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.

Care trajectories of individuals with anxiety disorders: A retrospective cohort study.

BACKGROUND: Anxiety disorders (ADs) are associated with increased healthcare use (HCU), and individuals may seek healthcare through various pathways according to clinical and individual characteristics. This study aimed to characterize care trajectories (CTs) of individuals with ADs. METHODS: This is a retrospective cohort study using the Care Trajectories - Enriched Data cohort, a linkage between the Canadian Community Health Surveys (CCHS), and health administrative data from Quebec. The cohort included 5143 respondents reporting ADs to the CCHS between 2009 and 2016. We measured CTs over 5 years before CCHS using a state sequence analysis. RESULTS: The cohort was categorized into five types of CTs. Type 1 (52.7 %) was the lowest care-seeking group, with fewer comorbidities. Type 2 (24.0 %) had higher levels of physical and mental health comorbidities and moderate HCU, mainly ambulatory visits to general practitioners. Type 3 (13.1 %) represented older patients with the highest level of physical illnesses and high HCU, predominantly ambulatory consultation of specialists other than psychiatrists. Types 4 and 5 combined young and middle-aged patients suffering from severe psychological distress. HCU of type 4 (6.7 %) was high, mainly consultations of ambulatory psychiatrists, and HCU of type 5 (3.5 %), was the highest and mostly in acute care. LIMITATIONS: Administrative and survey data may have coding errors, missing data and self-report biases. CONCLUSION: Five types of CTs showed distinct patterns of HCU often modulated by physical and mental health comorbidities, which emphasizes the importance of considering ADs when individuals seek care for other mental health conditions or physical illness.

Profiles of frequent emergency department users with chronic conditions: a latent class analysis.

OBJECTIVES: Frequent emergency department users represent a small proportion of users while cumulating many visits. Previously identified factors of frequent use include high physical comorbidity, mental health disorders, poor socioeconomic status and substance abuse. However, frequent users do not necessarily exhibit all these characteristics and they constitute a heterogeneous population. This study aims to establish profiles of frequent emergency department users in an adult population with chronic conditions. DESIGN: This is a retrospective cohort study using administrative databases. SETTING: All adults who visited the emergency department between 2012 and 2013 (index date) in the province of Quebec (Canada), diagnosed with at least one chronic condition, and without dementia were included. Patients living in remote areas and who died in the year following their index date were excluded. We used latent class analysis, a probability-based model to establish profiles of frequent emergency department users. Frequent use was defined as having five visits or more during 1 year. Patient characteristics included sociodemographic characteristics, physical and mental comorbidities and prior healthcare utilisation. RESULTS: Out of 4 51 775 patients who visited emergency departments at least once in 2012-2013, 13 676 (3.03%) were frequent users. Four groups were identified: (1) 'low morbidity' (n=5501, 40.2%), (2) 'high physical comorbidity' (n=3202, 23.4%), (3) 'injury or chronic non-cancer pain' (n=2313, 19.5%) and (4) 'mental health or alcohol/substance abuse' (n=2660, 16.9%). CONCLUSIONS: The four profiles have distinct medical and socioeconomic characteristics. These profiles provide useful information for developing tailored interventions that would address the specific needs of each type of frequent emergency department users.

Cardiovascular Health Peaks and Meteorological Conditions: A Quantile Regression Approach.

Cardiovascular morbidity and mortality are influenced by meteorological conditions, such as temperature or snowfall. Relationships between cardiovascular health and meteorological conditions are usually studied based on specific meteorological events or means. However, those studies bring little to no insight into health peaks and unusual events far from the mean, such as a day with an unusually high number of hospitalizations. Health peaks represent a heavy burden for the public health system; they are, however, usually studied specifically when they occur (e.g., the European 2003 heatwave). Specific analyses are needed, using appropriate statistical tools. Quantile regression can provide such analysis by focusing not only on the conditional median, but on different conditional quantiles of the dependent variable. In particular, high quantiles of a health issue can be treated as health peaks. In this study, quantile regression is used to model the relationships between conditional quantiles of cardiovascular variables and meteorological variables in Montreal (Canada), focusing on health peaks. Results show that meteorological impacts are not constant throughout the conditional quantiles. They are stronger in health peaks compared to quantiles around the median. Results also show that temperature is the main significant variable. This study highlights the fact that classical statistical methods are not appropriate when health peaks are of interest. Quantile regression allows for more precise estimations for health peaks, which could lead to refined public health warnings.

Persistent frequent emergency department users with chronic conditions: A population-based cohort study.

BACKGROUND: Frequent emergency department users are patients cumulating at least four visits per year. Few studies have focused on persistent frequent users, who maintain their frequent user status for multiple consecutive years. This study targets an adult population with chronic conditions, and its aims are: 1) to estimate the prevalence of persistent frequent ED use; 2) to identify factors associated with persistent frequent ED use (frequent use for three consecutive years) and compare their importance with those associated with occasional frequent ED use (frequent use during the year following the index date); and 3) to compare characteristics of "persistent frequent users" to "occasional frequent users" and to "users other than persistent frequent users". METHODS: This is a retrospective cohort study using Quebec administrative databases. All adult patients who visited the emergency department in 2012, diagnosed with chronic conditions, and living in non-remote areas were included. Patients who died in the three years following their index date were excluded. The main outcome was persistent frequent use (≥4 visits per year during three consecutive years). Potential predictors included sociodemographic characteristics, physical and mental comorbidities, and prior healthcare utilization. Odds ratios were computed using multivariable logistic regression. RESULTS: Out of 297,182 patients who visited ED at least once in 2012, 3,357 (1.10%) were persistent frequent users. Their main characteristics included poor socioeconomic status, mental and physical comorbidity, and substance abuse. Those characteristics were also present for occasional frequent users, although with higher percentages for the persistent user group. The number of previous visits to the emergency department was the most important factor in the regression model. The occasional frequent users' attrition rate was higher between the first and second year of follow-up than between the second and third year. CONCLUSIONS: Persistent frequent users are a subpopulation of frequent users with whom they share characteristics, such as physical and mental comorbidities, though the former are poorer and younger. More research is needed in order to better understand what factors can contribute to persistent frequent use.