Evaluation and comparison of covariate balance metrics in studies with time-dependent confounding.

Marginal structural models have been increasingly used by analysts in recent years to account for confounding bias in studies with time-varying treatments. The parameters of these models are often estimated using inverse probability of treatment weighting. To ensure that the estimated weights adequately control confounding, it is possible to check for residual imbalance between treatment groups in the weighted data. Several balance metrics have been developed and compared in the cross-sectional case but have not yet been evaluated and compared in longitudinal studies with time-varying treatment. We have first extended the definition of several balance metrics to the case of a time-varying treatment, with or without censoring. We then compared the performance of these balance metrics in a simulation study by assessing the strength of the association between their estimated level of imbalance and bias. We found that the Mahalanobis balance performed best. Finally, the method was illustrated for estimating the cumulative effect of statins exposure over one year on the risk of cardiovascular disease or death in people aged 65 and over in population-wide administrative data. This illustration confirms the feasibility of employing our proposed metrics in large databases with multiple time-points.

Traditional Methods Hold Their Ground Against Machine Learning in Predicting Potentially Inappropriate Medication Use in Older Adults.

OBJECTIVES: Machine learning methods have gained much attention in health sciences for predicting various health outcomes but are scarcely used in pharmacoepidemiology. The ability to identify predictors of suboptimal medication use is essential for conducting interventions aimed at improving medication outcomes. It remains uncertain whether machine learning methods could enhance the identification of potentially inappropriate medication use among older adults compared with traditional methods. This study aimed to (1) to compare the performances of machine learning models in predicting use of potentially inappropriate medications and (2) to quantify and compare the relative importance of predictors in a population of community-dwelling older adults (>65 years) in the province of Québec, Canada. METHODS: We used the Québec Integrated Chronic Disease Surveillance System and selected a cohort of 1 105 295 older adults of whom 533 719 were potentially inappropriate medication users. Potentially inappropriate medications were defined according to the Beers list. We compared performances between 5 popular machine learning models (gradient boosting machines, logistic regression, naive Bayes, neural networks, and random forests) based on receiver operating characteristic curves and other performance criteria, using a set of sociodemographic and medical predictors. RESULTS: No model clearly outperformed the others. All models except neural networks were in agreement regarding the top predictors (sex and anxiety-depressive disorders and schizophrenia) and the bottom predictors (rurality and social and material deprivation indices). CONCLUSIONS: Including other types of predictors (eg, unstructured data) may be more useful for increasing performance in prediction of potentially inappropriate medication use.

Multimorbidity prevalence and health outcome prediction: assessing the impact of lookback periods, disease count, and definition criteria in health administrative data at the population-based level.

BACKGROUND: Health administrative databases play a crucial role in population-level multimorbidity surveillance. Determining the appropriate retrospective or lookback period (LP) for observing prevalent and newly diagnosed diseases in administrative data presents challenge in estimating multimorbidity prevalence and predicting health outcome. The aim of this population-based study was to assess the impact of LP on multimorbidity prevalence and health outcomes prediction across three multimorbidity definitions, three lists of diseases used for multimorbidity assessment, and six health outcomes. METHODS: We conducted a population-based study including all individuals ages > 65 years on April 1st, 2019, in Québec, Canada. We considered three lists of diseases labeled according to the number of chronic conditions it considered: (1) L60 included 60 chronic conditions from the International Classification of Diseases (ICD); (2) L20 included a core of 20 chronic conditions; and (3) L31 included 31 chronic conditions from the Charlson and Elixhauser indices. For each list, we: (1) measured multimorbidity prevalence for three multimorbidity definitions (at least two [MM2+], three [MM3+] or four (MM4+) chronic conditions); and (2) evaluated capacity (c-statistic) to predict 1-year outcomes (mortality, hospitalisation, polypharmacy, and general practitioner, specialist, or emergency department visits) using LPs ranging from 1 to 20 years. RESULTS: Increase in multimorbidity prevalence decelerated after 5-10 years (e.g., MM2+, L31: LP = 1y: 14%, LP = 10y: 58%, LP = 20y: 69%). Within the 5-10 years LP range, predictive performance was better for L20 than L60 (e.g., LP = 7y, mortality, MM3+: L20 [0.798;95%CI:0.797-0.800] vs. L60 [0.779; 95%CI:0.777-0.781]) and typically better for MM3 + and MM4 + definitions (e.g., LP = 7y, mortality, L60: MM4+ [0.788;95%CI:0.786-0.790] vs. MM2+ [0.768;95%CI:0.766-0.770]). CONCLUSIONS: In our databases, ten years of data was required for stable estimation of multimorbidity prevalence. Within that range, the L20 and multimorbidity definitions MM3 + or MM4 + reached maximal predictive performance.

