scholarly journals Using NC DETECT for Comprehensive Morbidity Surveillance on Poisoning and Overdose

2015 ◽  
Vol 7 (1) ◽  
Author(s):  
Amy Ising ◽  
Katherine J. Harmon ◽  
Anna E. Waller ◽  
Scott Proescholdbell ◽  
Lana Deyneka
Keyword(s):  
North Carolina ◽  
Drug Overdose ◽  
Opioid Analgesic ◽  
Prescription Opioid ◽  
Opioid Overdose ◽  
Aggregate Level ◽  
Case Definitions ◽  
Alcohol Poisoning ◽  
Methadone Overdose ◽  
Line Listing

Twelve new locally defined case definitions were added to NC DETECT in May and June 2014 to facilitate timely surveillance for poisoning and overdose in North Carolina. The case definitions cover acute alcohol poisoning, poisoning, unintentional poisoning, heroin overdose, medication or drug overdose, methadone overdose, opioid overdose, prescription opioid analgesic overdose, Narcan/naloxone, and unintentional medication or drug overdose. Authorized users can monitor trends and review line listing details for their jurisdictions and compare their counties at the aggregate level to other counties and the state.

Economic Conditions and Drug and Opioid Overdose Deaths

2017 ◽  
Vol 76 (4) ◽  
pp. 462-477 ◽  
Author(s):  
Ezequiel Brown ◽  
George L. Wehby
Keyword(s):  
Drug Overdose ◽  
Fixed Effects ◽  
House Prices ◽  
Insurance Coverage ◽  
House Price ◽  
State Level ◽  
Economic Conditions ◽  
Prescription Opioid ◽  
Opioid Overdose ◽  
Overdose Deaths

We examine the effects of state-level economic conditions including unemployment rates, median house price, median household income, insurance coverage, and annual and weekly work time on deaths on drug overdose deaths including from opioids and prescription opioids between 1999 and 2014. We employ difference-in-differences estimation controlling for state and year fixed effects, state-specific time trends, and demographic characteristics. Drug overdose deaths significantly declined with higher house prices, an effect driven by reduction in prescription-opioid mortality, by nearly 0.17 deaths per 100,000 (~4%) with a $10,000 increase in median house price. House price effects were more pronounced and only significant among males, non-Hispanic Whites, and individuals younger 45 years. Other economic indicators had insignificant effects. Our findings suggest that economic downturns that substantially reduce house prices such as the Great Recession can increase opioid-related deaths, suggesting that efforts to control access to such drugs should especially intensify during these periods.

scholarly journals Improving risk factor identification for opioid overdose deaths in Tennessee

2019 ◽  
Vol 11 (1) ◽  
Author(s):  
Sarah J. Nechuta ◽  
Jenna Moses ◽  
Molly Golladay ◽  
Adele Lewis ◽  
Julia Goodin ◽  
...  
Keyword(s):  
Risk Factor ◽  
Drug Overdose ◽  
Medical Examiner ◽  
Prescription Opioid ◽  
Opioid Overdose ◽  
Prescription Opioids ◽  
Death Certificates ◽  
Postmortem Toxicology ◽  
Icd 10 ◽  
Overdose Deaths

