scholarly journals Emergency departments at the crossroads of intersecting epidemics (HIV, HCV, injection drug use and opioid overdose)-Estimating HCV incidence in an urban emergency department population

2018 ◽  
Vol 25 (11) ◽  
pp. 1397-1400 ◽  
Author(s):  
Y.-H. Hsieh ◽  
A. V. Patel ◽  
G. S. Loevinsohn ◽  
D. L. Thomas ◽  
R. E. Rothman
PLoS ONE ◽  
2020 ◽  
Vol 15 (6) ◽  
pp. e0233927
Author(s):  
Erik S. Anderson ◽  
Carly Russell ◽  
Kellie Basham ◽  
Martha Montgomery ◽  
Helen Lozier ◽  
...  

Author(s):  
Nathan W Furukawa ◽  
Erin F Blau ◽  
Zach Reau ◽  
David Carlson ◽  
Zachary D Raney ◽  
...  

Abstract Background Persons who inject drugs (PWID) have frequent healthcare encounters related to their injection drug use (IDU) but are often not tested for human immunodeficiency virus (HIV). We sought to quantify missed opportunities for HIV testing during an HIV outbreak among PWID. Methods PWID with HIV diagnosed in 5 Cincinnati/Northern Kentucky counties during January 2017–September 2018 who had ≥1 encounter 12 months prior to HIV diagnosis in 1 of 2 Cincinnati/Northern Kentucky area healthcare systems were included in the analysis. HIV testing and encounter data were abstracted from electronic health records. A missed opportunity for HIV testing was defined as an encounter for an IDU-related condition where an HIV test was not performed and had not been performed in the prior 12 months. Results Among 109 PWID with HIV diagnosed who had ≥1 healthcare encounter, 75 (68.8%) had ≥1 IDU-related encounters in the 12 months before HIV diagnosis. These 75 PWID had 169 IDU-related encounters of which 86 (50.9%) were missed opportunities for HIV testing and occurred among 46 (42.2%) PWID. Most IDU-related encounters occurred in the emergency department (118/169; 69.8%). Using multivariable generalized estimating equations, HIV testing was more likely in inpatient compared with emergency department encounters (adjusted relative risk [RR], 2.72; 95% confidence interval [CI], 1.70–4.33) and at the healthcare system receiving funding for emergency department HIV testing (adjusted RR, 1.76; 95% CI, 1.10–2.82). Conclusions PWID have frequent IDU-related encounters in emergency departments. Enhanced HIV screening of PWID in these settings can facilitate earlier diagnosis and improve outbreak response.


Author(s):  
Wendy Macias-Konstantopoulos ◽  
Alan Heins ◽  
Carolyn J. Sachs ◽  
Paula J. Whiteman ◽  
Neil-Jeremy G. Wingkun ◽  
...  

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Stefanie P. Albert ◽  
Rosa Ergas ◽  
Sita Smith ◽  
Gillian Haney ◽  
Monina Klevens

