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 to traditional methods. The aim of this study was 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 Quebec, Canada. METHODS: We used the Quebec 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 five popular machine learning models (gradient boosting machines, logistic regression, naïve Bayes, neural networks, and random forests) based on ROC 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 (e.g., unstructured data) may be more useful for increasing performance in prediction of potentially inappropriate medication use.

Profiles of healthcare use of persons living with dementia: A population-based cohort study.

AIM: Persons living with dementia are a heterogeneous population with complex needs whose healthcare use varies widely. This study aimed to identify the healthcare use profiles in a cohort of persons with incident dementia, and to describe their characteristics. METHODS: This is a retrospective cohort study of health administrative data in Quebec (Canada). The study population included persons who: (i) had an incident dementia diagnosis between 1 April 2015 and 31 March 2016; (ii) were aged ≥65 years and living in the community at the time of diagnosis. We carried out a latent class analysis to identify subgroups of healthcare users. The final number of groups was chosen based on clinical interpretation and statistical indicators. RESULTS: The study cohort consisted of 15 584 individuals with incident dementia. Four profiles of healthcare users were identified: (i) Low Users (36.4%), composed of individuals with minimal healthcare use and fewer comorbidities; (ii) Ambulatory Care-Centric Users (27.5%), mainly composed of men with the highest probability of visiting cognition specialists; (iii) High Acute Hospital Users (23.6%), comprised of individuals mainly diagnosed during hospitalization, with higher comorbidities and mortality rate; and (iv) Long-Term Care Destined Users (12.5%), who showed the highest proportion of antipsychotics prescriptions and delayed hospitalization discharge. CONCLUSIONS: We identified four distinct subgroups of healthcare users within a population of persons living with dementia, providing a valuable context for the development of interventions tailored to specific needs within this diverse population. Geriatr Gerontol Int 2024; ••: ••-••.

10-Year Multimorbidity Trajectories in Older People Have Limited Benefit in Predicting Short-Term Health Outcomes in Comparison to Standard Multimorbidity Thresholds: A Population-Based Study.

Purpose: To identify multimorbidity trajectories among older adults and to compare their health outcome predictive performance with that of cross-sectional multimorbidity thresholds (eg, ≥2 chronic conditions (CCs)). Patients and Methods: We performed a population-based longitudinal study with a random sample of 99,411 individuals aged >65 years on April 1, 2019. Using health administrative data, we calculated for each individual the yearly CCs number from 2010 to 2019 and constructed the trajectories with latent class growth analysis. We used logistic regression to determine the increase in predictive capacity (c-statistic) of multimorbidity trajectories and traditional cross-sectional indicators (≥2, ≥3, or ≥4 CCs, assessed in April 2019) over that of a baseline model (including age, sex, and deprivation). We predicted 1-year mortality, hospitalization, polypharmacy, and frequent general practitioner, specialist, or emergency department visits. Results: We identified eight multimorbidity trajectories, each representing between 3% and 25% of the population. These trajectories exhibited trends of increasing, stable, or decreasing number of CCs. When predicting mortality, the 95% CI for the increase in the c-statistic for multimorbidity trajectories [0.032-0.044] overlapped with that of the ≥3 indicator [0.037-0.050]. Similar results were observed when predicting other health outcomes and with other cross-sectional indicators. Conclusion: Multimorbidity trajectories displayed comparable health outcome predictive capacity to those of traditional cross-sectional multimorbidity indicators. Given its ease of calculation, continued use of traditional multimorbidity thresholds remains relevant for population-based multimorbidity surveillance and clinical practice.

A comparative analysis of medication counting methods to assess polypharmacy in medico-administrative databases.

