scholarly journals The opioid epidemic: how have buprenorphine waivered OB/GYNs impacted treatment availability in New York?

2022 ◽  
Vol 226 (1) ◽  
pp. S610-S611
Author(s):  
Khadijah Bland ◽  
Elaine L. Hill ◽  
Mira Chaskes ◽  
Neil S. Seligman
Keyword(s):  
New York ◽  
2018 ◽  
Vol 108 (12) ◽  
pp. 1621-1622 ◽  
Author(s):  
Yamilette Hernandez ◽  
Sarah Meyers-Ohki ◽  
Sarah Farkas ◽  
Samuel Ball ◽  
Kenneth Leonard ◽  
...  

2019 ◽  
Vol 6 (Supplement_2) ◽  
pp. S99-S99
Author(s):  
Chaorui Huang ◽  
David Lucero ◽  
Denise Paone ◽  
Ellenie Tuazon ◽  
Demetre Daskalakis

Abstract Background Along with a growing opioid epidemic nationwide, opioid users often have an increased risk of severe infectious diseases including endocarditis, osteomyelitis, and central nervous system (CNS) abscess. As the largest city in the United States, New York City (NYC) may serve as a study model for opioid use and infectious diseases. We investigated the association between opioid use and hospitalizations for endocarditis, osteomyelitis, and CNS abscess in NYC. Methods Data for NYC residents aged ≥18 years discharged from New York State hospitals during 2001–2014 were analyzed using a hospital discharge dataset. We defined a hospitalization for endocarditis, osteomyelitis, and CNS abscess as one with a principal or secondary diagnosis for these conditions within the discharge record. We identified opioid users by examining principal or secondary diagnoses for opioid use within the discharge record at the time of hospitalization for endocarditis, osteomyelitis, and CNS abscess. Log-binomial model was applied among all hospitalized patients using endocarditis, osteomyelitis, and CNS abscess as the outcome, adjusting for age, sex, race, and borough. Results During 2001–2014, there were 139,392 hospitalizations in total for endocarditis, osteomyelitis, or CNS abscess, of which 8,823 (6.3%) were among opioid users. There was an increased risk of hospitalization for endocarditis [RR: 2.6 (95% CI: 2.5–2.7)], osteomyelitis [RR: 1.1 (95% CI: 1.1–1.1)], and CNS abscesses [RR: 1.9 (95% CI: 1.8–2.1)] among hospitalized opioid users compared with hospitalized nonopioid users, adjusted by age, sex, race, and borough. Hospitalized opioid users had four times the risk for endocarditis hospitalization compared with hospitalized nonopioid users in the 18–44 year age group (RR: 4.2 [95% CI: 3.9–4.5]) (Table 1). Conclusion These results provide further evidence that opioid use is associated with an increased risk of endocarditis, osteomyelitis, and CNS abscess. Efforts to combat the opioid epidemic might lower the overall incidence of endocarditis, osteomyelitis, and CNS abscess. Disclosures All authors: No reported disclosures.


2017 ◽  
Vol 28 (4) ◽  
Author(s):  
Patricia Tooker

There is no “magic potion” or vaccine to prevent youth from using alcohol or other drugs. Adolescent substance abuse prevention programs have been largely ineffective because the messaging is taken for granted. Efforts based on theories of growth and development patterns, and are inclusive of strategies beyond the classroom and home, have demonstrated encouraging findings particularly when members of the community are involved. This paper will explore factors behind illicit substance use among youth in Staten Island, New York and how Wagner College is playing an important part of a collective impact initiative that is starting to make a difference.


10.2196/23426 ◽  
2021 ◽  
Vol 7 (4) ◽  
pp. e23426
Author(s):  
Anthony Xiang ◽  
Wei Hou ◽  
Sina Rashidian ◽  
Richard N Rosenthal ◽  
Kayley Abell-Hart ◽  
...  

