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      Comparison of Medication Prescribing Before and After the COVID-19 Pandemic Among Nursing Home Residents in Ontario, Canada

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          Key Points

          Question

          How are COVID-19 and related disruptions in care associated with changes in the dispensation of medications commonly used among nursing home residents?

          Findings

          In this population-based cohort study with an interrupted time-series analysis of all nursing home residents from the 630 facilities in Ontario, Canada, the emergence of the COVID-19 pandemic was associated with significant increases in the use of antipsychotics, benzodiazepines, antidepressants, anticonvulsants, and opioids and no meaningful changes in the use of antibiotics or selected cardiovascular medications.

          Meaning

          The finding of increased use of medications with the potential for adverse effects among nursing home residents during the initial wave of the pandemic warrants ongoing monitoring for prescribing appropriateness and related resident outcomes.

          Abstract

          Importance

          COVID-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.

          Objective

          To examine the association between the COVID-19 pandemic and prescription medication changes among nursing home residents.

          Design, Setting, and Participants

          This 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.

          Exposures

          Onset of the COVID-19 pandemic on March 1, 2020.

          Main Outcomes and Measures

          Weekly 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.

          Results

          Across 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 Relevance

          In 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.

          Abstract

          This population-based cohort study examines the association between the initial wave of the COVID-19 pandemic and changes in medication dispensation patterns among nursing home residents in the province of Ontario, Canada.

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          Most cited references56

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          Presenting Characteristics, Comorbidities, and Outcomes Among 5700 Patients Hospitalized With COVID-19 in the New York City Area

          There is limited information describing the presenting characteristics and outcomes of US patients requiring hospitalization for coronavirus disease 2019 (COVID-19).
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            Balance diagnostics for comparing the distribution of baseline covariates between treatment groups in propensity-score matched samples

            The propensity score is a subject's probability of treatment, conditional on observed baseline covariates. Conditional on the true propensity score, treated and untreated subjects have similar distributions of observed baseline covariates. Propensity-score matching is a popular method of using the propensity score in the medical literature. Using this approach, matched sets of treated and untreated subjects with similar values of the propensity score are formed. Inferences about treatment effect made using propensity-score matching are valid only if, in the matched sample, treated and untreated subjects have similar distributions of measured baseline covariates. In this paper we discuss the following methods for assessing whether the propensity score model has been correctly specified: comparing means and prevalences of baseline characteristics using standardized differences; ratios comparing the variance of continuous covariates between treated and untreated subjects; comparison of higher order moments and interactions; five-number summaries; and graphical methods such as quantile–quantile plots, side-by-side boxplots, and non-parametric density plots for comparing the distribution of baseline covariates between treatment groups. We describe methods to determine the sampling distribution of the standardized difference when the true standardized difference is equal to zero, thereby allowing one to determine the range of standardized differences that are plausible with the propensity score model having been correctly specified. We highlight the limitations of some previously used methods for assessing the adequacy of the specification of the propensity-score model. In particular, methods based on comparing the distribution of the estimated propensity score between treated and untreated subjects are uninformative. Copyright © 2009 John Wiley & Sons, Ltd.
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              Presymptomatic SARS-CoV-2 Infections and Transmission in a Skilled Nursing Facility

              Abstract Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection can spread rapidly within skilled nursing facilities. After identification of a case of Covid-19 in a skilled nursing facility, we assessed transmission and evaluated the adequacy of symptom-based screening to identify infections in residents. Methods We conducted two serial point-prevalence surveys, 1 week apart, in which assenting residents of the facility underwent nasopharyngeal and oropharyngeal testing for SARS-CoV-2, including real-time reverse-transcriptase polymerase chain reaction (rRT-PCR), viral culture, and sequencing. Symptoms that had been present during the preceding 14 days were recorded. Asymptomatic residents who tested positive were reassessed 7 days later. Residents with SARS-CoV-2 infection were categorized as symptomatic with typical symptoms (fever, cough, or shortness of breath), symptomatic with only atypical symptoms, presymptomatic, or asymptomatic. Results Twenty-three days after the first positive test result in a resident at this skilled nursing facility, 57 of 89 residents (64%) tested positive for SARS-CoV-2. Among 76 residents who participated in point-prevalence surveys, 48 (63%) tested positive. Of these 48 residents, 27 (56%) were asymptomatic at the time of testing; 24 subsequently developed symptoms (median time to onset, 4 days). Samples from these 24 presymptomatic residents had a median rRT-PCR cycle threshold value of 23.1, and viable virus was recovered from 17 residents. As of April 3, of the 57 residents with SARS-CoV-2 infection, 11 had been hospitalized (3 in the intensive care unit) and 15 had died (mortality, 26%). Of the 34 residents whose specimens were sequenced, 27 (79%) had sequences that fit into two clusters with a difference of one nucleotide. Conclusions Rapid and widespread transmission of SARS-CoV-2 was demonstrated in this skilled nursing facility. More than half of residents with positive test results were asymptomatic at the time of testing and most likely contributed to transmission. Infection-control strategies focused solely on symptomatic residents were not sufficient to prevent transmission after SARS-CoV-2 introduction into this facility.
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                Author and article information