A Bootstrap Approach for Evaluating Uncertainty in the Number of Groups Identified by Latent Class Growth Models.

The use of longitudinal finite mixture models such as group-based trajectory modeling has seen a sharp increase during the last few decades in the medical literature. However, these methods have been criticized, especially because of the data-driven modeling process, which involves statistical decision-making. In this paper, we propose an approach that uses the bootstrap to sample observations with replacement from the original data to validate the number of groups identified and to quantify the uncertainty in the number of groups. The method allows investigation of the statistical validity and uncertainty of the groups identified in the original data by checking to see whether the same solution is also found across the bootstrap samples. In a simulation study, we examined whether the bootstrap-estimated variability in the number of groups reflected the replicationwise variability. We evaluated the ability of 3 commonly used adequacy criteria (average posterior probability, odds of correct classification, and relative entropy) to identify uncertainty in the number of groups. Finally, we illustrate the proposed approach using data from the Quebec Integrated Chronic Disease Surveillance System to identify longitudinal medication patterns between 2015 and 2018 in older adults with diabetes.

An Alternative Perspective on the Robust Poisson Method for Estimating Risk or Prevalence Ratios.

The robust Poisson method is becoming increasingly popular when estimating the association of exposures with a binary outcome. Unlike the logistic regression model, the robust Poisson method yields results that can be interpreted as risk or prevalence ratios. In addition, it does not suffer from frequent nonconvergence problems such as the most common implementations of maximum likelihood estimators of the log-binomial model. However, using a Poisson distribution to model a binary outcome may seem counterintuitive. Methodologic papers have often presented this as a good approximation to the more natural binomial distribution. In this article, we provide an alternative perspective to the robust Poisson method based on the semiparametric theory. This perspective highlights that the robust Poisson method does not require assuming a Poisson distribution for the outcome. In fact, the method only assumes a log-linear relation between the risk or prevalence of the outcome and the explanatory variables. This assumption and the consequences of its violation are discussed. We also provide suggestions to reduce the risk of violating the modeling assumption. Additionally, we discuss and contrast the robust Poisson method with other approaches for estimating exposure risk or prevalence ratios. See video abstract at, http://links.lww.com/EDE/B987 .

The 5-year longitudinal diagnostic profile and health services utilization of patients treated with electroconvulsive therapy in Quebec: a population-based study.

PURPOSE: Electroconvulsive therapy (ECT) is effective for treating several psychiatric disorders. However, only a minority of patients are treated with ECT. It is of primary importance to characterize their profile for epidemiological purposes and to inform clinical practice. We aimed to characterize the longitudinal profile of psychopathology and services utilization of patients first treated with ECT. METHODS: We conducted a population-based comparative study using data from a national administrative database in Quebec. Patients who received a first ECT between 2002 and 2016 were compared to controls who were hospitalized in psychiatry but did not receive ECT. We performed descriptive analyses to compare psychiatric diagnoses, domains of psychopathology (internalizing, externalizing and thought/psychotic disorders), medical services and medication use in the 5 years prior to the ECT or hospitalization. RESULTS: 5 080 ECT patients were compared with 179 594 controls. Depressive, anxiety, bipolar and psychotic disorders were more frequent in the ECT group. 96.2% of ECT patients had been diagnosed with depression and 53.8% with a primary psychotic disorder. In the ECT group, 1.0% had been diagnosed exclusively with depression and 47.0% had disorders from that belong to all three domains of psychopathology. Having both internalizing and thought/psychotic disorders was associated with an increased likelihood of receiving ECT vs having internalizing disorders alone (unadjusted OR = 2.93; 95% CI = 2.63, 3.26). All indicators of mental health services utilization showed higher use among ECT patients. CONCLUSION: Our results provide robust evidence of complex longitudinal psychopathology and extensive services utilization among ECT patients.