Background Opioid overdose-related deaths have increased dramatically in recent years. Combating the opioid epidemic requires better understanding of the epidemiology of opioid poisoning (OP) and opioid use disorder (OUD). Objective We aimed to discover geospatial patterns in nonmedical opioid use and its correlations with demographic features related to despair and economic hardship, most notably the US presidential voting patterns in 2016 at census tract level in New York State. Methods This cross-sectional analysis used data from New York Statewide Planning and Research Cooperative System claims data and the presidential voting results of 2016 in New York State from the Harvard Election Data Archive. We included 63,958 patients who had at least one OUD diagnosis between 2010 and 2016 and 36,004 patients with at least one OP diagnosis between 2012 and 2016. Geospatial mappings were created to compare areas of New York in OUD rates and presidential voting patterns. A multiple regression model examines the extent that certain factors explain OUD rate variation. Results Several areas shared similar patterns of OUD rates and Republican vote: census tracts in western New York, central New York, and Suffolk County. The correlation between OUD rates and the Republican vote was .38 (P<.001). The regression model with census tract level of demographic and socioeconomic factors explains 30% of the variance in OUD rates, with disability and Republican vote as the most significant predictors. Conclusions At the census tract level, OUD rates were positively correlated with Republican support in the 2016 presidential election, disability, unemployment, and unmarried status. Socioeconomic and demographic despair-related features explain a large portion of the association between the Republican vote and OUD. Together, these findings underscore the importance of socioeconomic interventions in combating the opioid epidemic.


2020 ◽  
Author(s):  
Anthony Xiang ◽  
Sina Rashidian ◽  
Wei Hou ◽  
Richard N Rosenthal ◽  
Kayley Abell-Hart ◽  
...  

Background: Opioid overdose related deaths have increased dramatically in recent years. Combating the opioid epidemic requires better understanding of the epidemiology of opioid poisoning (OP) and opioid use disorder (OUD). Objective: We aimed to discover geospatial patterns in problematic opioid use and its correlations with demographic features related to despair and economic hardship, most notably the US presidential voting patterns in 2016 at census tract level in New York State. Methods: This cross-sectional analysis used data from New York Statewide Planning and Research Cooperative System claims data and the presidential voting results of 2016 in New York State from the Harvard Election Data Archive. We included 63,958 patients who had at least one opioid use disorder (OUD) diagnosis between 2010 and 2016, and 36,004 patients with at least one opioid poisoning (OP) diagnosis between 2012 and 2016. A logistic regression model was used to determine the associations between patient level characteristics (sex, age group, race, and payment type) and OUD and OP patient rates at census tract level. Results: Several areas shared similar patterns of OUD rates and Republican vote: census tracts in Western New York, Central New York, and Suffolk County. The Spearman rank correlation between OUD rates and the Republican vote was 0.38 (P < 0.0001). A multiple regression model of census tract level demographic and socioeconomic factors explains 29% of the variance in OUD rates, with disability and republican vote the biggest predictors. Conclusions: At the census tract level, opioid use disorder rates were positively correlated with Republican support in the 2016 presidential election, disability, unemployment, and unmarried status. Socioeconomic and demographic features explain a large portion of the association between the Republican vote and opioid use disorder. Together, these findings underscore the importance of socioeconomic interventions in combatting the opioid epidemic.


2020 ◽  
Author(s):  
Anthony Xiang ◽  
Wei Hou ◽  
Sina Rashidian ◽  
Richard N Rosenthal ◽  
Kayley Abell-Hart ◽  
...  

BACKGROUND Opioid overdose-related deaths have increased dramatically in recent years. Combating the opioid epidemic requires better understanding of the epidemiology of opioid poisoning (OP) and opioid use disorder (OUD). OBJECTIVE We aimed to discover geospatial patterns in nonmedical opioid use and its correlations with demographic features related to despair and economic hardship, most notably the US presidential voting patterns in 2016 at census tract level in New York State. METHODS This cross-sectional analysis used data from New York Statewide Planning and Research Cooperative System claims data and the presidential voting results of 2016 in New York State from the Harvard Election Data Archive. We included 63,958 patients who had at least one OUD diagnosis between 2010 and 2016 and 36,004 patients with at least one OP diagnosis between 2012 and 2016. Geospatial mappings were created to compare areas of New York in OUD rates and presidential voting patterns. A multiple regression model examines the extent that certain factors explain OUD rate variation. RESULTS Several areas shared similar patterns of OUD rates and Republican vote: census tracts in western New York, central New York, and Suffolk County. The correlation between OUD rates and the Republican vote was .38 (<i>P</i>&lt;.001). The regression model with census tract level of demographic and socioeconomic factors explains 30% of the variance in OUD rates, with disability and Republican vote as the most significant predictors. CONCLUSIONS At the census tract level, OUD rates were positively correlated with Republican support in the 2016 presidential election, disability, unemployment, and unmarried status. Socioeconomic and demographic despair-related features explain a large portion of the association between the Republican vote and OUD. Together, these findings underscore the importance of socioeconomic interventions in combating the opioid epidemic.