BACKGROUND: The variety of methods for counting medications may lead to confusion when attempting to compare the extent of polypharmacy across different populations. OBJECTIVE: To compare the prevalence estimates of polypharmacy derived from medico-administrative databases, using different methods for counting medications. METHODS: Data were drawn from the Québec Integrated Chronic Disease Surveillance System. A random sample of 110,000 individuals aged >65 was selected, including only those who were alive and covered by the public drug plan during the one-year follow-up. We used six methods to count medications: #1-cumulative one-year count, #2-average of four quarters' cumulative counts, #3-count on a single day, #4-count of medications used in first and fourth quarters, #5-count weighted by duration of exposure, and #6-count of uninterrupted medication use. Polypharmacy was defined as ≥5 medications. Cohen's Kappa was calculated to assess the level of agreement between the methods. RESULTS: A total of 93,516 (85 %) individuals were included. The prevalence of polypharmacy varied across methods. The highest prevalence was observed with cumulative methods (#1:74.1 %; #2:61.4 %). Single day count (#3:47.6 %), first and fourth quarters count (#4:49.5 %), and weighted count (#5:46.6 %) yielded similar results. The uninterrupted use count yielded the lowest estimate (#6:35.4 %). The weighted method (#5) showed strong agreement with the first and fourth quarters count (#4). Cumulative methods identified higher proportions of younger, less multimorbid individuals compared to other methods. CONCLUSION: Counting methods significantly affect polypharmacy prevalence estimates, necessitating their consideration when comparing and interpretating results.

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.

Rural-Urban Differences in Healthcare Use in Persons With Dementia Between 2000 and 2019: A Quebec Population-Based Study.

Background: Rural persons with dementia face medical services gaps. This study compares the health service utilization of rural and urban community-dwelling individuals with incident dementia. Methods: This study used a repeated annual cross-sectional cohort design spanning a period from 2000 to 2019 analyzing age-adjusted rates for 20 indicators of service use and mortality one year after diagnosis in Quebec administrative databases. Results: Of 237,259 persons, 20.1% were rural. Most rural persons had more emergency department visits and hospitalizations, shorter stays, less alternate level of care and fewer family physicians' and cognition specialists' visits. All groups had similar long-term care and mortality rates. Conclusion: Policy implications of these disparities are discussed.

Polypharmacy and risk of fractures in older adults: A systematic review.

BACKGROUND: Fractures have serious health consequences in older adults. While some medications are individually associated with increased risk of falls and fractures, it is not clear if this holds true for the use of many medications (polypharmacy). We aimed to identify what is known about the association between polypharmacy and the risk of fractures in adults aged ≥65 and to examine the methods used to study this association. METHODS: We conducted a systematic review with narrative synthesis of studies published up to October 2023 in PubMed, Embase, CINAHL, PsychINFO, Cochrane Library, Web of Science, and the grey literature. Two independent reviewers screened titles, abstracts, and full texts, then performed data extraction and quality assessment. RESULTS: Among the 31 studies included, 11 different definitions of polypharmacy were used and were based on three medication counting methods (concurrent use 15/31, cumulative use over a period 6/31, daily average 3/31, and indeterminate 7/31). Overall, polypharmacy was frequent and associated with higher fracture risk. A dose-response relationship between increasing number of medications and increased risk of fractures was observed. However, only seven studies adjusted for major confounders (age, sex, and chronic disease). The quality of the studies ranged from poor to high. CONCLUSIONS: Polypharmacy appears to be a relevant modifiable risk factor for fractures in older individuals that can easily be used to identify those at risk. The diversity of medication calculation methods and definitions of polypharmacy highlights the importance of a detailed methodology to understand and compare results.

[Programme d'été sur le vieillissement de l'Institut du vieillissement des Instituts de Recherche en Santé du Canada : trois pistes de réflexion de participants du Québec].

Chaque année, les Instituts de recherche en santé du Canada (IRSC) subventionnent le Programme d'été sur le vieillissement (PEV). Cette année, la semaine de formation qui rassemblait des étudiants canadiens de tous les cycles supérieurs avait pour thème la recherche multidisciplinaire au quatrième âge. Cette note de recherche présente trois éléments de réflexion de deux participants de l'édition 2023 du PEV : 1) les enjeux liés au vieillissement sont des occasions de transformer les paradigmes de la recherche; 2) la recherche collaborative doit être sociétale, et s'étendre au-delà du cercle restreint des milieux universitaires; 3) les critères d'équité, de diversité et d'inclusion intégrés aux projets de recherche doivent se refléter au sein des organisations qui mènent la recherche.