ObjectiveTo examine specific drugs present based on postmortem toxicology for prescription opioid, heroin, and fentanyl overdoses classified based on ICD-10 coding. To compare drugs identified from postmortem toxicology with those listed on the death certificate for opioid overdoses.IntroductionUsing death certificates alone to identify contributing substances in drug overdose deaths may result in misclassification and underestimation of the burden of illicit and prescription opioids and other drugs in drug-related deaths. To enable timely and targeted prevention in Tennessee (TN), the identification and monitoring of new drugs and trends in use should utilize toxicology and medicolegal death investigation data directly, as recommended by others 1-3. These data can inform mortality outcome definitions for improved surveillance and risk factor identification 4-7. To our knowledge, this is the first analysis to use statewide linked toxicology and death certificate data in TN.MethodsWe identified 615 opioid involved overdose deaths in TN of unintentional (underlying ICD-10 codes: X40-X44) or undetermined (underlying ICD-10 codes: Y10-Y14) intent during June 1st to December 31st 2017. Utilizing the Interim Medical Examiner Database (I-MED), we identified postmortem toxicology reports for 454 cases, which were from one of three national laboratories used by a state Regional Forensic Center. Toxicology data were abstracted and independently verified by two co-authors and linked to the TN death statistical file that included cause of death information (literal text and ICD-10 codes) and demographics. The analysis focuses on cases with an available toxicology report.ResultsWe identified 171 prescription opioid overdoses, 221 fentanyl overdoses, and 113 heroin overdoses. Table 1 displays postmortem toxicology profiles for major drugs/classes. For prescription opioid deaths (excluding fentanyl and heroin), positive toxicology results for prescription opioids were as follows: methadone (11%), buprenorphine (14%), hydrocodone (14%), oxycodone (36%) and oxymorphone (also a metabolite, 47%). Benzodiazepines were present in close to 58% of prescription opioid overdoses; stimulants (cocaine, amphetamines, methamphetamines) in about 25%. For fentanyl and heroin deaths, prescription opioids were detected in about 26% and 34%, respectively; stimulants in about 57.9% and 52.2%, respectively, and benzodiazepines 36-37%. Fentanyl was present on toxicology in about half of heroin overdoses, and 6–monoacetylmorphine in 72.6%.ConclusionsUsing medical examiners’ data, including toxicology data, improves estimation of contributing drugs involved in opioid deaths. This analysis provides jurisdiction-specific data on drugs that can help with monitoring trends and informs risk factor identification. Future work includes adding information on prescribed opioid and benzodiazepines using TN’s Prescription Drug Monitoring Database and evaluating demographic variation in contributing drugs between toxicology and DC data to identify susceptible populations.References1. Slavova S, O'Brien DB, Creppage K, Dao D, Fondario A, Haile E, Hume B, Largo TW, Nguyen C, Sabel JC, Wright D, Council of S, Territorial Epidemiologists Overdose S. Drug Overdose Deaths: Let's Get Specific. Public Health Rep.2. Horon IL, Singal P, Fowler DR, Sharfstein JM. Standard Death Certificates Versus Enhanced Surveillance to Identify Heroin Overdose-Related Deaths. Am J Public Health. 2018;108(6):777-81.3. Mertz KJ, Janssen JK, Williams KE. Underrepresentation of heroin involvement in unintentional drug overdose deaths in Allegheny County, PA. J Forensic Sci. 2014;59(6):1583-5.4. Landen MG, Castle S, Nolte KB, Gonzales M, Escobedo LG, Chatterjee BF, Johnson K, Sewell CM. Methodological issues in the surveillance of poisoning, illicit drug overdose, and heroin overdose deaths in new Mexico. Am J Epidemiol. 2003;157(3):273-8.5. Davis GG, National Association of Medical E, American College of Medical Toxicology Expert Panel on E, Reporting Opioid D. Complete republication: National Association of Medical Examiners position paper: Recommendations for the investigation, diagnosis, and certification of deaths related to opioid drugs. J Med Toxicol. 2014;10(1):100-6.6. Slavova S, Bunn TL, Hargrove SL, Corey T. Linking Death Certificates, Postmortem Toxicology, and Prescription History Data for Better Identification of Populations at Increased Risk for Drug Intoxication Deaths. Pharmaceutical Medicine. 2017;31(3):155-65.7. Hurstak E, Rowe C, Turner C, Behar E, Cabugao R, Lemos NP, Burke C, Coffin P. Using medical examiner case narratives to improve opioid overdose surveillance. Int J Drug Policy. 2018;54:35-42. 

scholarly journals Assessment of a Surveillance Case Definition for Heroin Overdose in Emergency Medical Services Data

2018 ◽  
Vol 10 (1) ◽  
Author(s):  
Michael D. Singleton ◽  
Peter J. Rock
Keyword(s):  
Emergency Medical Services ◽  
Drug Overdose ◽  
Case Definition ◽  
Opioid Overdose ◽  
Data Systems ◽  
Case Definitions ◽  
Heroin Overdose ◽  
Emergency Medical ◽  
Icd 10 ◽  
Data Elements

