scholarly journals Opioid Drug Death Investigations

2017 ◽  
Vol 7 (1) ◽  
pp. 50-59 ◽  
Author(s):  
Daniel Morgan
Keyword(s):  
Public Health Surveillance ◽  
Health Surveillance ◽  
Steady Increase ◽  
Opioid Overdose ◽  
The Past ◽  
Drug Death ◽  
Death Investigation ◽  
Medical Examiners ◽  
Medicolegal Death Investigation

Opioid-related deaths have transitioned over the past 15 years, beginning with a steady increase in the incidence of fatal prescription overdoses, followed by a dramatic increase in deaths caused by illicit opioids, namely heroin and fentanyl. These trends in drug-related deaths are identified by medical examiners and coroners who serve an important role in public health surveillance. Medicolegal death investigators, being first responders, often recognize spates of drug-related deaths in real time. While few jurisdictions are unaffected by the epidemic, some medicolegal death investigators may have less experience detecting fatal opioid overdoses. This review will outline many of the medical, behavioral, and physical indicators of a deadly prescription or illicit opioid overdose. All aspects of a thorough medicolegal death investigation will be discussed, including the proper documentation of the scene and evidence handling. Investigative questions and follow-up procedures will also be reviewed.

scholarly journals Near-Real-Time Surveillance of Illnesses Related to Shellfish Consumption in British Columbia: Analysis of Poison Center Data (Preprint)

2017 ◽  
Author(s):  
Victoria Wan ◽  
Lorraine McIntyre ◽  
Debra Kent ◽  
Dennis Leong ◽  
Sarah B Henderson
Keyword(s):  
Public Health ◽  
Real Time ◽  
Public Health Surveillance ◽  
Data File ◽  
Health Surveillance ◽  
Poison Control ◽  
Short Term ◽  
Control Data

BACKGROUND Data from poison centers have the potential to be valuable for public health surveillance of long-term trends, short-term aberrations from those trends, and poisonings occurring in near-real-time. This information can enable long-term prevention via programs and policies and short-term control via immediate public health response. Over the past decade, there has been an increasing use of poison control data for surveillance in the United States, Europe, and New Zealand, but this resource still remains widely underused. OBJECTIVE The British Columbia (BC) Drug and Poison Information Centre (DPIC) is one of five such services in Canada, and it is the only one nested within a public health agency. This study aimed to demonstrate how DPIC data are used for routine public health surveillance in near-real-time using the case study of its alerting system for illness related to consumption of shellfish (ASIRCS). METHODS Every hour, a connection is opened between the WBM software Visual Dotlab Enterprise, which holds the DPIC database, and the R statistical computing environment. This platform is used to extract, clean, and merge all necessary raw data tables into a single data file. ASIRCS automatically and retrospectively scans a 24-hour window within the data file for new cases related to illnesses from shellfish consumption. Detected cases are queried using a list of attributes: the caller location, exposure type, reasons for the exposure, and a list of keywords searched in the clinical notes. The alert generates a report that is tailored to the needs of food safety specialists, who then assess and respond to detected cases. RESULTS The ASIRCS system alerted on 79 cases between January 2015 and December 2016, and retrospective analysis found 11 cases that were missed. All cases were reviewed by food safety specialists, and 58% (46/79) were referred to designated regional health authority contacts for follow-up. Of the 42% (33/79) cases that were not referred to health authorities, some were missing follow-up information, some were triggered by allergies to shellfish, and some were triggered by shellfish-related keywords appearing in the case notes for nonshellfish-related cases. Improvements were made between 2015 and 2016 to reduce the number of cases with missing follow-up information. CONCLUSIONS The surveillance capacity is evident within poison control data as shown from the novel use of DPIC data for identifying illnesses related to shellfish consumption in BC. The further development of surveillance programs could improve and enhance response to public health emergencies related to acute illnesses, chronic diseases, and environmental exposures.