Changes in Polypharmacy and Psychotropic Medication Use After Diagnosis of Major Neurocognitive Disorders: A Population-based Study in Québec, Canada.

BACKGROUND: Older adults with major neurocognitive disorder (MNCD) are often exposed to polypharmacy. We aimed to assess the prescribing and discontinuation patterns of medications following diagnosis of MNCD among community-dwelling older adults. METHODS: Using the Quebec Integrated Chronic Disease Surveillance System, we conducted a population-based cohort study comparing 1-year prediagnosis and postdiagnosis use of medications between a group of individuals older than 65 years newly diagnosed with MNCD in 2016-2017 and a control group without MNCD. The difference-in-difference method was used to estimate the prediagnosis and postdiagnosis variation in the number of medications prescribed and in the proportion of psychotropic and anticholinergic medication users. RESULTS: In the MNCD group, the mean number of medications used (excluding Alzheimer disease treatments) increased by 1.25 in the year after the diagnosis. The respective increase was 0.45 in the control group, yielding an adjusted difference-in-differences of 0.81 (95% confidence interval: 0.74; 0.87) between groups. The adjusted difference-in-differences in the proportions of antipsychotic, antidepressant, and anticholinergic medication users was 13.2% (12.5; 13.9), 7.1% (6.5; 7.7), and 3.8% (3.1; 4.6), respectively. CONCLUSIONS: The medication burden among older adults tends to increase in the year following a diagnosis of MNCD. The use of antipsychotics and antidepressants may explain a part of the observed increase.

Attitudes and beliefs of older adults and caregivers towards deprescribing in French-speaking countries: a multicenter cross-sectional study.

PURPOSE: Successful deprescribing requires understanding the attitudes of older adults and caregivers towards this process. This study aimed to capture these attitudes in four French-speaking countries and to investigate associated factors. METHODS: A multicenter cross-sectional study was conducted by administrating the French version of the revised Patients' Attitudes Towards Deprescribing (rPATD) questionnaire in Belgium, Canada, France, and Switzerland. Community-dwelling or nursing home older adults ≥ 65 years taking ≥ 1 prescribed medications and caregivers of older adults with similar characteristics were included. Multivariate logistic regressions were carried out to examine factors associated with willingness to deprescribe. RESULTS: A total of 367 older adults (79.3 ± 8.7 years, 63% community-dwelling, 54% ≥ 5 medications) and 255 unrelated caregivers (64.4 ± 12.6 years) of care recipients (83.4 ± 7.9 years, 52% community-dwelling, 69% ≥ 5 medications) answered the questionnaire. Among them, 87.5% older adults and 75.6% caregivers would be willing to stop medications if the physician said it was possible. Reluctance to stop a medication taken for a long time was expressed by 46% of both older adults and caregivers. A low score for the factor "concerns about stopping" (older adults: aOR: 0.21; 95% CI: 0.07-0.59), and a high score for the factor "involvement" (older adults: aOR: 2.66; 95% CI: 1.01-7.07; caregivers: aOR: 11.28; 95% CI: 1.48-85.91) were associated with willingness to deprescribe. CONCLUSIONS: A significant proportion of older adults and caregivers of French-speaking countries are open to deprescribing. Despite this apparent willingness, deprescribing conversations in clinical practice remains marginal, emphasizing the importance of optimizing the integration of existing tools such as rPATD.