Effect of statin use for the primary prevention of cardiovascular disease among older adults: a cautionary tale concerning target trials emulation.

OBJECTIVES: Evidence concerning the effect of statins in primary prevention of cardiovascular disease (CVD) among older adults is lacking. Using Quebec population-wide administrative data, we emulated a hypothetical randomized trial including older adults >65 years on April 1, 2013, with no CVD history and no statin use in the previous year. STUDY DESIGN AND SETTING: We included individuals who initiated statins and classified them as exposed if they were using statin at least 3 months after initiation and nonexposed otherwise. We followed them until March 31, 2018. The primary outcome was the composite endpoint of coronary events (myocardial infarction, coronary bypass, and percutaneous coronary intervention), stroke, and all-cause mortality. The intention-to-treat (ITT) effect was estimated with adjusted Cox models and per-protocol effect with inverse probability of censoring weighting. RESULTS: A total of 65,096 individuals were included (mean age = 71.0 ± 5.5, female = 55.0%) and 93.7% were exposed. Whereas we observed a reduction in the composite outcome (ITT-hazard ratio (HR) = 0.75; 95% CI: 0.68-0.83) and mortality (ITT-HR = 0.69; 95% CI: 0.61-0.77) among exposed, coronary events increased (ITT-HR = 1.46; 95% CI: 1.09-1.94). All multibias E-values were low indicating that the results were not robust to unmeasured confounding, selection, and misclassification biases simultaneously. CONCLUSION: We cannot conclude on the effectiveness of statins in primary prevention of CVD among older adults. We caution that an in-depth reflection on sources of biases and careful interpretation of results are always required in observational studies.

Evidence-based data for newly approved medications' use in older adults: An analysis from clinical trials to monographs.

BACKGROUND: Older adults have historically been excluded from clinical trials, limiting evidence-based data. An updated picture of the situation with newly marketed medications is needed. We aimed to describe (1) the recommendations specific to older adults in monographs of newly marketed medications; (2) the representation of older adults in clinical trials of those medications. METHODS: In November 2020, we listed all medications that received a notice of compliance from Health Canada between January 2006 and September 2020, excluding those with indications irrelevant to community-dwelling older adults and locally acting medications. We assessed the availability and clarity of recommendations in monographs regarding older adults. Using Clinicaltrials.gov, we identified randomized controlled double-blind Phase III-IV trials led in Canada/United States of a sample of 30 commonly used medications among those previously listed. We extracted information on study design, participants, and efficacy/safety analysis specific to older patients. We used simple linear regression and Chi-square/Fisher's exact tests to analyze time trends in the representation of older adults over different periods. RESULTS: A total of 195 monographs were included. Of the 130 monographs reporting a dosing recommendation in older adults, 53 (41%) also reported limited/insufficient data in this population or its subgroups. Of the 373 trials included, 217 (58%) did not integrate a maximum age as an inclusion criterion. However, only 113 (30%) reported including a proportion of older adults representative (or over-representative) of the Canadian older population. Most trials (n = 289; 78%) did not provide efficacy or safety data specific to older adults. In our sample, the number/proportion of older adults in trials seemed to be increasingly reported over time, either explicitly or implicitly (e.g., inclusion criterion specifies <65 years old). CONCLUSIONS: Newly marketed medications still appear to under-represent older adults. The resulting lack of clear recommendations in monographs compromises evidence-based practice, thereby perpetuating the risk to older adults' health.

How does deprescribing (not) reduce mortality? A review of a meta-analysis in community-dwelling older adults casts uncertainty over claimed benefits.

