CONTEXT: Pain is common in nursing home settings. OBJECTIVES: To describe scheduled analgesic use among nursing home (NH) residents experiencing non-cancer pain and evaluate factors associated with scheduled analgesic use. METHODS: We identified 2508 residents living in one of 185 NHs predominantly from one for-profit chain, with pain recorded on two consecutive Minimum Data Set assessments. Pharmacy transaction files provided detailed medication information. Logistic regression models adjusted for clustering of residents in NHs identified factors related to scheduled prescription analgesics. RESULTS: Twenty-three percent had no scheduled analgesics prescribed. Those with scheduled analgesics were more likely to have excruciating pain (5.5% vs. 1.2%) and moderate pain documented (64.7% vs. 47.5%) than residents without scheduled analgesics. Hydrocodone (41.7%), short-acting oxycodone (16.6%), and long-acting fentanyl (9.4%) were common, and 13.8% reported any nonsteroidal anti-inflammatory agent use. Factors associated with decreased odds of scheduled analgesics included severe cognitive impairment (adjusted odds ratio [AOR] 0.56; 95% confidence interval [CI] 0.36 to 0.88), age more than 85 years (AOR 0.57; 95% CI 0.41 to 0.80), and Parkinson's disease (AOR 0.55; 95% CI 0.30 to 0.99). Factors associated with increased odds of scheduled analgesic use included history of fracture (AOR 1.79; 95% CI 1.16 to 2.76), diabetes (AOR 1.30; 95% CI 1.02 to 1.66), and higher Minimum Data Set mood scores (AOR 1.11; 95% CI 1.04 to 1.19). CONCLUSION: Some improvements in pharmacologic management of pain in NHs have been realized. Yet, presence of pain without scheduled analgesics prescribed was still common. Evidence-based procedures to assure adherence to clinical practice guidelines for pain management in this setting are warranted.
CONTEXT: Pain is common in nursing home settings. OBJECTIVES: To describe scheduled analgesic use among nursing home (NH) residents experiencing non-cancer pain and evaluate factors associated with scheduled analgesic use. METHODS: We identified 2508 residents living in one of 185 NHs predominantly from one for-profit chain, with pain recorded on two consecutive Minimum Data Set assessments. Pharmacy transaction files provided detailed medication information. Logistic regression models adjusted for clustering of residents in NHs identified factors related to scheduled prescription analgesics. RESULTS: Twenty-three percent had no scheduled analgesics prescribed. Those with scheduled analgesics were more likely to have excruciating pain (5.5% vs. 1.2%) and moderate pain documented (64.7% vs. 47.5%) than residents without scheduled analgesics. Hydrocodone (41.7%), short-acting oxycodone (16.6%), and long-acting fentanyl (9.4%) were common, and 13.8% reported any nonsteroidal anti-inflammatory agent use. Factors associated with decreased odds of scheduled analgesics included severe cognitive impairment (adjusted odds ratio [AOR] 0.56; 95% confidence interval [CI] 0.36 to 0.88), age more than 85 years (AOR 0.57; 95% CI 0.41 to 0.80), and Parkinson's disease (AOR 0.55; 95% CI 0.30 to 0.99). Factors associated with increased odds of scheduled analgesic use included history of fracture (AOR 1.79; 95% CI 1.16 to 2.76), diabetes (AOR 1.30; 95% CI 1.02 to 1.66), and higher Minimum Data Set mood scores (AOR 1.11; 95% CI 1.04 to 1.19). CONCLUSION: Some improvements in pharmacologic management of pain in NHs have been realized. Yet, presence of pain without scheduled analgesics prescribed was still common. Evidence-based procedures to assure adherence to clinical practice guidelines for pain management in this setting are warranted.
Authors: Jacob N Hunnicutt; Stavroula A Chrysanthopoulou; Christine M Ulbricht; Anne L Hume; Jennifer Tjia; Kate L Lapane Journal: J Am Geriatr Soc Date: 2017-09-21 Impact factor: 5.562
Authors: Kevin M Fain; Carlos Castillo-Salgado; David D Dore; Jodi B Segal; Andrew R Zullo; G Caleb Alexander Journal: J Am Med Dir Assoc Date: 2016-10-06 Impact factor: 4.669
Authors: Toby O Smith; Rachel Purdy; Sarah K Latham; Sarah R Kingsbury; Graham Mulley; Philip G Conaghan Journal: Rheumatol Int Date: 2015-08-06 Impact factor: 2.631