Trends in benzodiazepine and alternative hypnotic use in relation with multimorbidity among older adults in Quebec, Canada.

BACKGROUND: Benzodiazepines and other hypnotic alternatives are associated with increased risks of adverse events. Heightened awareness of risks may have changed prescribing habits over the years. However, these trends are not fully described, especially in vulnerable people such as multimorbid older adults. OBJECTIVE: We aimed to describe the annual prevalence of benzodiazepine and other hypnotic use in relation to multimorbidity among older adults in the province of Quebec, Canada, from 2000 to 2016. METHOD: We conducted a population-based study using the Quebec Integrated Chronic Disease Surveillance System. We included all individuals aged ≥66 years covered by the public drug plan. For each year, we evaluated the sex- and age-standardized proportion of benzodiazepine and other hypnotic users, defined as individuals with at least one drug claim in the year. We stratified our results according to multimorbidity and used log-binomial regression to study trends. RESULTS: The proportion of individuals using benzodiazepines decreased from 34.8% in 2000 to 24.8% in 2016 (p for trend <0.001). Multimorbid people (≥2 chronic diseases) remained the highest users over the years, with 43.3% and 30.6% of them being users in 2000 and 2016, respectively. Conversely, the proportion of users increased for other hypnotics, particularly for trazodone and quetiapine, rising from 5.4% to 8.4% (p < 0.001), and especially among multimorbid individuals (from 7.4% to 11.6%). CONCLUSION: Older adults used benzodiazepines less frequently but quetiapine and trazodone more frequently in recent years. The use of these medications, particularly in multimorbid people at risk of adverse events, must be addressed.

Multimorbidity measures from health administrative data using ICD system codes: A systematic review.

BACKGROUND: We aimed to identify and characterize adult population-based multimorbidity measures using health administrative data and the International Classification of Diseases (ICD) codes for disease identification. METHODS: We performed a narrative systematic review of studies using or describing development or validation of multimorbidity measures. We compared the number of diseases included in the measures, the process of data extraction (case definition) and the validation process. We assessed the methodological robustness using eight criteria, five based on general criteria for indicators (AIRE instrument) and three multimorbidity-specific criteria. RESULTS: Twenty-two multimorbidity measures were identified. The number of diseases they included ranged from 5 to 84 (median = 20), with 19 measures including both physical and mental conditions. Diseases were identified using ICD codes extracted from inpatient and outpatient data (18/22) and sometimes including drug claims (10/22). The validation process relied mainly on the capacity of the measures to predict health outcome (5/22), or on the validation of each individual disease against a gold standard (8/22). Six multimorbidity measures met at least six of the eight robustness criteria assessed. CONCLUSION: There is significant heterogeneity among the measures used to assess multimorbidity in administrative databases, and about a third are of low to moderate quality. A more consensual approach to the number of diseases or groups of diseases included in multimorbidity measures may improve comparison between regions, and potentially provide better control for multimorbidity-related confounding in studies.

Prescribing and deprescribing in very old age: perceptions of very old adults, caregivers and health professionals.

BACKGROUND: although they are major consumers of medications, there is little evidence-based data to guide prescribing and deprescribing of medications for very old adults (80+ years). OBJECTIVES: to discover the perceptions of very old adults, caregivers and health professionals in order to further examine the clinical and ethical issues raised by prescribing and deprescribing in very old age. METHODS: individual interviews were conducted with very old adults (n = 10) and caregivers (n = 6), whereas group interviews were conducted with health professionals (n = 11). The themes covered included perceptions of medication use, polypharmacy, deprescribing and patient-health professional relationships. Thematic analysis was used to identify areas of convergence and divergence. RESULTS: very old adults are satisfied with the medications they are taking, do not see the need to reduce their medication use and consider their doctor as the expert who should make the decisions regarding treatment. The perceptions of caregivers are similar to those of older adults, whereas health professionals believe that very old adults take a lot of inappropriate medications and list multiple barriers to deprescribing. All participants describe a normalisation of medication use with ageing. CONCLUSION: there is a dichotomy between the perception of the very old adults/caregivers and that of health professionals regarding the safety of medication in very old age. A cultural change regarding medication use seems essential to optimise therapy and support deprescribing in clinical practice since the potential issues raised by researchers do not resonate with the main stakeholders.

