Faculty Bibliography

To address the epidemic of opioid misuse and overdose, the New York City Department of Health and Mental Hygiene partnered with an expert panel of emergency medicine physicians to develop voluntary guidelines for judicious prescribing of opioids upon discharge from an emergency department. A qualitative evaluation of the guidelines was conducted using semistructured interviews with emergency department directors and providers. The guidelines were widely supported by respondents and cited as helpful in easing difficult negotiations with patients requesting opioids. Involvement of the expert panel in development of guidelines was particularly valuable in ensuring their credibility. Health departments should consider partnering with emergency physicians to promote the public health goal of judicious opioid prescribing.

The risk of severe precipitated opioid withdrawal (POW) is amplified when precipitated by a long-acting opioid antagonist. IM extended release naltrexone (XRNTX;Vivitrol®) is an FDA approved therapy to prevent relapse of opioid and alcohol abuse. Two cases of precipitated opioid withdrawal from XRNTX are presented that illustrate different patient reactions to POW. A 56-year-old woman developed a hypertensive emergency and required continuous intravenous vasodilator, clonidine, and intensive care monitoring after re-initiation of XRNTX following opioid relapse. A 25-year-old man developed agitation and altered mental status after receipt of XRNTX at the conclusion of a twelve-day detoxification program during which he continued surreptitious use of heroin. The patient received benzodiazepines and haloperidol without adequate affect, and required intubation with propofol, lorazepam, and dexmedetomidine infusions. Management of POW from XRNTX is a challenge to emergency providers and protocols to guide management do not exist. Recommended therapies include intravenous fluids, anti-emetics, clonidine, or benzodiazepines as well as therapy tailored to the organ system affected. To minimize risk of POW it is important for providers instituting XRNTX to adhere to the manufacturers warnings and clinic protocols including a naloxone challenge and ensure an adequate opioid free period prior to administration of XRNTX.

BACKGROUND:The misuse of prescription opioids (MUPO) is a leading public health concern. Social media are playing an expanded role in public health research, but there are few methods for estimating established epidemiological metrics from social media. The purpose of this study was to demonstrate that the geographic variation of social media posts mentioning prescription opioid misuse strongly correlates with government estimates of MUPO in the last month. METHODS:We wrote software to acquire publicly available tweets from Twitter from 2012 to 2014 that contained at least one keyword related to prescription opioid use (n = 3,611,528). A medical toxicologist and emergency physician curated the list of keywords. We used the semantic distance (SemD) to automatically quantify the similarity of meaning between tweets and identify tweets that mentioned MUPO. We defined the SemD between two words as the shortest distance between the two corresponding word-centroids. Each word-centroid represented all recognized meanings of a word. We validated this automatic identification with manual curation. We used Twitter metadata to estimate the location of each tweet. We compared our estimated geographic distribution with the 2013-2015 National Surveys on Drug Usage and Health (NSDUH). RESULTS:Tweets that mentioned MUPO formed a distinct cluster far away from semantically unrelated tweets. The state-by-state correlation between Twitter and NSDUH was highly significant across all NSDUH survey years. The correlation was strongest between Twitter and NSDUH data from those aged 18-25 (r = 0.94, p < 0.01 for 2012; r = 0.94, p < 0.01 for 2013; r = 0.71, p = 0.02 for 2014). The correlation was driven by discussions of opioid use, even after controlling for geographic variation in Twitter usage. CONCLUSIONS:Mentions of MUPO on Twitter correlate strongly with state-by-state NSDUH estimates of MUPO. We have also demonstrated that a natural language processing can be used to analyze social media to provide insights for syndromic toxicosurveillance.