ObjectiveThe aims of this project were 1) to assess the validity of a surveillance case definition for identifying heroin overdoses (HOD) in a NEMSIS 3–compliant, state ambulance reporting system; and 2) to develop an approach that can be applied to assess the validity of case definitions for other types of drug overdose events in similar data state data systems.IntroductionIn 2016, the Centers for Disease Control and Prevention funded 12 states, under the Enhanced State Opioid Overdose Surveillance (ESOOS) program, to utilize state Emergency Medical Services (EMS) and emergency department (ED) syndromic surveillance (SyS) data systems to increase timeliness of state data on drug overdoses. A key aspect of the ESOOS program is the development and validation of case definitions for drug overdoses for EMS and ED SyS data systems. Kentucky’s ESOOS team conducted a pilot validation study of a candidate EMS case definition for HOD, using data from the Kentucky State Ambulance Reporting System (KStARS). We examined internal, face validity of the EMS HOD case definition by reviewing pertinent information captured in KStARS data elements; and we examined external agreement with HOD cases identified Kentucky’s statewide hospital billing database.MethodsFrom KStARS, we extracted EMS emergent transports by any ambulance service to hospitals in a single, large health care system in Kentucky. We included responses with dispatch dates between January 1, 2017 and March 31, 2017. From Kentucky’s statewide hospital claims data system, we extracted inpatient discharges, ED visits and observational stays at the destination hospitals, with admit dates in the same range. We classified EMS cases as HOD based on specific combinations of the following criteria for EMS data elements: primary or secondary provider impression of heroin poisoning (T40.1X4), heroin-related keywords in the patient care narrative or chief complaint, and patient’s response to naloxone as indicated in the medications list1. We used standard drug overdose case definitions for ICD-10-CM-coded hospital billing data2 to classify hospital records from the destination facilities to the same categories. We produced descriptive analyses of the heroin overdose cases detected in both data sources, EMS and hospital. To assess the degree of overlap in the HOD cases identified by the two data systems, we matched the identified EMS HOD cases against the entire set of UKHC hospital cases. Finally, we assessed the validity of the classification of EMS cases as heroin overdoses by reviewing the EMS patient care narratives and related EMS data elements, as well as the ICD-10-CM hospital diagnostic codes for cases that matched to a hospital record.ResultsWe identified 5,517 emergent EMS transports to the destination hospitals in the first quarter of 2017. Of these, 94 (17/1,000) were identified by our case definition as a HOD. We identified 29,631 unduplicated, emergent encounters at the destination hospitals (including inpatient discharges, ED visits, and observational stays; and excluding elective and newborn encounters). Of these, 105 (3.5/1,000) included a diagnostic code for HOD. Linkage of EMS and hospital cases indicated that 141 unique HOD cases were identified in the two files combined. Of these, 58 (41%) were identified as HOD in both systems. 23 HOD cases identified in EMS were matched to a hospital record that had no mention of a HOD; and 13 could not be matched to a hospital record. Additionally, 47 HOD cases identified in the destination hospitals were not matched to an EMS transport to those destination facilities. Overall, 76 out of the 94 (81%) EMS cases identified as heroin overdoses were judged likely to be true heroin overdoses, as indicated by either 1) positive response to naloxone and patient admission of recent heroin use, or 2) hospital diagnosis of heroin overdose, or both. For 2% of identified cases, there was evidence of a false positive finding. The remaining 17% of identified heroin cases were inconclusive: there was information suggestive of opioid overdose, but no clear evidence to suggest, nor to rule out, that the opioid was heroin. Generally, inconclusive cases were identified as heroin overdoses due to positive response to naloxone, combined with mention of the word “heroin” in the narrative that did not indicate an HOD. Examples of the latter include negations (patient denies heroin use) or a bystander who stated that the patient had a history of heroin use.ConclusionsWe assessed the performance of a straightforward case definition for heroin overdose for EMS data. Face validity of 81% of identified heroin overdoses was supported by clerical review of EMS records and/or hospital ICD-10-CM diagnostic codes. Some proportion of the other 19% of cases that were identified as heroin overdoses may have been overdoses involving opioids other than heroin, but we could not quantify that proportion based on the available information.Future work will consider sensitivity (true heroin overdoses that may fail to be captured by this case definition) and refinements to the basic definition that may yield improved results. Lessons learned from this pilot project will inform subsequent, larger-scale validation studies for EMS drug overdose case definitions.References1. Rhode Island Enhanced State Opioid Overdose Surveillance (ESOOS). Case Definition for Emergency Medical Services. Aug 2017.2. Injury Surveillance Workgroup 7. Consensus Recommendations for National and State Poisoning Surveillance. The Safe States Alliance. Atlanta, GA. April 2012.