Does socio-economic status influence the effect of multimorbidity on the frequent use of ambulatory care services in a universal healthcare system? A population-based cohort study.

BACKGROUND: Frequent healthcare users place a significant burden on health systems. Factors such as multimorbidity and low socioeconomic status have been associated with high use of ambulatory care services (emergency rooms, general practitioners and specialist physicians). However, the combined effect of these two factors remains poorly understood. Our goal was to determine whether the risk of being a frequent user of ambulatory care is influenced by an interaction between multimorbidity and socioeconomic status, in an entire population covered by a universal health system. METHODS: Using a linkage of administrative databases, we conducted a population-based cohort study of all adults in Quebec, Canada. Multimorbidity (defined as the number of different diseases) was assessed over a two-year period from April 1st 2012 to March 31st 2014 and socioeconomic status was estimated using a validated material deprivation index. Frequents users for a particular category of ambulatory services had a number of visits among the highest 5% in the total population during the 2014-15 fiscal year. We used ajusted logistic regressions to model the association between frequent use of health services and multimorbidity, depending on socioeconomic status. RESULTS: Frequent users (5.1% of the population) were responsible for 25.2% of all ambulatory care visits. The lower the socioeconomic status, the higher the burden of chronic diseases, and the more frequent the visits to emergency departments and general practitioners. Socioeconomic status modified the association between multimorbidity and frequent visits to specialist physicians: those with low socioeconomic status visited specialist physicians less often. The difference in adjusted proportions of frequent use between the most deprived and the least deprived individuals varied from 0.1% for those without any chronic disease to 5.1% for those with four or more chronic diseases. No such differences in proportions were observed for frequent visits to an emergency room or frequent visits to a general practitioner. CONCLUSION: Even in a universal healthcare system, the gap between socioeconomic groups widens as a function of multimorbidity with regard to visits to the specialist physicians. Further studies are needed to better understand the differential use of specialized care by the most deprived individuals.

Exploring polypharmacy with artificial intelligence: data analysis protocol.

BACKGROUND: Polypharmacy is common among older adults and it represents a public health concern, due to the negative health impacts potentially associated with the use of several medications. However, the large number of medication combinations and sequences of use makes it complicated for traditional statistical methods to predict which therapy is genuinely associated with health outcomes. The project aims to use artificial intelligence (AI) to determine the quality of polypharmacy among older adults with chronic diseases in the province of Québec, Canada. METHODS: We will use data from the Quebec Integrated Chronic Disease Surveillance System (QICDSS). QICDSS contains information about prescribed medications in older adults in Quebec collected over 20 years. It also includes diagnostic codes and procedures, and sociodemographic data linked through a unique identification number for each individual. Our research will be structured around three interconnected research axes: AI, Health, and Law&Ethics. The AI research axis will develop algorithms for finding frequent patterns of medication use that correlate with health events, considering data locality and temporality (explainable AI or XAI). The Health research axis will translate these patterns into polypharmacy indicators relevant to public health surveillance and clinicians. The Law&Ethics axis will assess the social acceptability of the algorithms developed using AI tools and the indicators developed by the Heath axis and will ensure that the developed indicators neither discriminate against any population group nor increase the disparities already present in the use of medications. DISCUSSION: The multi-disciplinary research team consists of specialists in AI, health data, statistics, pharmacy, public health, law, and ethics, which will allow investigation of polypharmacy from different points of view and will contribute to a deeper understanding of the clinical, social, and ethical issues surrounding polypharmacy and its surveillance, as well as the use of AI for health record data. The project results will be disseminated to the scientific community, healthcare professionals, and public health decision-makers in peer-reviewed publications, scientific meetings, and reports. The diffusion of the results will ensure the confidentiality of individual data.

