Dataset Information

Internet searches for opioids predict future emergency department heroin admissions.

ABSTRACT: BACKGROUND:For a number of fiscal and practical reasons, data on heroin use have been of poor quality, which has hampered the ability to halt the growing epidemic. Internet search data, such as those made available by Google Trends, have been used as a low-cost, real-time data source for monitoring and predicting a variety of public health outcomes. We aimed to determine whether data on opioid-related internet searches might predict future heroin-related admissions to emergency departments (ED). METHODS:Across nine metropolitan statistical areas (MSAs) in the United States, we obtained data on Google searches for prescription and non-prescription opioids, as well as Substance Abuse and Mental Health Services Administration (SAMHSA) data on heroin-related ED visits from 2004 to 2011. A linear mixed model assessed the relationship between opioid-related Internet searches and following year heroin-related visits, controlling for MSA GINI index and total number of ED visits. RESULTS:The best-fitting model explained 72% of the variance in heroin-related ED visits. The final model included the search keywords "Avinza," "Brown Sugar," "China White," "Codeine," "Kadian," "Methadone," and "Oxymorphone." We found regional differences in where and how people searched for opioid-related information. CONCLUSIONS:Internet search-based modeling should be explored as a new source of insights for predicting heroin-related admissions. In geographic regions where no current heroin-related data exist, Internet search modeling might be a particularly valuable and inexpensive tool for estimating changing heroin use trends. We discuss the immediate implications for using this approach to assist in managing opioid-related morbidity and mortality in the United States.

SUBMITTER: Young SD

PROVIDER: S-EPMC6436381 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

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Internet searches for opioids predict future emergency department heroin admissions.

Young Sean D SD Zheng Kai K Chu Larry F LF Humphreys Keith K

Drug and alcohol dependence 20180619

<h4>Background</h4>For a number of fiscal and practical reasons, data on heroin use have been of poor quality, which has hampered the ability to halt the growing epidemic. Internet search data, such as those made available by Google Trends, have been used as a low-cost, real-time data source for monitoring and predicting a variety of public health outcomes. We aimed to determine whether data on opioid-related internet searches might predict future heroin-related admissions to emergency departmen ...[more]

PMID: 30036853

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Project description:Background Identification of stroke patients at increased risk of emergency department (ED) visits or hospital admissions allows implementation of mitigation strategies. We evaluated the ability of the Patient-Reported Outcomes Information Measurement System (PROMIS) patient-reported outcomes (PROs) collected as part of routine care to predict 1-year emergency department (ED) visits and admissions when added to other readily available clinical variables. Methods and Results This was a cohort study of 1696 patients with ischemic stroke, intracerebral hemorrhage, subarachnoid hemorrhage, or transient ischemic attack seen in a cerebrovascular clinic from February 17, 2015, to June 11, 2018, who completed the following PROs at the visit: Patient Health Questionnaire-9, Quality of Life in Neurological Disorders cognitive function, PROMIS Global Health, sleep disturbance, fatigue, anxiety, social role satisfaction, physical function, and pain interference. A series of logistic regression models was constructed to determine the ability of models that include PRO scores to predict 1-year ED visits and all-cause and unplanned admissions. In the 1 year following the PRO encounter date, 1046 ED visits occurred in 548 patients; 751 admissions occurred in 453 patients. All PROs were significantly associated with future ED visits and admissions except PROMIS sleep. Models predicting unplanned admissions had highest optimism-corrected area under the curve (range, 0.684-0.724), followed by ED visits (range, 0.674-0.691) and then all-cause admissions (range, 0.628-0.671). PROs measuring domains of mental health had stronger associations with ED visits; PROs measuring domains of physical health had stronger associations with admissions. Conclusions PROMIS scales improve the ability to predict ED visits and admissions in patients with stroke. The differences in model performance and the most influential PROs in the prediction models suggest differences in factors influencing future hospital admissions and ED visits.