ObjectiveWe sought to measure the burden of emergency department (ED) visits associated with injection drug use (IDU), HIV infection, and homelessness; and the intersection of homelessness with IDU and HIV infection in Massachusetts via syndromic surveillance data.IntroductionIn Massachusetts, syndromic surveillance (SyS) data have been used to monitor injection drug use and acute opioid overdoses within EDs. Currently, Massachusetts Department of Public Health (MDPH) SyS captures over 90% of ED visits statewide. These real-time data contain rich free-text and coded clinical and demographic information used to categorize visits for population level public health surveillance.Other surveillance data have shown elevated rates of opioid overdose related ED visits, Emergency Medical Service incidents, and fatalities in Massachusetts from 2014-20171,2,3. Injection of illicitly consumed opioids is associated with an increased risk of infectious diseases, including HIV infection. An investigation of an HIV outbreak among persons reporting IDU identified homelessness as a social determinant for increased risk for HIV infection.MethodsTo accomplish our objectives staff used an existing MDPH SyS IDU syndrome definition4, developed a novel syndrome definition for HIV-related visits, and adapted Maricopa County's homelessness syndrome definition. Syndromes were applied to Massachusetts ED data through the CDC’s BioSense Platform. Visits meeting the HIV and homelessness syndromes were randomly selected and reviewed to assess accuracy; inclusion and exclusion criteria were then revised to increase specificity. The final versions of all three syndrome definitions incorporate free-text elements from the chief complaint and triage notes, as well as International Statistical Classification of Diseases and Related Health Problems, 9th (ICD-9) and 10th Revision (ICD-10) diagnostic codes. Syndrome categories were not mutually exclusive, and all reported visits occurring at Massachusetts EDs were included in the analysis.Syndromes CreatedFor the HIV infection syndrome definition, we incorporated the free-text term “HIV” in both the chief complaint and triage notes. Visit level review demonstrated that the following exclusions were needed to reduce misspellings, inclusion of partial words, and documentation of HIV testing results: “negative for HIV”, “HIV neg”, “negative test for HIV”, “hive”, “hivies”, and “vehivcle”. Additionally, the following diagnostic codes were incorporated: V65.44 (Human immunodeficiency virus [HIV] counseling), V08 (asymptomatic HIV infection status), V01.79 (contact with or exposure to other viral diseases), 795.71 (nonspecific serologic evidence of HIV), V73.89 (special screening examination for other specified viral diseases), 079.53 (HIV, type 2 [HIV-2]), Z20.6 (contact with and (suspected) exposure to HIV), Z71.7 (HIV counseling), B20 (HIV disease), Z21 (asymptomatic HIV infection status), R75 (inconclusive laboratory evidence of HIV), Z11.4 (encounter for screening for HIV), and B97.35 (HIV-2 as the cause of diseases classified elsewhere).Building on the Maricopa County homeless syndrome definition, we incorporated a variety of free-text inclusion and exclusion terms. To meet this definition visits had to mention: “homeless”, or “no housing”, or, “lack of housing”, or “without housing”, or “shelter” but not animal and domestic violence shelters. We also selected the following ICD-10 codes for homelessness and inadequate housing respectively, Z59.0 and Z59.1.We analyzed MDPH SyS data for visits occurring from January 1, 2016 through June 30, 2018. Rates per 10,000 ED visits categorized as IDU, HIV, or homeless were calculated. Subsequently, visits categorized as IDU, HIV, and meeting both IDU and HIV syndrome definitions (IDU+HIV) were stratified by homelessness.ResultsSyndrome Burden on EDThe MDPH SyS dataset contains 6,767,137 ED visits occurring during the study period. Of these, 82,819 (1.2%) were IDU-related, 13,017 (0.2%) were HIV-related, 580 (<0.01%) were related to IDU + HIV, and 42,255 visits (0.6%) were associated with homelessness.The annual rate of IDU-related visits increased 15% from 2016 through June of 2018 (from 113.63 to 130.57 per 10,000 visits); while rates of HIV-related and IDU + HIV-related visits remained relatively stable. The overall rate of visits associated with homelessness increased 47% (from 49.99 to 73.26 per 10,000 visits).Rates of IDU, HIV, and IDU + HIV were significantly higher among visits associated with homelessness. Among visits that met the homeless syndrome definition compared to those that did not: the rate of IDU-related visits was 816.0 versus 118.03 per 10,000 ED visits (X2= 547.12, p<0. 0001); the rate of visits matching the HIV syndrome definition was 145.54 versus 18.44 per 10,000 ED visits (X2= 99.33, p<0.0001); and the rate of visits meeting the IDU+HIV syndrome definition was 15.86 versus 0.76 per 10,000 visits (X2= 13.72, p= 0.0002).ConclusionsMassachusetts is experiencing an increasing burden of ED visits associated with both IDU and homelessness that parallels increases in opioid overdoses. Higher rates of both IDU and HIV-related visits were associated with homelessness. An understanding of the intersection between opioid overdoses, IDU, HIV, and homelessness can inform expanded prevention efforts, introduction of alternatives to ED care, and increase consideration of housing status during ED care.Continued surveillance for these syndromes, including collection and analysis of demographic and clinical characteristics, and geographic variations, is warranted. These data can be useful to providers and public health authorities for planning healthcare services.References1. Vivolo-Kantor AM, Seth P, Gladden RM, et al. Vital Signs: Trends in Emergency Department Visits for Suspected Opioid Overdoses — United States, July 2016–September 2017. MMWR Morbidity and Mortality Weekly Report 2018; 67(9);279–285 DOI: http://dx.doi.org/10.15585/mmwr.mm6709e12. Massachusetts Department of Public Health. Chapter 55 Data Brief: An assessment of opioid-related deaths in Massachusetts, 2011-15. 2017 August. Available from: https://www.mass.gov/files/documents/2017/08/31/data-brief-chapter-55-aug-2017.pdf3. Massachusetts Department of Public Health. MA Opioid-Related EMS Incidents 2013-September 2017. 2018 Feb. Available from: https://www.mass.gov/files/documents/2018/02/14/emergency-medical-services-data-february-2018.pdf4. Bova, M. Using emergency department (ED) syndromic surveillance to measure injection-drug use as an indicator for hepatitis C risk. Powerpoint presented at: 2017 Northeast Epidemiology Conference. 2017 Oct 18 – 20; Northampton, Massachusetts, USA.


CJEM ◽  
2018 ◽  
Vol 21 (2) ◽  
pp. 226-234 ◽  
Author(s):  
Andrew Kestler ◽  
Amanda Giesler ◽  
Jane Buxton ◽  
Gray Meckling ◽  
Michelle Lee ◽  
...  

AbstractObjectiveTake-home naloxone (THN) reduces deaths from opioid overdose. To increase THN distribution to at-risk emergency department (ED) patients, we explored reasons for patients’ refusing or accepting THN.MethodsIn an urban teaching hospital ED, we identified high opioid overdose risk patients according to pre-specified criteria. We offered eligible patients THN and participation in researcher-administered surveys, which inquired about reasons to refuse or accept THN and about THN dispensing location preferences. We analyzed refusal and acceptance reasons in open-ended responses, grouped reasons into categories (absolute versus conditional refusals,) then searched for associations between patient characteristics and reasons.ResultsOf 247 patients offered THN, 193 (78.1%) provided reasons for their decision. Of those included, 69 (35.2%) were female, 91 (47.2%) were under age 40, 61 (31.6%) were homeless, 144 (74.6%) reported injection drug use (IDU), and 131 (67.9%) accepted THN. Of 62 patients refusing THN, 19 (30.7%) felt “not at risk” for overdose, while 28 (45.2%) gave conditional refusal reasons: “too sick,” “in a rush,” or preference to get THN elsewhere. Non-IDU was associated with stating “not at risk,” while IDU, homelessness, and age under 40 were associated with conditional refusals. Among acceptances, 86 (65.7%) mentioned saving others as a reason. Most respondents preferred other dispensing locations beside the ED, whether or not they accepted ED THN.ConclusionED patients refusing THN felt “not at risk” for overdose or felt their ED visit was not the right time or place for THN. Most accepting THN wanted to save others.


2008 ◽  
Author(s):  
Debbie Y. Mohammed ◽  
Patricia C. Kloser

2011 ◽  
Author(s):  
L. Jackson ◽  
M. Dykeman ◽  
J. Gahagan ◽  
J. Karabanow ◽  
J. Parker

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