One-year persistence of potentially inappropriate medication use in older adults: A population-based study.

AIMS: To assess the 1-year persistence of potentially inappropriate medication (PIM) use and identify associated factors in community-dwelling older adults in Quebec, Canada. METHODS: A population-based cohort study was conducted using the Quebec Integrated Chronic Disease Surveillance System. Individuals insured by the public drug plan and aged ≥66 years who initiated a PIM between 1 April 2014 and 31 March 2015 were followed-up for 1 year. PIMs were identified using the 2015 Beers criteria. One-year persistence of PIM use was defined as continuous treatment with any PIM, without interruption for more than 60 days between prescriptions refills. Poisson regression models were performed to identify factors associated with 1-year persistence of any PIM. RESULTS: In total, 25.1% of PIM initiators were persistent at 1 year. In non-persistent individuals, the median time to PIM discontinuation was 31 days (interquartile range 21-92). Individuals were more persistent at 1 year with antipsychotics (43.9%), long-duration sulphonylureas (40.2%), antiarrhythmics/immediate-release nifedipine (36.5%) and proton pump inhibitors (36.0%). Factors significantly associated with persistence were an increased age, being a man and having a high number of medications and chronic diseases, especially dementia, diabetes and cardiovascular diseases. CONCLUSIONS: One-quarter of community-dwelling older adults are continuously exposed to PIMs. To optimize medication prescribing in the older population, further interventions are needed to limit the use of PIMs most likely to be continued, especially in individuals most at risk of being persistent and also particularly vulnerable to adverse events.

Is Benzodiazepine Use Associated With the Risk of Dementia and Cognitive Impairment-Not Dementia in Older Persons? The Canadian Study of Health and Aging.

Background: The use of benzodiazepines in relation to cognitive decline remains an area of controversy in aging populations. Objective: This study aims to evaluate the risk of cognitive impairment-not dementia (CIND), Alzheimer disease (AD), and all-cause dementia with benzodiazepine use. The effect modification by sex was also investigated. Methods: Data come from the Canadian Study of Health and Aging, a 10-year multicentric study involving 10 263 participants randomly selected, 65 years and older, living in the community and in institutions. Current exposure to benzodiazepines was assessed in a face-to-face interview or self-reported in a questionnaire. Cox proportional hazard regression models, using age as time scale, were conducted to estimate hazard ratios, with adjustment for sex, education, smoking, alcohol intake, depression, physical activity, nonsteroidal anti-inflammatory drug use, and vascular comorbidities. Results: Data sets included 5281 participants for dementia as the outcome, 5015 for AD, and 4187 for CIND. Compared with nonusers, current use of benzodiazepines was associated with an increased risk of CIND (hazard ratio = 1.36; 95% CI = 1.08-1.72) in the simplest model. Results remained similar in the fully adjusted model (hazard ratio = 1.32; 95% CI = 1.04-1.68). There was no association between benzodiazepine use and the risk of dementia or AD. All these effects were similar between men and women. Conclusion and Relevance: Benzodiazepine use in older people from the general population is related to subsequent occurrence of cognitive dysfunction but not implicated in the pathogenesis of dementia or AD. Caution should be exercised when prescribing benzodiazepines to preserve global cognitive function.

Potentially inappropriate medications in older adults: a population-based cohort study.