Some meta-analyses suggest that deprescribing may reduce mortality. Our aim was to determine the underlying factors contributing to this observed reduction. We analysed data from 12 randomized controlled trials included in the latest meta-analysis on deprescribing in community-dwelling older adults. Our analysis focused on deprescribed medications and potential methodological concerns. Only a third (4/12) of the trials aimed to study mortality, and that too as a secondary outcome. Five trials reported a reduction in total medications, potentially inappropriate medications or drug-related problems. Information on specific classes of deprescribed medications was limited, although a wide array was concerned (e.g., antihypertensive, sedative, gastro-intestinal medications and vitamins). Follow-up periods were ≤1 year in 11 trials, and five trials included ≤150 participants. Small sample sizes often resulted in imbalanced groups (e.g., comorbidities, number of potentially inappropriate medications), yet no trials presented multivariable analyses. In the two trials with the most weight in the meta-analysis, several deaths occurred before the intervention, making it difficult to draw conclusions about the impact of the deprescribing intervention on mortality. These methodological issues cast significant uncertainty on the benefits of deprescribing on mortality outcomes. Large-scale, well-designed trials are needed to address this issue effectively.

Psychotropic medication use pre and post-diagnosis of cluster B personality disorder: a Quebec's health services register cohort.

Background: Cluster B personality disorders (PDs) are considered some of the most severe mental health conditions. Scarce evidence exists about the real-world utilization of psychotropics for cluster B PD individuals. Objective: We aimed to uncover trends and patterns of psychotropic medication use among individuals diagnosed with cluster B PD in the year before and after their diagnosis and to identify factors associated with medication use in a large cohort of individuals newly diagnosed with cluster B PDs. Methods: We conducted a population-based observational study using Quebec's health services register. We identified Quebec residents aged ≥14 years and insured with the provincial drug plan with a first diagnosis of cluster B PD recorded between April 1, 2002, and March 31, 2019. Cluster B PD was defined with ICD-9/10 diagnostic codes. We retrieved all claims for the main psychotropic medication classes: antipsychotics, antidepressants, anxiolytics, mood stabilizers, and attention-deficit/hyperactivity disorder (ADHD) medications. We calculated the proportion of individuals exposed to these medication classes and analyzed trends over the years using robust Poisson regression models, adjusting for potential confounders. We used robust Poisson regression to identify factors associated with medication class use. Results: We identified 87,778 new cases of cluster B PD, with a mean age of 44.5 years; 57.5% were women. Most frequent psychiatric comorbidities in the five years before cluster B PD diagnosis were depression (50.9%), anxiety (49.7%), and psychotic disorders (37.5%). Most individuals (71.0%) received at least one psychotropic during the year before cluster B PD diagnosis, and 78.5% received at least one of these medications in the subsequent year. The proportion of users increased after the diagnosis for antidepressants (51.6-54.7%), antipsychotics (35.9-45.2%), mood stabilizers (14.8-17.0%), and ADHD medications (5.1-5.9%), and remained relatively stable for anxiolytics (41.4-41.7%). Trends over time showed statistically significant increased use of antipsychotics and ADHD medications, decreased use of anxiolytics and mood stabilizers, and a stable use of antidepressants. Conclusion: Psychotropic medication use is highly prevalent among cluster B PD individuals. We observed an increase in medication use in the months following the diagnosis, particularly for antipsychotics, antidepressants, and mood stabilizers.

The impact of team-based primary care on medication-related outcomes in older adults: A comparative analysis of two Canadian provinces.

Objective: To evaluate if access to team-based primary care is related to medication management outcomes for older adults. Methods: We completed two retrospective cohort studies using administrative health data for older adults (66+) in Ontario (n = 428,852) and Québec (n = 310,198) who were rostered with a family physician (FP) between the 2001/02 and 2017/18 fiscal years. We generated matched comparison groups of older adults rostered to an FP practicing in a team-based model, and older adults rostered to an FP in a non-team model. We compared the following outcomes between these groups: any adverse drug reactions (ADRs), any potentially inappropriate prescription (PIP), and polypharmacy. Average treatment effects of access to team-based care were estimated using a difference-in-differences estimator. Results: The risk of an ADR was 22 % higher (RR = 1.22, 95 % CI = 1.18, 1.26) for older adults rostered to a team-based FP in Québec and 6 % lower (RR = 0.943, 95 % CI = 0.907, 0.978) in Ontario. However, absolute risk differences were less than 0.5 %. Differences in the risk of polypharmacy were small in Québec (RR = 1.005, 95 % CI = 1.001, 1.009) and Ontario (RR = 1.004, 95 % CI = 1.001, 1.007) and had absolute risk differences of less than 1 % in both provinces. Effects on PIP were not statistically or clinically significant in adjusted models. Interpretation: We did not find evidence that access to team-based primary care in Ontario or Québec meaningfully improved medication management outcomes for older adults.