0035 Development of 12 poisoning and drug overdose case definitions for use with emergency department data in North Carolina

2015 ◽  
Vol 21 (Suppl 1) ◽  
pp. A27.2-A28 ◽  
Author(s):  
Katherine Harmon ◽  
Amy Ising ◽  
Scott Proescholdbell ◽  
Clifton Barnett ◽  
Steve Marshall ◽  
...  
Keyword(s):  
Emergency Department ◽  
North Carolina ◽  
Drug Overdose ◽  
Case Definitions ◽  
Emergency Department Data

scholarly journals Restoration of breathing after opioid overdose and spinal cord injury using temporal interference stimulation

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Michael D. Sunshine ◽  
Antonino M. Cassarà ◽  
Esra Neufeld ◽  
Nir Grossman ◽  
Thomas H. Mareci ◽  
...  
Keyword(s):  
Spinal Cord ◽  
Spinal Cord Injury ◽  
Motor Neurons ◽  
Drug Overdose ◽  
Cervical Spinal Cord ◽  
Opioid Overdose ◽  
Electrode Position ◽  
Spinal Motor Neurons ◽  
Cord Injury ◽  
Low Amplitude

AbstractRespiratory insufficiency is a leading cause of death due to drug overdose or neuromuscular disease. We hypothesized that a stimulation paradigm using temporal interference (TI) could restore breathing in such conditions. Following opioid overdose in rats, two high frequency (5000 Hz and 5001 Hz), low amplitude waveforms delivered via intramuscular wires in the neck immediately activated the diaphragm and restored ventilation in phase with waveform offset (1 Hz or 60 breaths/min). Following cervical spinal cord injury (SCI), TI stimulation via dorsally placed epidural electrodes uni- or bilaterally activated the diaphragm depending on current and electrode position. In silico modeling indicated that an interferential signal in the ventral spinal cord predicted the evoked response (left versus right diaphragm) and current-ratio-based steering. We conclude that TI stimulation can activate spinal motor neurons after SCI and prevent fatal apnea during drug overdose by restoring ventilation with minimally invasive electrodes.

A Mixed-Methods Comparison of a National and State Opioid Overdose Surveillance Definition

2021 ◽  
Vol 136 (1_suppl) ◽  
pp. 31S-39S
Author(s):  
Danielle M. Brathwaite ◽  
Catherine S. Wolff ◽  
Amy I. Ising ◽  
Scott K. Proescholdbell ◽  
Anna E. Waller
Keyword(s):  
North Carolina ◽  
False Positive ◽  
False Positive Rate ◽  
International Classification Of Diseases ◽  
Opioid Overdose ◽  
The North ◽  
Classification Of Diseases ◽  
Positive Rate ◽  
Icd 10 ◽  
Ed Visits

Objectives We assessed the differences between the first version of the Centers for Disease Control and Prevention (CDC) opioid surveillance definition for suspected nonfatal opioid overdoses (hereinafter, CDC definition) and the North Carolina Disease Event Tracking and Epidemiologic Collection Tool (NC DETECT) surveillance definition to determine whether the North Carolina definition should include additional International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) codes and/or chief complaint keywords. Methods Two independent reviewers retrospectively reviewed data on North Carolina emergency department (ED) visits generated by components of the CDC definition not included in the NC DETECT definition from January 1 through July 31, 2018. Clinical reviewers identified false positives as any ED visit in which available evidence supported an alternative explanation for patient presentation deemed more likely than an opioid overdose. After individual assessment, reviewers reconciled disagreements. Results We identified 2296 ED visits under the CDC definition that were not identified under the NC DETECT definition during the study period. False-positive rates ranged from 2.6% to 41.4% for codes and keywords uniquely identifying ≥10 ED visits. Based on uniquely identifying ≥10 ED visits and a false-positive rate ≤10.0%, 4 of 16 ICD-10-CM codes evaluated were identified for NC DETECT definition inclusion. Only 2 of 25 keywords evaluated, “OD” and “overdose,” met inclusion criteria to be considered a meaningful addition to the NC DETECT definition. Practice Implications Quantitative and qualitative trends in coding and keyword use identified in this analysis may prove helpful for future evaluations of surveillance definitions.

scholarly journals Linking Emergency Medical Services and Emergency Department Data to Improve Overdose Surveillance in North Carolina

