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Objective Frequent users represent a small proportion of emergency department users, but they account for a disproportionately large number of visits. Their use of emergency departments is often considered suboptimal. It would be more efficient to identify and treat those patients earlier in their health problem trajectory. It is therefore essential to describe their characteristics and to predict their emergency department use. In order to do so, adequate statistical tools are needed. The objective of this study was to determine the statistical tools used in identifying variables associated with frequent use or predicting the risk of becoming a frequent user. Methods We performed a scoping review following an established 5-stage methodological framework. We searched PubMed, Scopus and CINAHL databases in February 2019 using search strategies defined with the help of an information specialist. Out of 4534 potential abstracts, we selected 114 articles based on defined criteria and presented in a content analysis. Results We identified four classes of statistical tools. Regression models were found to be the most common practice, followed by hypothesis testing. The logistic regression was found to be the most used statistical tool, followed by χ² test and t-test of associations between variables. Other tools were marginally used. Conclusions This scoping review lists common statistical tools used for analysing frequent users in emergency departments. It highlights the fact that some are well established while others are much less so. More research is needed to apply appropriate techniques to health data or to diversify statistical point of views. [ABSTRACT FROM AUTHOR]

Context The advanced access (AA) model is based on several core pillars, including balancing appointment supply and demand, regularly adjusting supply, optimizing appointment systems and collaboration practices. Exposure of family medicine resident to AA within university family medicine groups (U-FMGs) is a promising strategy to widen its dissemination. It is also essential to reflect on aspects of the model that could be adopted as well as those requiring adaptation to improve the residency experience. Objective Determine compatibility of U-FMG residency programs with AA pillars. Study design and Analysis Cross-sectional survey of local residency program characteristics with respect to AA pillars. Program compatibility with 4 AA pillars was categorized inductively by a research team that included clinicians, AA experts, a residency program expert and 4 family medicine residents. Setting 46 U-FMGs in Quebec, Canada Population studied The chief resident and academic director of each U-FMG Instrument A de novo online survey questionnaire piloted with 3 former chief residents. The survey included 32 questions about family group practices, residency rotation programs, opportunities to collaborate with other professionals and training received on AA. The questionnaire and 2 reminders were sent by email to all respondents. Outcome measures Characteristics of residency programs were grouped by AA pillar. A three-level score (compatible, moderately compatible, or not very compatible with the principles of AA) was assigned to each group of characteristics of local U-FMG residency programs. Results 38 of 46 U-FMGs participated (82.6%). No U-FMG obtained a score of compatible for all 4 pillars considered. Balancing appointment supply and demand appeared to be adequate for >70% of U-FMGs. However, 60% of U-FMG appointment systems were not very compatible with the AA model, mostly because the proportion of the schedule reserved for urgent appointments was insufficient. Opportunities for collaboration were compatible with AA principles in 32% of programs. Almost 66% of programs offered training on AA. Conclusions Our study highlights the heterogeneity among residency programs with respect to their compatibility with AA. Our theoretical approach limits the objective assessment of the impact on timely access for patients. A second part of the project correlating AA indicators with residency program characteristics is ongoing. [ABSTRACT FROM AUTHOR]

Background: Chronic non-cancer pain (CNCP) is common among frequent emergency department (ED) users, although factors underlying this association are unclear. This study estimated the association between sustained opioid use and frequent ED use among patients with CNCP., Methods: Retrospective cohort study using a Canadian provincial health insurer database (Régie d'Assurance Maladie du Québec). The database included adults with both ≥1 chronic condition and ≥ 1 ED visit in 2012 or 2013. Inclusion in the study further required a CNCP diagnosis, public drug insurance coverage and 1-year survival after the first ED visit in 2012 or 2013 (index visit). Multivariable logistic regression was used to derive ORs of frequent ED use (≥5 visits in the year following the index visit) subsequent to sustained opioid use (≥60 days opioids prescription within 90 days preceding the index visit), adjusting for important covariables., Results: From 576 688 patients in the database, 58 237 were included in the study. Of these, 4109 (7.1%) had received a sustained opioid prescription and 4735 (8.1%) were frequent ED users in the follow-up year. Sustained opioid use was not associated with frequent ED use in the multivariable model (OR: 1.06, 95% CI 0.94 to 1.19). Novel associated covariables were benzodiazepine prescription (OR: 1.21, 95% CI 1.12 to 1.30) and polypharmacy (OR: 1.23, 95% CI 1.13 to 1.34)., Conclusions: Due to confounding by social and medical vulnerability, patients with CNCP with sustained opioid use appear to have a higher propensity for frequent ED use in unadjusted models. However, sustained opioid use was not associated with frequent ED use in these patients after adjustment., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. No commercial re-use. See rights and permissions. Published by BMJ.)