Notes from the Field: High Prevalence of Fentanyl Detected by the Maryland Emergency Department Drug Surveillance System - Baltimore, Maryland, 2019.
Ontology highlight
ABSTRACT:
SUBMITTER: Dezman Z
PROVIDER: S-EPMC7315791 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:BackgroundWe sought to determine the prevalence and sociodemographic and clinical correlates of acute and convalescent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), hepatitis C virus (HCV), and human immunodeficiency virus (HIV) infections among emergency department (ED) patients in Baltimore.MethodsRemnant blood samples from 7450 unique patients were collected over 4 months in 2020 for SARS-CoV-2 antibody (Ab), HCV Ab, and HIV-1/2 antigen and Ab. Among them, 5012 patients were tested by polymerase chain reaction for SARS-CoV-2 based on clinical suspicion. Sociodemographics, ED clinical presentations, and outcomes associated with coinfections were assessed.ResultsOverall, 729 (9.8%) patients had SARS-CoV-2 (acute or convalescent), 934 (12.5%) HCV, 372 (5.0%) HIV infection, and 211 patients (2.8%) had evidence of any coinfection (HCV/HIV, 1.5%; SARS-CoV-2/HCV, 0.7%; SARS-CoV-2/HIV, 0.3%; SARS-CoV-2/HCV/HIV, 0.3%). The prevalence of SARS-CoV-2 (acute or convalescent) was significantly higher in those with HCV or HIV vs those without (13.6% vs 9.1%, P < .001). Key sociodemographic disparities (race, ethnicity, and poverty) and specific ED clinical characteristics were significantly correlated with having any coinfections vs no infection or individual monoinfection. Among those with HCV or HIV, aged 18-34 years, Black race, Hispanic ethnicity, and a cardiovascular-related chief complaint had a significantly higher odds of having SARS-CoV-2 (prevalence ratios: 2.02, 2.37, 5.81, and 2.07, respectively).ConclusionsThe burden of SARS-CoV-2, HCV, and HIV co-pandemics and their associations with specific sociodemographic disparities, clinical presentations, and outcomes suggest that urban EDs should consider implementing integrated screening and linkage-to-care programs for these 3 infections.
| S-EPMC8982772 | biostudies-literature
Project description:BackgroundAbout 30% of home healthcare patients are hospitalized or visit an emergency department (ED) during a home healthcare (HHC) episode. Novel data science methods are increasingly used to improve identification of patients at risk for negative outcomes.ObjectivesThe aim of the study was to identify patients at heightened risk hospitalization or ED visits using HHC narrative data (clinical notes).MethodsThis study used a large database of HHC visit notes (n = 727,676) documented for 112,237 HHC episodes (89,459 unique patients) by clinicians of the largest nonprofit HHC agency in the United States. Text mining and machine learning algorithms (Naïve Bayes, decision tree, random forest) were implemented to predict patient hospitalization or ED visits using the content of clinical notes. Risk factors associated with hospitalization or ED visits were identified using a feature selection technique (gain ratio attribute evaluation).ResultsBest performing text mining method (random forest) achieved good predictive performance. Seven risk factors categories were identified, with clinical factors, coordination/communication, and service use being the most frequent categories.DiscussionThis study was the first to explore the potential contribution of HHC clinical notes to identifying patients at risk for hospitalization or an ED visit. Our results suggest that HHC visit notes are highly informative and can contribute significantly to identification of patients at risk. Further studies are needed to explore ways to improve risk prediction by adding more data elements from additional data sources.