Project description:Study objectiveOpioid abuse and overdose constitute an ongoing health emergency. Many presume opioids have little potential for iatrogenic addiction when used as directed, particularly in short courses, as is typical of the emergency department (ED) setting. We preliminarily explore the possibility that initial exposure to opioids by EDs could be related to subsequent opioid misuse.MethodsThis cross-sectional study surveyed a convenience sample of patients reporting heroin or nonmedical opioid use at an urban, academic ED. We estimated the proportion whose initial exposure to opioids was a legitimate medical prescription and the proportion of those prescriptions that came from an ED. Secondary measurements included the proportion of patients receiving nonopioid substances before initial opioid exposure, the source of opioids between initial exposure and onset of regular nonmedical use, and time from initial prescription to opioid use disorder.ResultsOf 59 subjects, 35 (59%; 95% confidence interval [CI] 47% to 71%) reported they were first exposed to opioids by a legitimate medical prescription, and for 10 of 35 (29%; 95% CI 16% to 45%), the prescription came from an ED. Most medically exposed subjects (28/35; 80%; 95% CI 65% to 91%) reported nonopioid substance use or treatment for nonopioid substance use disorders preceding the initial opioid exposure. Emergency providers were a source of opioids between exposure and onset of regular nonmedical use in 11 of 35 cases (31%; 95% CI 18% to 48%). Thirty-one of the 35 medically exposed subjects reported the time of onset of nonmedical use; median time from exposure to onset of nonmedical use was 6 months for use to get high (N=25; interquartile range [IQR] 2 to 36), 12 months for regular use to get high (N=24; IQR 2 to 36), 18 months for use to avoid withdrawal (N=26; IQR 2 to 38), and 24 months for regular use to avoid withdrawal (N=27; IQR 2 to 48). Eleven subjects (36%; 95% CI 21% to 53%) began nonmedical use within 2 months, and 9 of 11 (82%; 95% CI 53% to 96%) reported nonopioid substance use or treatment for alcohol abuse before initial opioid exposure.ConclusionAlthough short-term opioid administration by emergency providers is unlikely to cause addiction by itself, ED opioid prescriptions may contribute to the development of addiction in some patients. There is an urgent need for further research to estimate long-term risks of short-course opioid therapy so that the risk of iatrogenic addiction can be appropriately balanced with the benefit of analgesia.

Project description:BackgroundEmergency departments (EDs) see a rising number of patients, but only a small fraction of ED patients need immediate intensive care. The characteristics of these patients are mostly unknown and there is reason to believe that there are large inter-hospital differences in thresholds for intensive care admissions from the ED. The purpose of this study was to give a nationwide overview of ED admissions directly to intensive care units.MethodsWe used the Swedish Intensive care Registry to identify all patients admitted to intensive care from the ED (January 1, 2013 until June 7, 2018). The primary outcome was discharge diagnosis after intensive care (primary ICU diagnosis code). ICU mortality and" ICU admission due to only observation" were analyzed as secondary outcomes.Results110,072 ICU admissions were included, representing 94,546 unique patients. Intoxication, trauma and neurological conditions were the most common causes for intensive care, but large variations according to age, sex and hospital type were seen. Intoxication was the most prevalent diagnosis in young adults (46.8% of admissions in 18-29 years old), whereas infectious diseases predominated in the elderly (17.0% in 65-79 years old). Overall, ICU mortality was 7.2%, but varied substantially with age, sex, type of hospital and medical condition. Cardiac conditions had the highest mortality rates, reaching 32.9%. The mortality was higher in academic centers compared to rural hospitals (9.3% vs 5.0%). It was more common to be admitted to ICU for only observation in rural hospitals than in academic centers (20.1% vs 7.8%). Being admitted to ICU only for observation was most common in patients with intoxication (30.6%).ConclusionsOverall, intoxication was the most common cause for ICU admission from the ED. However, causes of ED ICU admissions differ substantially according to age, sex and hospital type. Being admitted to the ICU only for observation was most common in intoxicated patients.Trial registrationNot applicable (no interventions).

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Internet searches for opioids predict future emergency department heroin admissions.

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Internet searches for opioids predict future emergency department heroin admissions.

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