Marginal structural models with latent class growth analysis of treatment trajectories: Statins for primary prevention among older adults.

Latent class growth analysis is increasingly proposed as a solution to summarize the observed longitudinal treatment into a few distinct groups. When latent class growth analysis is combined with standard approaches like Cox proportional hazards models, confounding bias is not properly addressed because of time-varying covariates that have a double role of confounders and mediators. We propose to use latent class growth analysis to classify individuals into a few latent classes based on their medication adherence pattern, then choose a working marginal structural model that relates the outcome to these groups. The parameter of interest is defined as a projection of the true marginal structural model onto the chosen working model. Simulation studies are used to illustrate our approach and compare it with unadjusted, baseline covariates adjusted, time-varying covariates adjusted, and inverse probability of trajectory groups weighted adjusted models. Our proposed approach yielded estimators with little or no bias and appropriate coverage of confidence intervals in these simulations. We applied our latent class growth analysis and marginal structural model approach to a database comprising information on 52,790 individuals from the province of Quebec, Canada, aged more than 65 and who were statin initiators to estimate the effect of statin-usage trajectories on a first cardiovascular event.

Sex-specific medication trajectories in older adults newly diagnosed with diabetes.

Background: People with diabetes tend to use many medications to treat diabetes and comorbidities. Nevertheless, the evolution of polypharmacy in newly diagnosed males and females has been little studied. Objective: The objective of this paper was to identify and describe medication trajectories in incident diabetes cases according to sex. Methods: Data were obtained from the Quebec Integrated Chronic Disease Surveillance System. We built a population-based cohort of community-dwelling individuals aged >65 years diagnosed with diabetes in 2014 who were alive and covered with the public drug plan until March 31, 2019. Latent class models were used to identify medication trajectory groups in males and females separately. Results: Of the 10,363 included individuals, 51.4% were males. Females were older and more likely to have more medication claims than males. Four trajectory groups were identified for males and five for females. Most trajectories showed sustained and stable number of medications over time. For each sex, only one of the trajectory groups included a mean annual number of medications lesser than five. Slight increasing trends of medication use were detected in the trajectories composed of very high users, which included older, more comorbid individuals frequently exposed to potentially inappropriate medications. Conclusions: Most males and females with incident diabetes had a high burden of medication following the year of diagnosis and were classified in a group of sustained medication use over time. The largest increase in medication was among those who had higher level of polypharmacy of questionable quality at baseline, raising concerns about the innocuity of such medication trajectories.

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.

A Proposed Curricular Framework for an Interprofessional Approach to Deprescribing.

Deprescribing involves reducing or stopping medications that are causing more harm than good or are no longer needed. It is an important approach to managing polypharmacy, yet healthcare professionals identify many barriers. We present a proposed pre-licensure competency framework that describes essential knowledge, teaching strategies, and assessment protocols to promote interprofessional deprescribing skills. The framework considers how to involve patients and care partners in deprescribing decisions. An action plan and example curriculum mapping exercise are included to help educators assess their curricula, and select and implement these concepts and strategies within their programs to ensure learners graduate with competencies to manage increasingly complex medication regimens as people age. Supplementary Information: The online version contains supplementary material available at 10.1007/s40670-022-01704-9.

Psychiatric and non-psychiatric polypharmacy among older adults with schizophrenia: Trends from a population-based study between 2000 and 2016.