| S-EPMC7606545 | biostudies-literature
Project description:ObjectivesHospital emergency departments (EDs) are a place where many Americans seek treatment of dental conditions. Racial and ethnic minorities consistently have higher rates of ED utilization than whites for dental conditions. The reasons for these disparities and significant public health concerns are investigated less often. In this paper, we measure trends in racial disparities in ED discharges for dental conditions in Maryland from 2010 to 2013. To understand these disparities, we also describe differences between racial groups in age, gender, income, location, payer, comorbidities, and the availability of dental care.Methods2010-2013 State Emergency Department Data for Maryland were used in the analysis. Rates per 100,000 of the population are calculated using information from census population estimates. Cost-to-charge ratios are used to estimate the costs of ED discharges. Dental/oral health-related conditions (DOHRC) are defined as discharge diagnoses of ICD-9-CM codes 520.0 through 529.9. Descriptive statistics and fixed effects logistic regression models with a rare event correction are used to analyze the data.ResultsBlacks, especially females aged 25-34, have larger proportions of total ED discharges due to DOHRC, and higher population rates of DOHRC, than any other racial or ethnic group. In 2013, Blacks represented 30% of Maryland's population and accounted for 52% of ED costs for DOHRC. Hispanics and those of other races have much lower rates of DOHRC discharges. The regression results show that the high proportion of DOHRC discharges among Blacks may be explained by the concentration of Blacks in low-income central cities with less access to dental care.ConclusionThere are significant racial disparities in the ED utilization for DOHRC in Maryland. These disparities reflect the lack of access to dental care due to both cost and geographic limitations. This results in high healthcare costs and ineffective solutions for patients. Addressing oral health disparities will require policy solutions that are targeted to the populations most at need, and action plans that combine community and state level efforts.
| S-EPMC5515044 | biostudies-literature
Project description:BackgroundSyndromic surveillance provides public health intelligence to aid in early warning and monitoring of public health impacts (e.g. seasonal influenza), or reassurance when an impact has not occurred. Using information collected during routine patient care, syndromic surveillance can be based on signs/symptoms/preliminary diagnoses. This approach makes syndromic surveillance much timelier than surveillance requiring laboratory confirmed diagnoses. The provision of healthcare services and patient access to them varies globally. However, emergency departments (EDs) exist worldwide, providing unscheduled urgent care to people in acute need. This provision of care makes ED syndromic surveillance (EDSyS) a potentially valuable tool for public health surveillance internationally. The objective of this study was to identify and describe the key characteristics of EDSyS systems that have been established and used globally.MethodsWe systematically reviewed studies published in peer review journals and presented at International Society of Infectious Disease Surveillance conferences (up to and including 2017) to identify EDSyS systems which have been created and used for public health purposes. Search criteria developed to identify "emergency department" and "syndromic surveillance" were applied to NICE healthcare, Global Health and Scopus databases.ResultsIn total, 559 studies were identified as eligible for inclusion in the review, comprising 136 journal articles and 423 conference abstracts/papers. From these studies we identified 115 EDSyS systems in 15 different countries/territories across North America, Europe, Asia and Australasia. Systems ranged from local surveillance based on a single ED, to comprehensive national systems. National EDSyS systems were identified in 8 countries/territories: 2 reported inclusion of ≥85% of ED visits nationally (France and Taiwan).ConclusionsEDSyS provides a valuable tool for the identification and monitoring of trends in severe illness. Technological advances, particularly in the emergency care patient record, have enabled the evolution of EDSyS over time. EDSyS reporting has become closer to 'real-time', with automated, secure electronic extraction and analysis possible on a daily, or more frequent basis. The dissemination of methods employed and evidence of successful application to public health practice should be encouraged to support learning from best practice, enabling future improvement, harmonisation and collaboration between systems in future.Prospero numberCRD42017069150 .
| S-EPMC7724621 | biostudies-literature
Project description:ObjectiveAccurate identification of self-harm presentations to Emergency Departments (ED) can lead to more timely mental health support, aid in understanding the burden of suicidal intent in a population, and support impact evaluation of public health initiatives related to suicide prevention. Given lack of manual self-harm reporting in ED, we aim to develop an automated system for the detection of self-harm presentations directly from ED triage notes.Materials and methodsWe frame this as supervised classification using natural language processing (NLP), utilizing a large data set of 477 627 free-text triage notes from ED presentations in 2012-2018 to The Royal Melbourne Hospital, Australia. The data were highly imbalanced, with only 1.4% of triage notes relating to self-harm. We explored various preprocessing techniques, including spelling correction, negation detection, bigram replacement, and clinical concept recognition, and several machine learning methods.ResultsOur results show that machine learning methods dramatically outperform keyword-based methods. We achieved the best results with a calibrated Gradient Boosting model, showing 90% Precision and 90% Recall (PR-AUC 0.87) on blind test data. Prospective validation of the model achieves similar results (88% Precision; 89% Recall).DiscussionED notes are noisy texts, and simple token-based models work best. Negation detection and concept recognition did not change the results while bigram replacement significantly impaired model performance.ConclusionThis first NLP-based classifier for self-harm in ED notes has practical value for identifying patients who would benefit from mental health follow-up in ED, and for supporting surveillance of self-harm and suicide prevention efforts in the population.