BACKGROUND: Non-optimal medication use among older adults is a public health concern. A concrete picture of potentially inappropriate medication (PIM) use is imperative to ensure optimal medication use. OBJECTIVE: To assess the prevalence of PIMs in community-dwelling older adults and identify associated factors. METHODS: A retrospective population-based cohort study was conducted using the Quebec Integrated Chronic Disease Surveillance System (QICDSS). The QICDSS includes data on drug claims for community-dwelling older adults with chronic diseases or at risk of developing chronic diseases aged ≥65 years who are insured by the public drug insurance plan. Individuals aged ≥66 years who were continuously insured with the public drug plan between 1 April 2014 and 31 March 2016 were included. PIMs were defined using the 2015 Beers criteria. We conducted multivariate robust Poisson regression analyses to explore factors associated with PIM use. RESULTS: A total of 1 105 295 individuals were included. Of these, 48.3% were prescribed at least one PIM. The most prevalent PIMs were benzodiazepines (25.7%), proton-pump inhibitors (21.3%), antipsychotics (5.6%), antidepressants (5.0%) and long-duration sulfonylureas (3.3%). Factors associated with PIM exposure included being a woman [rate ratio (RR): 1.20; 95% confidence interval (CI): 1.20-1.21], increased number of medications and having a high number of chronic diseases, especially mental disorders (RR: 1.50; 95% CI: 1.49-1.51). CONCLUSION: Almost one out of two community-dwelling older adults use a PIM. It is imperative to reduce the use of PIMs, by limiting their prescription and by promoting their deprescribing, which necessitates not only the active involvement of prescribers but also patients.

Combined impacts of multimorbidity and mental disorders on frequent emergency department visits: a retrospective cohort study in Quebec, Canada.

BACKGROUND: Multimorbidity and mental disorders are independently associated with frequent visits to the emergency department (≥ 3 visits/yr), but their interaction has been little studied. We aimed to measure the interaction between mental disorders and physical multimorbidity with respect to frequent visits to the emergency department. METHODS: We conducted a population-based cohort study of adults in Quebec from 2012 to 2016, using the Quebec Integrated Chronic Disease Surveillance System. We assessed multimorbidity as the number of physical illnesses and mental disorders as serious (psychotic or bipolar disorders), common or absent, using data from 2012 to 2014. We counted emergency department visits from 2014 to 2015. We used logistic regression to estimate interaction on frequent visits to the emergency department from 2 perspectives: of public health (additive scale as differences in risk) and of individual patients (multiplicative scale as odds ratios). RESULTS: Each additional physical illness was associated with a greater increase in the absolute risk of frequent visits to the emergency department for people with mental disorders. Between 0 and ≥ 4 physical conditions, the absolute risk increased more for individuals with serious mental disorders (16.2%) than common (15.3%) or no disorders (11.4%). On the relative scale, for people with no mental disorders and ≥ 4 physical conditions, odds of frequent visits to the emergency department were 6.2 (95% confidence interval [CI] 6.08-6.35) times the odds for people with no physical conditions. For individuals with common and serious mental illnesses, corresponding odds ratios were 4.75 (95% CI 4.60-4.90) and 3.7 (95% CI 3.18-3.57), respectively. INTERPRETATION: Mental disorders interact with physical multimorbidity to increase the odds of frequent visits to the emergency department. More research is needed on interventions that promote high-quality care for mental illness, especially in the context of physical multimorbidity.

Polypharmacy among Older Individuals with COPD: Trends between 2000 and 2015 in Quebec, Canada.

The treatment of chronic obstructive pulmonary disease (COPD) and concomitant diseases requires several medications. Yet there is little data on how the pharmacological burden progressed over time among older individuals with COPD. We aimed to: 1) describe the proportion of older adults with COPD in Quebec, Canada, that were exposed to polypharmacy (≥10, ≥15 or ≥20 medications/year) between 2000 and 2015; 2) calculate the proportion of individuals receiving specific prescriptions for COPD during this period. We conducted a population-based cohort study with the Quebec Integrated Chronic Disease Surveillance System. Individuals aged ≥66 years with COPD and covered by the universal public drug plan were included. We calculated the total number of drugs used at least once by each individual during each of the studied years, and used age-standardized proportions to compare proportions of users between the years. The average number of drugs used increased from 12.0 in 2000 to 14.8 in 2015. The proportion of individuals exposed to polypharmacy increased (≥10 drugs: 62.0% to 74.6%;≥15 drugs: 31.2% to 45.4%; ≥20 drugs: 12.3% to 22.4%). The proportion of individuals receiving long-acting bronchodilators increased from 18.7% in 2000 to 69.6% in 2015. The use of short-acting bronchodilators decreased from 81.5% to 67.9%, and that of inhaled corticosteroids from 60.6% to 26.0%. The proportion of users of methylxanthines decreased from 15.0% to 1.9%. Older individuals with COPD are increasingly exposed to polypharmacy. Identifying which polypharmacy is beneficial is a priority.

