Importance: New approaches are needed to provide care for individuals with problematic opioid use (POU). Rapid access addiction medicine (RAAM) clinics offer a flexible, low-barrier, rapid access care model for this population.
Objective: To assess the associations of RAAM clinics with emergency department (ED) visits, hospitalizations, and mortality for people with POU.
Design, Setting, And Participants: A retrospective cohort study involving a matched control group was performed using health administrative data from Ontario, Canada. Anonymized data from 4 Ontario RAAM clinics (cities of Ottawa, Toronto, Oshawa, and Sudbury) were linked with health administrative data. Analyses were performed on a cohort of individuals who received care at participating RAAM clinics and geographically matched controls who did not receive care at a RAAM clinic. All visits occurred between October 2, 2017, and October 30, 2019, and data analyses were completed in spring 2023. A propensity score-matching approach was used to balance confounding factors between groups, with adjustment for covariates that remained imbalanced after matching.
Exposures: Individuals who initiated care through the RAAM model (including assessment, pharmacotherapy, brief counseling, harm reduction, triage to appropriate level of care, navigation to community services and primary care, and related care) were compared with individuals who did not receive care through the RAAM model.
Main Outcomes And Measures: The primary outcome was a composite measure of ED visits for any reason, hospitalization for any reason, and all-cause mortality (all measured up to 30 days after index date). Outcomes up to 90 days after index date, as well as outcomes looking at opioid-related ED visits and hospitalizations, were also assessed.
Results: In analyses of the sample of 876 patients formed using propensity score matching, 440 in the RAAM group (mean [SD] age, 36.5 [12.6] years; 276 [62.7%] male) and 436 in the control group (mean [SD] age, 36.8 [13.8] years; 258 [59.2%] male), the pooled odds ratio (OR) for the primary, 30-day composite outcome of all-cause ED visit, hospitalization, or mortality favored the RAAM model (OR, 0.68; 95% CI, 0.50-0.92). Analysis of the same outcome for opioid-related reasons only also favored the RAAM intervention (OR, 0.47; 95% CI, 0.29-0.76). Findings for the individual events of hospitalization, ED visit, and mortality at both 30-day and 90-day follow-up also favored the RAAM model, with comparisons reaching statistical significance in most cases.
Conclusions And Relevance: In this cohort study of individuals with POU, RAAM clinics were associated with reductions in ED visits, hospitalizations, and mortality. These findings provide valuable evidence toward a broadened adoption of the RAAM model in other regions of North America and beyond.
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http://dx.doi.org/10.1001/jamanetworkopen.2023.44528 | DOI Listing |
Health Care Transit
February 2024
Department of Pediatrics, University of Southern California Keck School of Medicine, Los Angeles, CA, USA.
Limited evidence exists that serves to guide the field of practice and research pertaining to the long-term issues and needs of adults with spina bifida. Understanding the lived experience of adults with spina bifida has lagged behind considerably resulting in limited evidence-based guidance for individuals with spina bifida and their families and the health care professionals who provide services to this population. Given the paucity of knowledge of the lived experience as it pertains to adulthood, this scoping review was undertaken.
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December 2024
Department of Clinical Pharmacology, Hospital Pharmacy, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.
This work focusses on extending the deep compartment model (DCM) framework to the estimation of mixed-effects. By introducing random effects, model predictions can be personalized based on drug measurements, enabling the testing of different treatment schedules on an individual basis. The performance of classical first-order (FO and FOCE) and machine learning based variational inference (VI) algorithms were compared in a simulation study.
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June 2024
IInd Department of Dermatology, Colentina Clinical Hospital, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania.
Psoriasis is a common, life-long skin disease with a significant negative health and societal impact. Data on rates of disease control and treatment strategies are lacking in Central and Eastern European countries. We aimed to describe the real-world disease severity, control, and treatment strategies for psoriasis in patients from Central and Eastern European countries.
View Article and Find Full Text PDFExp Dermatol
April 2024
Department of Dermatology and Venereology, Institute of Clinical Medicine, University of Tartu, Tartu, Estonia.
J Pharmacokinet Pharmacodyn
August 2024
Department of Clinical Pharmacology, Hospital Pharmacy, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.
Conventional pharmacokinetic (PK) models contain several useful inductive biases guiding model convergence to more realistic predictions of drug concentrations. Implementing similar biases in standard neural networks can be challenging, but might be fundamental for model robustness and predictive performance. In this study, we build on the deep compartment model (DCM) architecture by introducing constraints that guide the model to explore more physiologically realistic solutions.
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