| S-EPMC8800520 | biostudies-literature
Project description:ObjectiveThe objective of this study was to examine trends in fatal and nonfatal overdose in a community-based sample of current and former people who inject drugs (PWID).MethodsData from 4826 current and former PWID from the AIDS Linked to the IntraVenous Experience (ALIVE) observational cohort study in Baltimore, Maryland, were used to characterize fatal and nonfatal overdose rates from 1998 to 2019. Poisson regression was used to examine factors associated with nonfatal overdose and differences by race among 1052 PWID between 2014 and 2019.ResultsFatal overdose rates reached a high of 13 per 1000 person-years in 2018. Among 1052 current and former PWID, of whom 75% were Black and one-third were female, the nonfatal overdose rate of 529 per 1000 person-years in 2019 was 8 times higher than 2014 (incidence rate ratio [IRR]=7.76, 95% CI: 3.35, 18.0). The annual adjusted increase in nonfatal overdose rate was 53% among Black PWID (IRR=1.53, 95% CI: 1.34, 1.75), compared to 14% among White PWID (IRR=1.14, 95% CI: 0.88, 1.46). Urban residence, opioid use, depressive symptoms, and hepatitis C infection were positively associated with nonfatal overdose among Black PWID. Recent injection drug use and tranquilizer use was associated with increased overdose among Black and White PWID.ConclusionsRates of fatal and nonfatal overdose were high and increased from 2014 to 2019 among current and former PWID, with the most dramatic increases in nonfatal overdose observed among Black PWID. These findings highlight the urgent need for additional resources to reduce the differential harms associated with opioids by race.
| S-EPMC8665116 | biostudies-literature
Project description:ImportanceSynthetic opioids, such as the fentanyl analogue and nitazene drug class, are among the fastest growing types of opioids being detected in patients in the emergency department (ED) with illicit opioid overdose (OD). However, clinical outcomes from OD of novel potent opioids (NPOs), specifically nitazenes, are unknown aside from small case series.ObjectiveTo determine naloxone administration and clinical sequelae of patients who were in the ED with NPO overdose compared with fentanyl OD.Design, setting, and participantsThis is a cohort study subgroup analysis of adults admitted to the ED and tested positive for NPOs among in the ongoing nationwide ToxIC Fentalog cohort study from 2020 to 2022. Patients who were in the ED with a presumed acute opioid OD and residual blood samples were included, and those testing positive for NPOs were analyzed. Patients were included in this analysis if their confirmatory testing was positive for an NPO analyte, such as brorphine, isotonitazene, metonitazene, and/or N-piperidinyl etonitazene. A comparison group included patients that were positive for fentanyl and devoid of any other analytes on toxicologic analysis.ExposuresPatients were exposed to NPOs, including brorphine, isotonitazene, metonitazene and/or N-piperidinyl etonitazene.Main outcomes and measuresThe primary outcome was the total number of naloxone doses and total cumulative naloxone dose administered as part of routine clinical care following the OD. Naloxone requirements and clinical sequelae of NPO-positive patients were compared with those testing positive for fentanyl only.ResultsDuring the study period, 2298 patients were screened, of whom 717 met inclusion criteria, 537 had complete laboratory testing data, with 11 (2.0%) positive for only fentanyl and 9 (1.7%) positive for NPOs (brorphine, isotonitazene, metonitazene, or N-piperidinyl etonitazene). The age range of patients was aged 20 to 57 years (4 males [44.4%] and 5 females [55.6%]). The NPO group received a statistically significantly higher mean (SD) number of naloxone boluses in-hospital (1.33 [1.50]) compared with the fentanyl group (0.36 [0.92]) (P = .02), which corresponded to a moderately large effect size (Cohen d = 0.78). Metonitazene overdose was associated with cardiac arrest and more naloxone doses overall. Metonitazene cases had a mean (SD) number of 3.0 (0) naloxone doses, and 2 of 2 patients (100%) with metonitazene overdoses were administered cardiopulmonary resuscitation.Conclusions and relevanceIn this cohort study of patients admitted to the ED with confirmed opioid overdose testing positive for NPOs, in-hospital naloxone dosing was high compared with patients who tested positive for fentanyl alone. Further study is warranted to confirm these preliminary associations.