scholarly journals The Past, Present, and Future of Public Health Surveillance

Scientifica ◽  
2012 ◽  
Vol 2012 ◽  
pp. 1-26 ◽  
Author(s):  
Bernard C. K. Choi
Keyword(s):  
Public Health ◽  
Public Health Surveillance ◽  
Field Investigation ◽  
Health Surveillance ◽  
Modern Concept ◽  
Public Health Action ◽  
The Past ◽  
Epidemiologic Surveillance ◽  
The Future ◽  
Definition Of

This paper provides a review of the past, present, and future of public health surveillance—the ongoing systematic collection, analysis, interpretation, and dissemination of health data for the planning, implementation, and evaluation of public health action. Public health surveillance dates back to the first recorded epidemic in 3180 B.C. in Egypt. Hippocrates (460 B.C.–370 B.C.) coined the terms endemic and epidemic, John Graunt (1620–1674) introduced systematic data analysis, Samuel Pepys (1633–1703) started epidemic field investigation, William Farr (1807–1883) founded the modern concept of surveillance, John Snow (1813–1858) linked data to intervention, and Alexander Langmuir (1910–1993) gave the first comprehensive definition of surveillance. Current theories, principles, and practice of public health surveillance are summarized. A number of surveillance dichotomies, such as epidemiologic surveillance versus public health surveillance, are described. Some future scenarios are presented, while current activities that can affect the future are summarized: exploring new frontiers; enhancing computer technology; improving epidemic investigations; improving data collection, analysis, dissemination, and use; building on lessons from the past; building capacity; enhancing global surveillance. It is concluded that learning from the past, reflecting on the present, and planning for the future can further enhance public health surveillance.

scholarly journals Comparing Syndromic Data to Discharge Data to Measure Opioid Overdose Emergency Department Visits

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Emilia S. Pasalic ◽  
Alana Marie Vivolo-Kantor ◽  
Pedro Martinez
Keyword(s):  
Public Health ◽  
Emergency Department ◽  
Public Health Surveillance ◽  
Health Surveillance ◽  
Data Sources ◽  
Opioid Overdose ◽  
Public Health Response ◽  
Discharge Data ◽  
Emergency Department Data ◽  
Health Response

