Journal of the American Medical Directors Association · 2025
Development of a Model to Predict the Risk of Chronic Opioid Use After Entry Into Long-Term Care Facilities.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Thuraisingam Sharmala, Eshetie Tesfahun C, Caughey Gillian E, Sluggett Janet K, Whitehead Craig, Crotty Maria, Corlis Megan, Visvanathan Renuka, Inacio Maria C
Аннотация
OBJECTIVES: Chronic opioid use is common in residents of long-term care facilities (LTCFs) and is associated with an increased risk of falls, fractures, and cognitive impairment. However, predictors of chronic opioid use in this cohort remain unclear. This study developed a prediction model for new chronic opioid use within 1 year of entry into LTCFs and identifies key predictors.
DESIGN: This study was a retrospective cohort analysis using data from the Registry of Senior Australians National Historical Cohort.
SETTING AND PARTICIPANTS: The cohort included non-Indigenous individuals 65 years and older who entered an LTCF in South Australia, Victoria, New South Wales, or Queensland between 2009 and 2019 who were not in palliative care and not a chronic opioid user before entry.
METHODS: Time to chronic opioid use within 1 year of entry was modeled using competing risk regression. Candidate predictors included individual, health care, medication, facility, and system-related factors. Model discrimination (C-index), calibration, and clinical utility were assessed.
RESULTS: Among 355,208 individuals (median age 85 years, 61% women, 54% with dementia), 7% (n = 25,171) became chronic opioid users. The prediction model had a C-index of 0.75 (95% CI, 0.74-0.76) and its calibration was acceptable. Eighteen predictors were identified, the strongest were nonchronic opioid use before entry, high medication assistance rating, history of pain, complex health care needs, and high sedative load.
CONCLUSION AND IMPLICATIONS: A good predictive ability and clinical utility model was developed for estimating the risk of chronic opioid use in new LTCF residents. Identifying residents at high risk of chronic opioid use at entry into long-term can guide targeted interventions for pain management and opioid stewardship initiatives.
DESIGN: This study was a retrospective cohort analysis using data from the Registry of Senior Australians National Historical Cohort.
SETTING AND PARTICIPANTS: The cohort included non-Indigenous individuals 65 years and older who entered an LTCF in South Australia, Victoria, New South Wales, or Queensland between 2009 and 2019 who were not in palliative care and not a chronic opioid user before entry.
METHODS: Time to chronic opioid use within 1 year of entry was modeled using competing risk regression. Candidate predictors included individual, health care, medication, facility, and system-related factors. Model discrimination (C-index), calibration, and clinical utility were assessed.
RESULTS: Among 355,208 individuals (median age 85 years, 61% women, 54% with dementia), 7% (n = 25,171) became chronic opioid users. The prediction model had a C-index of 0.75 (95% CI, 0.74-0.76) and its calibration was acceptable. Eighteen predictors were identified, the strongest were nonchronic opioid use before entry, high medication assistance rating, history of pain, complex health care needs, and high sedative load.
CONCLUSION AND IMPLICATIONS: A good predictive ability and clinical utility model was developed for estimating the risk of chronic opioid use in new LTCF residents. Identifying residents at high risk of chronic opioid use at entry into long-term can guide targeted interventions for pain management and opioid stewardship initiatives.