Geographic Variation in the Initiation of Commonly Used Opioids and Dosage Strength in United States Nursing Homes. Issue 10 (October 2018) - Hunnicutt, Jacob N.; Baek, Jonggyu; Alcusky, Matthew; Hume, Anne L.; Liu, Shao-Hsien; Ulbricht, Christine M.; Tjia, Jennifer; Lapane, Kate L.
Abstract : Objectives: To examine and quantify geographic variation in the initiation of commonly used opioids and prescribed dosage strength among older US nursing home residents. Methods: We merged 2011 Minimum Data Set 3.0 to Medicare claims and facility characteristics data to conduct a cross-sectional study among long-stay nursing home residents who initiated short-acting opioids commonly used in nursing homes (oxycodone, hydrocodone, or tramadol). We examined geographic variation in specific opioids initiated and potentially inappropriate doses (≥50 mg oral morphine equivalent/d) across hospital referral regions (HRRs). Multilevel logistic models quantified the proportional change in between-HRR variation and associations between commonly initiated opioids and inappropriate doses after adjusting for resident characteristics, facility characteristics, and state. Results: Oxycodone (9.4%) was initiated less frequently than hydrocodone (56.2%) or tramadol (34.5%) but varied dramatically between HRRs (range, 0%–74.5%). In total, resident/facility characteristics and state of residence, respectively explained 84.1%, 58.2%, 59.1%, and 46.6% of the between-HRR variation for initiating oxycodone, hydrocodone, tramadol, and inappropriate doses. In all cases, state explained the largest proportion of between-HRR variation. Relative to hydrocodone, residents initiating oxycodone were more likely (adjusted odds ratio, 5.00; 95% confidence interval, 4.57–5.47) and those initiating tramadol were less likely (adjusted odds ratio, 0.28; 95% confidence interval, 0.25–0.31) to be prescribed potentially inappropriately high doses. Conclusions: We documented extensive geographic variation in the opioid and dose initiated for nursing home residents, with state explaining the largest proportion of the observed variation. Further work is needed to understand potential drivers of opioid prescribing patterns at the state level. Abstract : Supplemental Digital Content is available in the text.