Background: Schizophrenia is a severe psychiatric disorder associated with multiple psychiatric and non-psychiatric comorbidities. As adults with schizophrenia age, they may use many medications, i.e., have polypharmacy. While psychiatric polypharmacy is well documented, little is known about trends and patterns of global polypharmacy. This study aimed to draw a portrait of polypharmacy among older adults with schizophrenia from 2000 to 2016. Methods: This population-based cohort study was conducted using the data of the Quebec Integrated Chronic Disease Surveillance System of the National Institute of Public Health of Quebec to characterize recent trends and patterns of medication use according to age and sex. We identified all Quebec residents over 65 years with an ICD-9 or ICD-10 diagnosis of schizophrenia between 2000 and 2016. We calculated the total number of medications used by every individual each year and the age-standardized proportion of individuals with polypharmacy, as defined by the usage of 5+, 10+, 15+, and 20+ different medications yearly. We identified the clinical and socio-demographic factors associated with polypharmacy using robust Poisson regression models considering the correlation of the responses between subjects and analyzed trends in the prevalence of different degrees of polypharmacy. Results: From 2000 to 2016, the median number of medications consumed yearly rose from 8 in 2000 to 11 in 2016. The age-standardized proportion of people exposed to different degrees of polypharmacy also increased from 2000 to 2016: 5+ drugs: 76.6%-89.3%; 10+ drugs: 36.9%-62.2%; 15+: 13.3%-34.4%; 20+: 3.9%-14.4%. Non-antipsychotic drugs essentially drove the rise in polypharmacy since the number of antipsychotics remained stable (mean number of antipsychotics consumed: 1.51 in 2000 vs. 1.67 in 2016). In the multivariate regression, one of the main clinically significant factor associated with polypharmacy was the number of comorbidities (e.g., Polypharmacy-10+: RR[2 VS. 0-1] = 1.4; 99% IC:1.3-1.4, RR[3-4] = 1.7 (1.7-1.8); RR[5+] = 2.1 (2.1-2.2); Polypharmacy-15+: RR[2 VS 0-1] = 1.6; 99% IC:1.5-1.7, RR[3-4] = 2.5 (2.3-2.7); RR[5+] = 4.1 (3.8-4.5). Conclusion: There was a noticeable increase in polypharmacy exposure among older adults with schizophrenia in recent years, mainly driven by non-antipsychotic medications. This raises concerns about the growing risks for adverse effects and drug-drug interactions in this vulnerable population.

Sensitivity and specificity of algorithms for the identification of nonspecific low back pain in medico-administrative databases.

ABSTRACT: Identifying nonspecific low back pain (LBP) in medico-administrative databases is a major challenge because of the number and heterogeneity of existing diagnostic codes and the absence of standard definitions to use as reference. The objective of this study was to evaluate the sensitivity and specificity of algorithms for the identification of nonspecific LBP from medico-administrative data using self-report information as the reference standard. Self-report data came from the PROspective Québec Study on Work and Health , a 24-year prospective cohort study of white-collar workers. All diagnostic codes that could be associated with nonspecific LBP were identified from the International Classification of Diseases, Ninth and Tenth Revisions ( ICD-9 and ICD-10 ) in physician and hospital claims. Seven algorithms for identifying nonspecific LBP were built and compared with self-report information. Sensitivity analyses were also conducted using more stringent definitions of LBP. There were 5980 study participants with (n = 2847) and without (n = 3133) LBP included in the analyses. An algorithm that included at least 1 diagnostic code for nonspecific LBP was best to identify cases of LBP in medico-administrative data with sensitivity varying between 8.9% (95% confidence interval [CI] 7.9-10.0) for a 1-year window and 21.5% (95% CI 20.0-23.0) for a 3-year window. Specificity varied from 97.1% (95% CI 96.5-97.7) for a 1-year window to 90.4% (95% CI 89.4-91.5) for a 3-year window. The low sensitivity we found reveals that the identification of nonspecific cases of LBP in administrative data is limited, possibly due to the lack of traditional medical consultation.