Validation of the Combined Comorbidity Index of Charlson and Elixhauser to Predict 30-Day Mortality Across ICD-9 and ICD-10.

OBJECTIVES: To validate and compare performance of an International Classification of Diseases, tenth revision (ICD-10) version of a combined comorbidity index merging conditions of Charlson and Elixhauser measures against individual measures in the prediction of 30-day mortality. To select a weight derivation method providing optimal performance across ICD-9 and ICD-10 coding systems. RESEARCH DESIGN: Using 2 adult population-based cohorts of patients with hospital admissions in ICD-9 (2005, n=337,367) and ICD-10 (2011, n=348,820), we validated a combined comorbidity index by predicting 30-day mortality with logistic regression. To appreciate performance of the Combined index and both individual measures, factors impacting indices performance such as population characteristics and weight derivation methods were accounted for. We applied 3 scoring methods (Van Walraven, Schneeweiss, and Charlson) and determined which provides best predictive values. RESULTS: Combined index [c-statistics: 0.853 (95% confidence interval: CI, 0.848-0.856)] performed better than original Charlson [0.841 (95% CI, 0.835-0.844)] or Elixhauser [0.841 (95% CI, 0.837-0.844)] measures on ICD-10 cohort. All weight derivation methods provided close high discrimination results for the Combined index (Van Walraven: 0.852, Schneeweiss: 0.851, Charlson: 0.849). Results were consistent across both coding systems. CONCLUSIONS: The Combined index remains valid with both ICD-9 and ICD-10 coding systems and the 3 weight derivation methods evaluated provided consistent high performance across those coding systems.

Opioid prescribing and dispensing: Experiences and perspectives from a survey of community pharmacists practising in the province of Quebec.

BACKGROUND: Canada leads in opioid prescription and consumption rates, and this has resulted in high levels of opioid-related morbidity and mortality. Pharmacists' input could contribute significantly to understanding the disadvantages of opioid prescribing and dispensing and improving the service. This study aimed to examine the experiences of community pharmacists in relation to opioid prescribing and dispensing, with a focus on optimizing collaboration and communication. METHODS: An online survey was performed among pharmacists from the province of Quebec, Canada, in 2016. Pharmacists were eligible if registered and working in community pharmacies. RESULTS: In all, 542 questionnaires were analyzed (participation rate of 8.1%). Pharmacotherapy-related problems were reported in at least 50% of opioid prescriptions: additional drug(s) required (reported by 30% of pharmacists), interaction(s) between opioid(s) and other drug(s) (16%), physician did not meet the general issuing standards for opioid prescriptions (26%) and patient had mild to moderate pain that was easily managed by a nonopioid analgesic (20%). Half of the patients were reported as requesting anticipated refills, possibly indicating abuse or poor pain control. Most pharmacists (89.6%) reported needing to contact physicians in 1 to 3 out of 10 opioid prescriptions, but many pharmacists (71.8%, often or very often) reported difficulties communicating with physicians. CONCLUSIONS: Pharmacists' observations of pharmacotherapy-related problems and patients' unusual behaviours reveal a significant number of issues related to opioid prescribing and dispensing in an outpatient setting. Improved collaboration between physicians and pharmacists appears mandatory to address the issues reported in this study.