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How do contraindications to non-opioid analgesics and opioids affect the likelihood that patients with back pain diagnoses in the primary care setting receive an opioid prescription? An observational cross-sectional study

dc.contributor.authorKeller, Michelle S.
dc.contributor.authorTruong, Lyna
dc.contributor.authorMays, Allison M.
dc.contributor.authorNeedleman, Jack
dc.contributor.authorHeilemann, Mary S. V.
dc.contributor.authorNuckols, Teryl K.
dc.date.accessioned2022-08-10T18:00:57Z
dc.date.available2022-08-10T18:00:57Z
dc.date.issued2021-02-20
dc.identifier.citationBMC Family Practice. 2021 Feb 20;22(1):41
dc.identifier.urihttps://doi.org/10.1186/s12875-021-01386-z
dc.identifier.urihttps://hdl.handle.net/2027.42/173453en
dc.description.abstractAbstract Background Given the risks of opioids, clinicians are under growing pressure to treat pain with non-opioid medications. Yet non-opioid analgesics such as non-steroidal anti-inflammatory drugs (NSAIDs) have their own risks: patients with kidney disease or gastrointestinal diseases can experience serious adverse events. We examined the likelihood that patients with back pain diagnoses and contraindications to NSAIDs and opioids received an opioid prescription in primary care. Methods We identified office visits for back pain from 2012 to 2017 and sampled the first office visit per patient per year (N = 24,543 visits). We created indicators reflecting contraindications for NSAIDs (kidney, liver, cardiovascular/cerebrovascular, and gastrointestinal diseases; concurrent or chronic use of anticoagulants/antiplatelets, chronic corticosteroid use) and opioids (depression, anxiety, substance use (SUD) and bipolar disorders, and concurrent benzodiazepines) and estimated four logistic regression models, with the one model including all patient visits and models 2–4 stratifying for previous opioid use. We estimated the population attributable risk for each contraindication. Results In our model with all patients-visits, patients received an opioid prescription at 4% of visits. The predicted probability (PP) of receiving an opioid was 4% without kidney disease vs. 7% with kidney disease; marginal effect (ME): 3%; 95%CI: 1–4%). For chronic or concurrent anticoagulant/antiplatelet prescriptions, the PPs were 4% vs. 6% (ME: 2%; 95%CI: 1–3%). For concurrent benzodiazepines, the PPs were 4% vs. 11% (ME: 7%, 95%CI: 5–9%) and for SUD, the PPs were 4% vs. 5% (ME: 1%, 95%CI: 0–3%). For the model including patients with previous long-term opioid use, the PPs for concurrent benzodiazepines were 25% vs. 24% (ME: -1%; 95%CI: − 18-16%). The population attributable risk (PAR) for NSAID and opioid contraindications was small. For kidney disease, the PAR was 0.16% (95%CI: 0.08–0.23%), 0.44% (95%CI: 0.30–0.58%) for anticoagulants and antiplatelets, 0.13% for substance use (95%CI: 0.03–0.22%) and 0.20% for concurrent benzodiazepine use (95%CI: 0.13–0.26%). Conclusions Patients with diagnoses of kidney disease and concurrent use of anticoagulants/antiplatelet medications had a higher probability of receiving an opioid prescription at a primary care visit for low back pain, but these conditions do not explain a large proportion of the opioid prescriptions.
dc.titleHow do contraindications to non-opioid analgesics and opioids affect the likelihood that patients with back pain diagnoses in the primary care setting receive an opioid prescription? An observational cross-sectional study
dc.typeJournal Article
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/173453/1/12875_2021_Article_1386.pdf
dc.identifier.doihttps://dx.doi.org/10.7302/5184
dc.language.rfc3066en
dc.rights.holderThe Author(s)
dc.date.updated2022-08-10T18:00:56Z
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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