ObjectiveEpidemiologists will understand the differences between syndromic and discharge emergency department data sources, the strengths and limitations of each data source, and how each of these different emergency department data sources can be best applied to inform a public health response to the opioid overdose epidemic.IntroductionTimely and accurate measurement of overdose morbidity using emergency department (ED) data is necessary to inform an effective public health response given the dynamic nature of opioid overdose epidemic in the United States. However, from jurisdiction to jurisdiction, differing sources and types of ED data vary in their quality and comprehensiveness. Many jurisdictions collect timely emergency department data through syndromic surveillance (SyS) systems, while others may have access to more complete, but slower emergency department discharge datasets. State and local epidemiologists must make decisions regarding which datasets to use and how to best operationalize, interpret, and present overdose morbidity using ED data. These choices may affect the number, timeliness, and accuracy of the cases identified.MethodsCDC partnered with 45 states and the District of Columbia to combat the worsening opioid overdose epidemic through three cooperative agreements: Prevention for States (PFS), Data Driven Prevention Initiative (DDPI), and Enhanced State Opioid Overdose Surveillance (ESOOS). To support funded jurisdictions in monitoring non-fatal opioid overdoses, CDC developed two different sets of indicator guidance for measuring non-fatal opioid overdoses using ED data, with each focusing on different ED data sources (SyS and discharge). We report on the following attributes for each type of ED data source1,2: 1) timeliness; 2) data quality (e.g., percent completeness by field); 3) validity; and 4) representativeness (e.g., percent of facilities included).ResultsWhen comparing timeliness across data sources, SyS data has clear advantages, with many jurisdictions receiving data within 24 hours of an event. For discharge data, timeliness is more variable with some jurisdictions receiving data within weeks while others wait over 1.5 years before receiving a complete discharge dataset. Data quality and completeness tends to be stronger in discharge datasets as facilities are required to submit complete discharge records with valid ICD-10-CM codes in order to be reimbursed by payers. By contrast, for SyS data systems, participating facilities may not consistently submit data for all possible fields, including diagnosis. Validity is dependent on the data source as well as the case definition or syndrome definition used; with this in mind, SyS data overdose indicators are designed to have high sensitivity, with less attention to specificity. Discharge data overdose indicators are designed to have a high positive predictive value, while sensitivity and specificity are both important considerations. Discharge datasets often include records for 100% of ED visits from all nonfederal, acute care-affiliated facilities in a state included. By contrast, representativeness of facilities in SyS data systems varies widely across states with some states having less than 50% of facilities reporting.ConclusionsCDC funded partners share overdose morbidity data with CDC using either ED SyS data, ED discharge data, or both. CDC indicator guidance for ED discharge data is designed for states to track changes in health outcomes over time for descriptive, performance monitoring, and evaluation purposes and to create rates that are more comparable across injury category, time, and place. Considering these objectives, CDC placed a higher priority on data quality, validity (i.e., positive predictive value), and representativeness, all of which are stronger attributes of discharge data. CDC’s indicator guidance for ED SyS data is designed for states to rapidly identify changes in nonfatal overdoses and to identify areas within a particular state that are experiencing rapid change in the frequency or types of overdose events. When considering these needs, CDC prioritized timeliness and validity in terms of sensitivity, both of which are stronger attributes of SyS data. SyS and discharge ED data each lend themselves to different informational applications and interpretations based on the strengths and limitations of each dataset. An effective, informed public health response to the opioid overdose epidemic requires continued investment in public health surveillance infrastructure, careful consideration of the needs of the data user, and transparency regarding the unique strengths and limitations of each dataset.References1. Pencheon, D. (2006). Oxford handbook of public health practice. 2nd ed. Oxford: Oxford University Press.2. Centers for Disease Control and Prevention (CDC) Evaluation Working Group on Public Health Surveillance Systems for Early Detection of Outbreaks. (May 7, 2004). Framework for Evaluating Public Health Surveillance Systems for Early Detection of Outbreaks. MMWR. Morbidity and Mortality Weekly Reports. Retrieved from: https://www.cdc.gov/mmwr/preview/mmwrhtml/rr5305a1.htm 

Public Health Surveillance and the Opioid Crisis

2019 ◽  
pp. 253-264
Author(s):  
Jeffrey P. Engel ◽  
Valerie N. Goodson ◽  
Megan Toe ◽  
Michael Landen
Keyword(s):  
Public Health ◽  
Disease Surveillance ◽  
Public Health Surveillance ◽  
Health Surveillance ◽  
Opioid Epidemic ◽  
Infectious Disease Surveillance ◽  
Health Practitioners ◽  
Public Health Practitioners ◽  
Case Based

The roles for public health surveillance are well established in the infectious disease surveillance literature; however, as they relate to noninfectious diseases and more specifically the current opioid epidemic, there is little standardization between states on what is being surveilled and there is a lack of definitions for some of the most important elements of the crisis, such as what constitutes an overdose death from opioids. Without standard definitions and processes, public health practitioners may develop response protocols based on incomplete data. As such, the opioid epidemic presents many challenges for public health surveillance by limiting the ability for case-based follow-up and stymies creation of a variety of shared indicators and metrics that make it difficult to capture the true burden of disease. In this chapter, the authors review prior surveillance activities related to substance use and share emerging consensus on opportunities to improve the surveillance among states and territories.

scholarly journals Surveillance of human listeriosis in France, 2001-2003

2006 ◽  
Vol 11 (6) ◽  
pp. 3-4 ◽  
Author(s):  
V Goulet ◽  
C Jacquet ◽  
P Martin ◽  
V Vaillant ◽  
E Laurent ◽  
...  
Keyword(s):  
Public Health ◽  
Listeria Monocytogenes ◽  
Public Health Surveillance ◽  
Food Samples ◽  
Health Surveillance ◽  
Outbreak Detection ◽  
Molecular Characterisation ◽  
Mandatory Notification