| S-EPMC10466160 | biostudies-literature
Project description:IntroductionOn January 1, 2014, the State of Maryland implemented the Global Budget Revenue (GBR) program. We investigate the impact of GBR on length of stay (LOS) for inpatients in emergency departments (ED) in Maryland.MethodsWe used the Hospital Compare data reports from the Centers for Medicare and Medicaid Services (CMS) and CMS Cost Reports Hospital Form 2552-10 from January 1, 2012-March 31, 2016, with GBR hospitals from Maryland and hospitals from West Virginia (WV), Delaware (DE), and Rhode Island (RI). We implemented difference-in-differences analysis and investigated the impact of GBR implementation on the LOS or ED1b scores of Maryland hospitals using a mixed-effects model with a state-level fixed effect, a hospital-level random effect, and state-level heterogeneity.ResultsThe GBR impact estimator was 9.47 (95% confidence interval [CI], 7.06 to 11.87, p-value<0.001) for Maryland GBR hospitals, which implies, on average, that GBR implementation added 9.47 minutes per year to the time that hospital inpatients spent in the ED in the first two years after GBR implementation. The effect of the total number of hospital beds was 0.21 (95% CI, 0.089 to 0.330, p-value = 0 .001), which suggests that the bigger the hospital, the longer the ED1b score. The state-level fixed effects for WV were -106.96 (95% CI, -175.06 to -38.86, p-value = 0.002), for DE it was 6.51 (95% CI, -8.80 to 21.82, p-value=0.405), and for RI it was -54.48 (95% CI, -82.85 to -26.10, p-value<0.001).ConclusionOur results indicate that GBR implementation has had a statistically significant negative impact on the efficiency measure ED1b of Maryland hospital EDs from January 2014 to April 2016. We also found that the significant state-level fixed effect implies that the same inpatient might experience different ED processing times in each of the four states that we studied.
| S-EPMC6860385 | biostudies-literature
Project description: Not available
| S-EPMC9984967 | biostudies-literature
Project description:Waterpipe smoking has been growing in popularity in the United States and worldwide. Most tobacco control regulations remain limited to cigarettes. Few studies have investigated waterpipe tobacco smoke exposures in a real world setting. We measured carbon monoxide (CO), particulate matter (PM)2.5, and airborne nicotine concentrations in seven waterpipe cafes in the greater Baltimore area. Area air samples were collected between two and five hours, with an average sampling duration of three hours. Waterpipe smoking behaviors were observed at each venue. Indoor air samplers for CO, PM2.5, and airborne nicotine were placed in the main seating area 1-2 m above the floor. Indoor airborne concentrations of PM2.5 and CO were markedly elevated in waterpipe cafes and exceeded concentrations that were observed in cigarette smoking bars. Air nicotine concentrations, although not as high as in venues that allow cigarette smoking, were markedly higher than in smoke-free bars and restaurants. Concentrations of PM approached occupational exposure limits and CO exceeded occupational exposure guidelines suggesting that worker protection measures need to be considered. This study adds to the literature indicating that both employees and patrons of waterpipe venues are at increased risk from complex exposures to secondhand waterpipe smoke.
| S-EPMC4333110 | biostudies-literature