Overdose

A retrospective analysis of emergency department data in NC for drug and opioid overdoses has been explained previously [1]. We built on this initial work to develop new poisoning and surveillance reports to facilitate near real time surveillance by health department and hospital users. In North Carolina, the availability for mortality and hospital discharge data are approximately one and two years after the event date, respectively. NC DETECT data are near real time and over 75% of ED visits receive at least one ICD-9-CM final diagnosis code within two weeks of the initial record receipt.

Objective

Twelve new case definitions were added to the NC DETECT Web Application to facilitate timely surveillance for poisoning and overdose. The process for developing these case definitions and the most recent outputs are described.

Drug poisoning, or overdose, is an epidemic problem in the United States1,2. In keeping with national trends, a recent study combining U.S. Veterans Health Administration (VHA) data with the National Death Index showed increases in opioid overdose mortality from 2001 to 20093. One of the challenges in monitoring the overdose epidemic is that collecting cohort data to analyze overdose rates can be laborintensive. Moreover, analysts are often unable to collect real-time data on overdose events. To explore solutions to these challenges, we examined opioid overdose by using Veteran healthcare data already being collected for syndromic surveillance.

Objective

To examine inpatient admissions for opioid overdose among U.S. Veterans using national-level surveillance data.

 

Drug overdoses and related deaths have been escalating nationally since 1970. In Virginia, the rate of drug overdose deaths increased 36% from 5.0 to 6.8 deaths per 100,000 population between 1999 and 2010. While initiated for bioterrorism event detection, syndromic surveillance has shown utility when extended to other health issues. ED visits may complement information from Overdose Deaths investigated by the Office of the Chief Medical Examiner (OCME) in describing drug overdose trends. Due to its real-time nature, syndromic surveillance data could act as an early indicator for emerging drug problems in the community, serving as an alert to public health.

Objective

Determine if syndromic surveillance data can be used to provide a real-time picture of the drug using population by analyzing trends of emergency department (ED) visits for unintentional drug overdose (Overdose Visits) in conjunction with unintentional deaths that prescription or illicit opiates contributed to or caused (Overdose Deaths).

Recreational drug use is a major problem in the United States and around the world. Specifically, drug abuse results in heavy use of emergency department (ED) services, and is a high financial burden to society and to the hospitals due to chronic ill health and multiple injection drug use complications. Intravenous drug users are at high risk of developing sepsis and endocarditis due to the use of a dirty or infected needle that is either shared with someone else or re-used. It can also occur when a drug user repeatedly injects into an inflamed and infected site or due to the poor overall health of an injection drug user. The average cost of hospitalization for aortic valve replacement in USA is about $165,000, and in order for the valve replacement to be successful, patients must abstain from using drugs.

Objective

To describe how the state syndromic surveillance system (NC DETECT) was used to initiate near real time surveillance for endocarditis, sepsis and skin infection among drug users.

Although Marin County ranks as the healthiest county in California, it ranks poorly in substance abuse indicators, including drug overdose mortality.1 Death certificates do not always include specific detail on the substances involved in a drug overdose.2 This lack of specificity makes it difficult to identify public health issues related to specific prescription drugs in our community. We analyzed 2013 drug overdose death toxicology reports to determine if they could improve the description of drug overdose deaths in our community and to describe associated data characteristics.

Objective

To describe the potential impact of using toxicology data to support drug overdose mortality surveillance.

Drug overdoses are an increasingly serious problem in the United States and worldwide. The CDC estimates that 47,055 drug overdose deaths occurred in the United States in 2014, 61% of which involved opioids (including heroin, pain relievers such as oxycodone, and synthetics).1 Overdose deaths involving opioids increased 3-fold from 2000 to 2014.1 These statistics motivate public health to identify emerging trends in overdoses, including geographic, demographic, and behavioral patterns (e.g., which combinations of drugs are involved). Early detection can inform prevention and response efforts, as well as quantifying the effects of drug legislation and other policy changes.

The fast subset scan2 detects significant spatial patterns of disease by efficiently maximizing a log-likelihood ratio statistic over subsets of data points, and has recently been extended to multidimensional data (MD-Scan).3 While MD-Scan is a potentially useful tool for drug overdose surveillance, the high dimensionality and sparsity of the data requires a new approach to estimate and represent baselines (expected counts), maintaining both accuracy and efficient computation when searching over subsets. 

Objective

We present the multidimensional tensor scan (MDTS), a new method for identifying emerging patterns in multidimensional spatio-temporal data, and demonstrate the utility of this approach for discovering emerging geographic, demographic, and behavioral trends in fatal drug overdoses.