                Journal
                JAMA Netw Open
                JAMA Netw Open
                JAMA Netw Open
                JAMA Network Open
                American Medical Association
                2574-3805
                2 August 2021
                August 2021
                2 August 2021
                : 4
                : 8
                : e2118441
                Affiliations
                [1 ]ICES (formerly Institute for Clinical Evaluative Sciences), Toronto, Ontario, Canada
                [2 ]Institute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
                [3 ]Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
                [4 ]Women’s College Research Institute, Women’s College Hospital, Toronto, Ontario, Canada
                [5 ]Division of Epidemiology, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
                [6 ]Department of Statistics and Actuarial Science, University of Waterloo, Waterloo, Ontario, Canada
                [7 ]Leslie Dan Faculty of Pharmacy, University of Toronto, Toronto, Ontario, Canada
                [8 ]Department of Family Medicine, University of Alberta, Edmonton, Canada
                [9 ]Division of Geriatric Medicine, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
                [10 ]School of Pharmacy, University of Waterloo, Waterloo, Ontario, Canada
                [11 ]Public Health Sciences, University of Waterloo, Waterloo, Ontario, Canada
                Author notes
                Article Information
                Accepted for Publication: May 21, 2021.
                Published: August 2, 2021. doi:10.1001/jamanetworkopen.2021.18441
                Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2021 Campitelli MA et al. JAMA Network Open.
                Corresponding Author: Colleen J. Maxwell, PhD, School of Pharmacy, University of Waterloo, 200 University Ave West, Waterloo, ON N2L 3G1, Canada ( colleen.maxwell@ 123456uwaterloo.ca ).
                Author Contributions: Mr Campitelli had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
                Concept and design: Campitelli, Bronskill, Maclagan, Harris, Cotton, Tadrous, Gruneir, Maxwell.
                Acquisition, analysis, or interpretation of data: Campitelli, Bronskill, Cotton, Tadrous, Gruneir, Hogan, Maxwell.
                Drafting of the manuscript: Campitelli, Hogan, Maxwell.
                Critical revision of the manuscript for important intellectual content: Campitelli, Bronskill, Maclagan, Harris, Cotton, Tadrous, Gruneir, Maxwell.
                Statistical analysis: Campitelli, Maclagan, Harris, Cotton, Gruneir.
                Obtained funding: Bronskill, Maxwell.
                Administrative, technical, or material support: Harris.
                Supervision: Bronskill, Tadrous, Maxwell.
                Conflict of Interest Disclosures: Dr Bronskill reported receiving grants from the Canadian Institutes of Health Research (CIHR), nonfinancial support from ICES (formerly Institute for Clinical Evaluative Sciences), and grants from the Ontario Health Data Platform (OHDP) during the conduct of the study. Dr Tadrous reported receiving grants from the Ontario Ministry of Health (MOH) and the Ministry of Long-term Care (MLTC) during the conduct of the study. Dr Maxwell reported receiving grants from the CIHR, nonfinancial support from the ICES, and grants from the OHDP during the conduct of the study. No other disclosures were reported.
                Funding/Support: This research was funded by the CIHR through operating grant MOP-136854 (Exploring frailty and its role in the assessment of high-risk medications and risk of poor health outcomes in vulnerable populations), by ICES through an annual grant from the Ontario MOH and the MLTC; and by the OHDP, a Province of Ontario initiative to support Ontario’s ongoing response to COVID-19 and its related effects.
                Role of the Funder/Sponsor: The sponsors had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
                Disclaimer: The opinions, results and conclusions reported in this article are those of the authors and are independent from the funding sources. No endorsement by the ICES, the MOH or MLTC, OHDP, its partners, or the Province of Ontario is intended or should be inferred. Parts of this material are based on data and information compiled and provided by the CIHI; however, the analyses, conclusions, opinions, and statements expressed herein are those of the authors and not necessarily those of CIHI.
                Additional Contributions: We thank IQVIA Solutions Canada Inc. for use of their Drug Information Database.
                Additional Information: The data set from this study is held securely in coded form at ICES. Although data sharing agreements prohibit ICES from making the data set publicly available, access may be granted to those who meet prespecified criteria for confidential access at https://www.ices.on.ca/DAS. Please contact the authors for any supplemental information related to the study such as the study protocol, analysis plan, or analytic code. The full data set creation plan and underlying analytic code are available from the authors upon request, understanding that the computer programs may rely on coding templates or macros that are unique to ICES and are therefore either inaccessible or may require modification.
                Article
                zoi210542
                10.1001/jamanetworkopen.2021.18441
                8329744
                34338794
                a2d2015e-8a29-4346-ab22-4f96d78167ee
                Copyright 2021 Campitelli MA et al. JAMA Network Open.

                This is an open access article distributed under the terms of the CC-BY License.

                History
                : 19 January 2021
                : 21 May 2021
                Categories
                Research
                Original Investigation
                Online Only
                Geriatrics

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