2021 ◽  
Vol 136 (1_suppl) ◽  
pp. 54S-61S
Author(s):  
Jonathan Fix ◽  
Amy I. Ising ◽  
Scott K. Proescholdbell ◽  
Dennis M. Falls ◽  
Catherine S. Wolff ◽  
...  
Keyword(s):  
Emergency Department ◽  
North Carolina ◽  
Emergency Medical Services ◽  
Data Linkage ◽  
Medical Services ◽  
Opioid Overdose ◽  
Naloxone Administration ◽  
Emergency Medical ◽  
Diagnosis Codes ◽  
Linkage Methods

Introduction Linking emergency medical services (EMS) data to emergency department (ED) data enables assessing the continuum of care and evaluating patient outcomes. We developed novel methods to enhance linkage performance and analysis of EMS and ED data for opioid overdose surveillance in North Carolina. Methods We identified data on all EMS encounters in North Carolina during January 1–November 30, 2017, with documented naloxone administration and transportation to the ED. We linked these data with ED visit data in the North Carolina Disease Event Tracking and Epidemiologic Collection Tool. We manually reviewed a subset of data from 12 counties to create a gold standard that informed developing iterative linkage methods using demographic, time, and destination variables. We calculated the proportion of suspected opioid overdose EMS cases that received International Classification of Diseases, Tenth Revision, Clinical Modification diagnosis codes for opioid overdose in the ED. Results We identified 12 088 EMS encounters of patients treated with naloxone and transported to the ED. The 12-county subset included 1781 linkage-eligible EMS encounters, with historical linkage of 65.4% (1165 of 1781) and 1.6% false linkages. Through iterative linkage methods, performance improved to 91.0% (1620 of 1781) with 0.1% false linkages. Among statewide EMS encounters with naloxone administration, the linkage improved from 47.1% to 91.1%. We found diagnosis codes for opioid overdose in the ED among 27.2% of statewide linked records. Practice Implications Through an iterative linkage approach, EMS–ED data linkage performance improved greatly while reducing the number of false linkages. Improved EMS–ED data linkage quality can enhance surveillance activities, inform emergency response practices, and improve quality of care through evaluating initial patient presentations, field interventions, and ultimate diagnoses.

scholarly journals Evaluation of a Medicaid performance improvement project to reduce high-dose opioid prescriptions

2022 ◽  
Vol 22 (1) ◽  
Author(s):  
Daniel M. Hartung ◽  
Jonah Geddes ◽  
Sara E. Hallvik ◽  
P. Todd Korthuis ◽  
Luke Middleton ◽  
...  
Keyword(s):  
Performance Improvement ◽  
Emergency Department Visits ◽  
Prescription Opioid ◽  
High Dose ◽  
Opioid Overdose ◽  
Opioid Use ◽  
Improvement Project ◽  
Opioid Prescribing ◽  
Percentage Points ◽  
Prescription Opioid Use

Abstract Background In 2015, Oregon’s Medicaid program implemented a performance improvement project to reduce high-dose opioid prescribing across its 16 coordinated care organizations (CCOs). The objective of this study was to evaluate the effect of that program on prescription opioid use and outcomes. Methods Using Medicaid claims data from 2014 to 2017, we conducted interrupted time-series analyses to examine changes in the prescription opioid use and overdose rates before (July 2014 to June 2015) and after (January 2016 to December 2017) implementation of Oregon’s high-dose policy initiative (July 2015 to December 2015). Prescribing outcomes were: 1) total opioid prescriptions 2) high-dose [> 90 morphine milligram equivalents per day] opioid prescriptions, and 3) proportion of opioid prescriptions that were high-dose. Opioid overdose outcomes included emergency department visits or hospitalizations that involved an opioid-related poisoning (total, heroin-involved, non-heroin involved). Analyses were performed at the state and CCO level. Results There was an immediate reduction in high dose opioid prescriptions after the program was implemented (− 1.55 prescription per 1000 enrollee; 95% CI − 2.26 to − 0.84; p < 0.01). Program implementation was also associated with an immediate drop (− 1.29 percentage points; 95% CI − 1.94 to − 0.64 percentage points; p < 0.01) and trend reduction (− 0.23 percentage point per month; 95% CI − 0.33 to − 0.14 percentage points; p < 0.01) in the monthly proportion of high-dose opioid prescriptions. The trend in total, heroin-involved, and non-heroin overdose rates increased significantly following implementation of the program. Conclusions Although Oregon’s high-dose opioid performance improvement project was associated with declines in high-dose opioid prescriptions, rates of opioid overdose did not decrease. Policy efforts to reduce opioid prescribing risks may not be sufficient to address the growing opioid crisis.

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