Mandatory notification of listeriosis began in France in 1999. Enhanced public health surveillance, including routine molecular characterisation of Listeria monocytogenes strains, epidemiologic follow up of cases, and collection of food samples, has improved the sensitivity of outbreak detection and response.

scholarly journals Opioid Surveillance using Social Media: How URLs are shared among Reddit members

2018 ◽  
Vol 10 (1) ◽  
Author(s):  
Albert Park ◽  
Mike Conway
Keyword(s):  
Public Health ◽  
Social Media ◽  
Information Seeking ◽  
Public Health Surveillance ◽  
The United States ◽  
Health Surveillance ◽  
Opioid Overdose ◽  
Unique Member ◽  
Surveillance Practice ◽  
Share Information

Objective: We aim to understand (1) the frequency of URL sharing and (2) types of shared URLs among opioid related discussions that take place in the social media platform called Reddit.Introduction: Nearly 100 people per day die from opioid overdose in the United States. Further, prescription opioid abuse is assumed to be responsible for a 15-year increase in opioid overdose deaths1. However, with increasing use of social media comes increasing opportunity to seek and share information. For instance, 80% of Internet users obtain health information online2, including popular social interaction sites like Reddit (http://www.reddit.com), which had more than 82.5 billion page views in 20153. In Reddit, members often share information, and include URLs to supplement the information. Understanding the frequency of URL sharing and types of shared URLs can improve our knowledge of information seeking/sharing behaviors as well as domains of shared information on social media. Such knowledge has the potential to provide opportunities to improve public health surveillance practice. We use Reddit to track opioid related discussions and then investigate types of shared URLs among Reddit members in those discussions.Methods: First, we use a dataset4—made available on Reddit—that has been used in several informatics studies5,6. The dataset is comprised of 13,213,173 unique member IDs, 114,320,798 posts, and 1,659,361,605 associated comments that are made on 239,772 (including active and inactive) subreddits (i.e., sub-communities) from October 2007 to May 2015. Second, we identified 9 terms that are associated with opioids. The terms are 'opioid', 'opium', 'morphine', 'opiate', 'hydrocodone', 'oxycodone', 'fentanyl', 'heroin', and 'methadone'. Third, we preprocessed the entire dataset (i.e., converting text to lower cases and removing punctuation) and extracted discussions with opioid terms and their metadata (e.g., user ID, post ID) via a lexicon-based approach. Fourth, we extracted URLs using Python from these discussions, categorized the URLs by domain, and then visualized the results in a bubble chart7.Results: We extracted 1,121,187 posts/comments that were made by 328,179 unique member IDs from 8,892 subreddits. Of the 1,121,187 posts/comments, 82,639 posts/comments contained URLs (7.37%), and these posts consisted of 272,551 individual URLs and 138,206 unique URLs. The types of shared URLs in these opioid related discussions are summarized in Figure 1. The color and size represent the type and size respectively of shared URLs. The ‘.com’ is in blue; ‘.org’ is in orange; and ‘.gov’ is in green.Conclusions: We present preliminary findings concerning the types of shared URLs in opioid-related discussions among Reddit members. Our initial results suggest that Reddit members openly discuss opioid related issues and URL sharing is a part of information sharing. Although members share many URLs from reliable information sources (e.g., ‘ncbi.nlm.nih.gov’, ‘wikipedia.org, ‘nytimes.com’, ‘sciencedirect.com’), further investigation is needed concerning many of the ‘.com’ URLs, which have the potential to contain high and/or low quality information (e.g., ‘youtube.com’, ‘reddit.com’, ‘google.com’, ‘amazon.com’) to fully understand information seeking/sharing behaviors on social media and to identify opportunities, such as misinformation dissemination for improving public health surveillance practice.

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