, 2020.ExposuresOnset of the COVID-19 pandemic on March 1, 2020.Main outcomes and measuresWeekly proportion of residents dispensed antipsychotics, benzodiazepines, antidepressants, anticonvulsants, opioids, antibiotics, angiotensin receptor blockers (ARBs), and angiotensin-converting enzyme (ACE) inhibitors. Autoregressive integrated moving average models with step and ramp intervention functions tested for level and slope changes in weekly medication use after the onset of the pandemic and were fit on prepandemic data for projected trends.ResultsAcross study years, the annual cohort size ranged from 75 850 to 76 549 residents (mean [SD] age, 83.4 [10.8] years; mean proportion of women, 68.9%). A significant increased slope change in the weekly proportion of residents who were dispensed antipsychotics (parameter estimate [β] = 0.051; standard error [SE] = 0.010; P < .001), benzodiazepines (β = 0.026; SE = 0.003; P < .001), antidepressants (β = 0.046; SE = 0.013; P < .001), trazodone hydrochloride (β = 0.033; SE = 0.010; P < .001), anticonvulsants (β = 0.014; SE = 0.006; P = .03), and opioids (β = 0.038; SE = 0.007; P < .001) was observed. The absolute difference in observed vs estimated use in the last week of the pandemic period ranged from 0.48% (for anticonvulsants) to 1.52% (for antipsychotics). No significant level or slope changes were found for antibiotics, ARBs, or ACE inhibitors.Conclusions and relevanceIn this population-based cohort study, statistically significant increases in the use of antipsychotics, benzodiazepines, antidepressants, anticonvulsants, and opioids followed the onset of the COVID-19 pandemic, although absolute differences were small. There were no significant changes for antibiotics, ARBs, or ACE inhibitors. Studies are needed to monitor whether changes in pharmacotherapy persist, regress, or accelerate during the course of the pandemic and how these changes affect resident-level outcomes.

Project description:Examination of the impact of the COVID-19 pandemic on rates of antipsychotic medication use, initiation and discontinuation, among newly admitted long-term care residents. Repeated cross-sectional study. Long-term care home residents in Alberta, British Columbia and Ontario, Canada assessed with the Minimum Data Set (MDS) 2.0 assessment. The cohort was segmented according to admission during the pandemic (March 2020/2021) and 2 pre-pandemic (March 2018/2019 and March 2019/2020) periods. Multivariable logistic regression models were fit to characterize the association between long-term care admission during the COVID-19 pandemic and the use of antipsychotic medications. A second set of logistic regression models were fit among residents with follow-up assessments to characterize the association between long-term care admission and antipsychotic initiation/discontinuation at follow-up. All models were adjusted for resident characteristics including sex, age group, Aggressive Behaviour Scale score, Cognitive Performance Scale score, and diagnoses of Alzheimer's disease and related dementias, anxiety disorder, depression, and bipolar disorder. 21 612 residents admitted during the pandemic and over 30 000 in each pre-pandemic period were included. Antipsychotic use increased during the pandemic period among newly admitted residents from both community (adjusted odds ratio [aOR] 1.20-1.29) and hospital settings (aOR 1.21-1.23). Residents admitted during the pandemic period were more likely to have antipsychotic medications initiated (aOR 1.25-1.26) and less likely to have had them discontinued (aOR 0.74-0.76) at the time of follow-up assessment. Multiple factors contributed to the observed increase in antipsychotic medication use among newly admitted long-term care home residents during the COVID-19 pandemic: increased medication use at the time of admission, increased medication initiation at follow-up, and decreased medication discontinuation at follow-up. A whole-systems approach that extends beyond long-term care into hospital and community settings is necessary to address this prevalent issue.

Project description:ImportancePolice shootings can cause serious acute injury, and knowledge of subsequent health outcomes may inform interventions to improve care.ObjectiveTo analyze long-term health care costs among survivors of police shootings compared with those surviving nonfirearm police enforcement injuries using a retrospective design.Design, setting, and participantsThis population-based cohort analysis identified adults (age ≥16 years) who were injured by police and required emergency medical care between April 1, 2002, and March 31, 2022, in Ontario, Canada.ExposurePolice shootings compared with other mechanisms of injury involving police.Main outcomes and measuresLong-term health care costs determined using a validated costing algorithm. Secondary outcomes included short-term mortality, acute care treatments, and rates of subsequent disability.ResultsOver the study, 13 545 adults were injured from police enforcement (mean [SD] age, 35 [12] years; 11 637 males [86%]). A total of 13 520 individuals survived acute injury, and 8755 had long-term financial data available (88 surviving firearm injury, 8667 surviving nonfirearm injury). Patients surviving firearm injury had 3 times greater health care costs per year (CAD$16 223 vs CAD$5412; mean increase, CAD$9967; 95% CI, 6697-13 237; US $11 982 vs US $3997; mean increase, US $7361; 95% CI, 4946-9776; P < .001). Greater costs after a firearm injury were not explained by baseline costs and primarily reflected increased psychiatric care. Other characteristics associated with increased long-term health care costs included prior mental illness and a substance use diagnosis.Conclusions and relevanceIn this longitudinal cohort study of long-term health care costs, patients surviving a police shooting had substantial health care costs compared with those injured from other forms of police enforcement. Costs primarily reflected psychiatric care and suggest the need to prioritize early recognition and prevention.