2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Candice Welhausen

ObjectiveI analyze a collection of data visualizations created during the crack and opioid epidemics, respectively, published by mainstream news media using three criteria: genre, subject matter, and language used to describe the graphic. I use precarity as a theoretical framework--that is, “a politically induced condition in which certain populations suffer from failing social and economic networks of support and become differentially exposed to injury, violence, and death” (Butler, 2009, p. 35)--to argue that visualizations created during the crack epidemic positioned addicts as criminals whereas opioid addicts have been positioned as patients in need of treatment.IntroductionIn late 2015, two economists studying health-related data inadvertently discovered an alarming trend: death rates for middle-aged, white Americans were dramatically increasing from drug overdoses (Kolata, 2015), particularly opioids (CDC, 2015). The opioid epidemic has since been widely publicized in the media. However, as critics have argued, the government's response to the crack epidemic differs dramatically from an arguably equally devastating “drug epidemic” that hit many inner US cities thirty years ago—the influx of crack cocaine. More specifically, opioid addicts, who tend to be white, have been positioned as patients, whereas in the 1970s and 80s during the war on drugs, heroin and crack addicts, respectively, who tended to be people of color, were criminalized (Hart, 2017; Hutchinson, 2017).MethodsI collected data visualzations created during the crack epidemic for 1/1/86-12/31/92 and for the opioid epidemic from 11/3/15 (the date the NYT covered Case and Deaton's study)-9/30/18 for opioids from the following mainstream news organizations: Newsweek, The Chicago Tribune, The Los Angeles (LA) Times, The New York Times (NYT), The Washington Post (WaPo), Time Magazine, U.S.A Today, and U.S. News and World Report. I then organized each collection by genre (bar or pie chart, line graph, map, etc), subject matter (crime-related, drug use and abuse related, effects on children, effects on health including deaths and treatment, STDs, and trafficking), and also assessed whether the text in the article directly referred to the graphic and discussed the data shown.ResultsSeventy three images were included of the crack epidemic and 100 were included for the opioid epidemic. The majority of graphics created during the crack epidemic were bar and line graphs whereas there was far more variation in the genre of graphics created during the opioid epidemic. The majority of graphics created during the crack epidemic also showed crime-related information (defined as crime rates, location of crimes, number of crimes committed, specific types of crimes such as homicides as well as information about arrests and sentencing) whereas very few data visualizations created during the opioid epidemic were related to crime. Indeed, the majority of these visuals showed effects on health (more specifically mortality). Finally, data visualizations create during the crack epidemic were rarely directed referred in the text of the article, but were usually discussed albeit, along with other visual information. In contrast, data visualizations created during the opioid epidemic were usually directly referenced and overtly discussed.ConclusionsI suggest that these results illustrates precarity (Bulter, 2009) by revealing systemic inequalities that protect some people, but leave others vulnerable through two counter narratives: opioid addiction is a public health issue, but crack addiction is a crime.ReferencesButler, Judith. (2009). Frames of war: When is life grievable? Brooklyn, NY: Verso Books.Case, A. and Deaton, A. (2015). Rising morbidity and mortality in midlife among white non-Hispanic Americans in the 21st century. Proceedings of the National Academy of Sciences of the United States of America. 112(49): 15078-15083.CDC. (2015). Controlled Substance Prescribing Patterns — Prescription Behavior Surveillance System, Eight States, 2013. Morbidity and Mortality Weekly Report. October 16, 2015 / 64(SS09);1-14. Hart, C. L. (2017, August 18). The real opioid emergency. The New York Times.Hutchinson, E. O. (2017, June 21). The opioid crisis in black and white. Huffington Post.Kolata, G. (2015, November 3). Rise in Deaths for U.S. Whites in Middle Age. The New York Times.


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