Project description:ImportanceRecent immigrants face unique cultural and logistical challenges that differ from those of long-standing residents, which may influence the type of care they receive at the end of life.ObjectiveTo compare places of care among recent immigrants and long-standing residents in Canada in the last 90 days of life.Design, setting, and participantsThis population-based retrospective cohort study used linked health administrative data on individuals from Ontario, Canada, who died between January 1, 2013, and December 31, 2016, extracted on February 26, 2020. Individuals were categorized by immigration status: recent immigrants (since 1985) and long-standing residents. Data were analyzed from December 27, 2019, to February 26, 2020.ExposuresAll decedents who immigrated to Canada between 1985 and 2016 were classified as recent immigrants. Subgroup analyses assessed the association of region of origin.Main outcomes and measuresThe main outcome was place of care, including institutional and noninstitutional settings, in the last 90 days of life. Descriptive statistics were used to compare characteristics and health service utilization among recent immigrants and long-standing residents. Negative binomial regression models estimated the rate ratios (RR) of using acute care and long-term care in the last 90 days of life.ResultsA total of 376 617 deceased individuals (median [IQR] age, 80 [68-88] years; 187 439 [49.8%] women and 189 178 [50.2%] men) were identified, among whom 22 423 (6.0%) were recent immigrants; recent immigrants were younger than long-standing residents (median [IQR] age, 76 [60-85] years vs 81 [69-88] years; P < .001), more likely to be living in lower income neighborhoods (12 357 immigrants [55.1%] vs 166 017 long-standing residents [46.9%] in the lower 2 income quintiles; P < .001), and had a higher Charlson Index score (score ≥5, 6294 immigrants [28.1%] vs 74 809 long-standing residents [21.1%]; P < .001). In the last 90 days of life, recent immigrants spent more days in intensive care units than long-standing residents (mean [SD], 2.64 [8.73] days vs 1.47 [5.70] days; P < .001), while long-standing residents spent more days using long-term care than recent immigrants (mean [SD], 19.49 [35.81] days vs 10.45 [27.42] days; P < .001). Being a recent immigrant was associated with a greater likelihood of acute inpatient care use (RR, 1.21; 95% CI, 1.18-1.24) and lower likelihood of long-term care use (RR, 0.66; 95% CI, 0.63-0.70), after adjusting for covariates.Conclusions and relevanceThese findings suggest that at the end of life, recent immigrants were significantly more likely to receive inpatient and intensive care unit services and die in acute care settings compared with long-standing residents. Further research is needed to examine differences in care preference and disparities for immigrant groups of different origins.

Project description:ObjectiveThe objective was to compare home care episode, standardised assessment, and service patterns in Ontario's publicly funded home care system during the first wave of the COVID-19 pandemic (i.e., March to September 2020) using the previous year as reference.Study design and settingWe plotted monthly time series data from March 2019 to September 2020 for home care recipients in Ontario, Canada. Home care episodes were linked to interRAI Home Care assessments, interRAI Contact Assessments, and home care services. Health status measures from the patient's most recent interRAI assessment were used to stratify the receipt of personal support, nursing, and occupational or physical therapy services. Significant level and slope changes were detected using Poisson, beta, and linear regression models.ResultsThe March to September 2020 period was associated with significantly fewer home care admissions, discharges, and standardised assessments. Among those assessed with the interRAI Home Care assessment, significantly fewer patients received any personal support services. Among those assessed with either interRAI assessment and identified to have rehabilitation needs, significantly fewer patients received any therapy services. Among patients receiving services, patients received significantly fewer hours of personal support and fewer therapy visits per month. By September 2020, the rate of admissions and services had mostly returned to pre-pandemic levels, but completion of standardised assessments lagged behind.ConclusionThe first wave of the COVID-19 pandemic was associated with substantial changes in Ontario's publicly funded home care system. Although it may have been necessary to prioritise service delivery during a crisis situation, standardised assessments are needed to support individualised patient care and system-level monitoring. Given the potential disruptions to home care services, future studies should examine the impact of the pandemic on the health and well-being of home care recipients and their caregiving networks.

Dataset Information

Cognitive Decline in Long-term Care Residents Before and During the COVID-19 Pandemic in Ontario, Canada.

Publications

Cognitive Decline in Long-term Care Residents Before and During the COVID-19 Pandemic in Ontario, Canada.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets