Demographic, geographic, and temporal patterns of ambulance runs for suspected opiate overdose in Rhode Island, 1997-20021

The changing epidemiology of opioid overdose in Baltimore, Maryland, 2012-2017: insights from emergency medical services

INTRODUCTION

An estimated 100,306 people died from an overdose from May 2020 to April 2021. Emergency Medical Services (EMS) are often the first responder to opioid overdose, and EMS encounter records can provide granular epidemiologic data on opioid overdose. This study describes the demographic, temporal, and geographic epidemiology of suspected opioid overdose in Baltimore City using data from Baltimore City Fire Department EMS encounters with the administration of the opioid antagonist naloxone.

METHOD

The present analyses used patient encounter data from 2012 to 2017 from the Baltimore City Fire Department, the city's primary provider of EMS services. The analytic sample included patient encounters within the city that involved naloxone administration to patients 15 years of age or older (n = 20,592). Negative binomial regression was used to calculate the incidence rates based on demographic characteristics, year, and census tract. Choropleth maps were used to show the geographic distribution of overdose incidence across census tracts in 2013, 2015, and 2017.

RESULTS

From 2012 to 2017, the annual number of EMS encounters with naloxone administrations approximately doubled every 2 years, and the temporal pattern of naloxone administration was similar to the pattern of fatal opioid-related overdoses. For most census tracts, incidence rates significantly increased over time. Population-based incidence of naloxone administration varied significantly by socio-demographic characteristics. Males, non-whites, and those 25-69 years of age had the highest incidence rates.

CONCLUSION

The incidence of naloxone administration increased dramatically over the study period. Despite significant cross-sectional variation in incidence across demographically and geographically defined groups, there were significant proportional increases in incidence rates, consistent with fatal overdose rates over the period. This study demonstrated the value of EMS data for understanding the local epidemiology of opioid-related overdose. Key MessagesPatterns of EMS encounters with naloxone administration appear to be an excellent proxy for patterns of opioid-related overdoses based on the consistency of fatal overdose rates over time.EMS plays a central role in preventing fatal opioid-related overdoses through the administration of naloxone, provision of other emergency services, and transportation to medical facilities.EMS encounters with naloxone administration could also be used to evaluate the impact of overdose prevention interventions and public health services.

Spatial clustering of heroin-related overdose incidents: a case study in Cincinnati, Ohio

Background

Drug overdose is one of the top leading causes of accidental death in the U.S., largely due to the opioid epidemic. Although the opioid epidemic is a nationwide issue, it has not affected the nation uniformly.

Methods

We combined multiple data sources, including emergency medical service response, American Community Survey data, and health facilities datasets to analyze distributions of heroin-related overdose incidents in Cincinnati, Ohio at the census block group level. The Ripley’s K function and the local Moran’s I statistics were performed to examine geographic variation patterns in heroin-related overdose incidents within the study area. Then, conditional cluster maps were plotted to examine a relationship between heroin-related incident rates and sociodemographic characteristics of areas as well as the resources for opioid use disorder treatment.

Results

The global spatial analysis indicated that there was a clustered pattern of heroin-related overdose incident rates at every distance across the study area. The univariate local spatial analysis identified 7 hot spot clusters, 27 cold spot clusters, and 1 outlier cluster. Conditional cluster maps showed characteristics of neighborhoods with high heroin overdose rates, such as a higher crime rate, a high percentage of the male, a high poverty level, a lower education level, and a lower income level. The hot spots in the Southwest areas of Cincinnati had longer distances to opioid treatment programs and buprenorphine prescribing physicians than the median, while the hot spots in the South-Central areas of the city had shorter distances to those health resources.

Conclusions

Our study showed that the opioid epidemic disproportionately affected Cincinnati. Multi-phased spatial clustering models based on various data sources can be useful to identify areas that require more policy attention and targeted interventions to alleviate high heroin-related overdose rates.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-13557-3.

Acceleration of opioid-related EMS runs in the spring of 2020: The National Emergency Medical Services Information System data for 2018-2020

BACKGROUND

State- and county-level reports suggest that the COVID-19 pandemic exacerbated the opioid crisis. We examined US national trends of nonfatal opioid overdose in 2020 in comparison to pre-COVID years 2018-2019.

METHODS

We used National Emergency Medical Services Information System (NEMSIS) data to conduct a temporal analysis from 2018 to 2020. Opioid-related EMS run was defined using five scenarios of naloxone administration. To determine annual patterns and slope inflection points, we used the Prophet model of the time series analysis. Linear slopes and their 95% confidence intervals (CIs) were calculated for pre-stay-at-home (pre-SaH) and SaH periods in 2020 and compared to the slopes during the same time in 2018-2019. Three cut-points for SaH start were considered: March 19, 24, and 29.

RESULTS

We identified 91,065, 144,802, and 242,904 opioid-related EMS runs in 2018-2020, respectively. In 2020, opioid-related runs increased in January-June, with a pronounced acceleration in March, which coincides with the stay-at-home (SaH) orders. In both 2018 and 2019, opioid-related runs increased in January-August without the spring acceleration. In 2020, weekly increases (95% CI) during SaH for all examined cut-points were significantly greater than in pre-SaH: 18.09 (16.03-20.16) vs. 6.44 (3.42-9.47) for March 19, 17.77 (15.57-19.98) vs. 4.85 (2.07-7.64) for March 24, 18.03 (15.68-20.39) vs. 4.97(2.4-7.54) for March 29. No significant difference was found between these periods in 2018-2019.

CONCLUSIONS

The acceleration of opioid-related EMS runs during the SaH period of 2020 suggests that EMS data may serve as an early warning system for local health jurisdictions to deploy harm reduction/prevention resources.

Ineffectiveness of paramedic naloxone administration as a standalone metric for community opioid overdoses and the increasing use of naloxone by community members

Introduction:With Canada's growing opioid crisis, many communities are attempting to monitor cases in real-time. Paramedic Naloxone Administration (PNA) has become a common metric for monitoring overdoses. We evaluate whether the use of naloxone administration counts represents an effective monitoring tool for community opioid overdoses.Methods:The electronic ambulance call report database of Peterborough Paramedics (Ontario, Canada) was examined. De-identified records from 2016-2019 with problem codes of "Opioid Overdose", along with all patients documented as receiving naloxone were extracted. Chi-square and Bonferroni-adjusted post hoc proportion tests were used for comparison of counts.Results:558 opioid overdoses were identified, 124 (22%) of which had PNA documented, 181(32%) had naloxone prior to arrival documented and 264 (47%) received no naloxone. Over the three years, the annual number of overdose cases increased, while the proportion of patients receiving PNA decreased significantly each year. PNA was also associated with calls in a residence. Naloxone was administered by a non-paramedic in 262 cases, with 181 of these identified as opioid overdoses and was more common in later years and in cases occurring in public places.Conclusion:PNA calls did not account for a significant percentage of opioid overdoses attended to by paramedics. The strong association between PNA and call location being a residence, along with increasing use of community naloxone kits, may cause certain populations to be under-represent if PNA is used as a standalone metric. The decreasing association with time may also lead to a falsely improving metric further reducing its effectiveness. Thus, PNA when used alone may no longer be a suitable metric for opioid overdose tracking.

The spatio-temporal distribution of naloxone administration events in rural Ohio 2010-16

INTRODUCTION

In 2017, Ohio had the second highest rate of drug overdose deaths in the United States. Current opioid related epidemiologic literature has begun to uncover the environmental level influences on the opioid epidemic and how the end results may ultimately manifest over space and time. This work is still nascent however, with most clustering research conducted at a spatial unit such as county level, which (1) can obscure differences between urban and rural communities, (2) does not consider dynamics that cross county lines, and (3) is difficult to interpret directly into strategic and localized intervention efforts. We address this gap by describing, at the Census block level, the spatial-temporal clustering of opioid related events in rural Ohio.

METHODS

We use the outcome of the administration of naloxone emergency medical service (EMS) calls in rural Ohio Census blocks during 2010-16 in a Poisson model of spatial scan statistics.

RESULTS

We found that naloxone event clustering in rural Ohio in the recent decade was widely dispersed over time and space, with clusters that average 17 times the risk of having an event compared to areas outside the cluster. Many of the larger spatial clusters crossed administrative boundaries (i.e., county lines) suggesting that opioid misuse may be less responsive to county level policies than to other factors.

DISCUSSION

Timely identification of localized overdose event clustering can guide affected communities toward rapid interventions aimed at minimizing the morbidity and mortality resulting from contagious opioid misuse.

A descriptive study of racial and ethnic differences of drug overdoses and naloxone administration in Pennsylvania

INTRODUCTION

Drug overdose is a significant public health problem, yet little is known about racial/ethnic differences in drug overdose rates and/or in responses to a drug overdose following naloxone administration. This paper examines differences in rates of survivorship, response, revival and administration of naloxone by race and ethnicity among those who experienced a drug overdose in Pennsylvania between January 1, 2018 and December 31, 2019. Spatio-temporal variations in drug overdose locations were examined to facilitate understanding of service development, planning, and delivery of effective treatment need.

METHODS

Ten thousand two hundred and ninety drug overdose incidents were analyzed from the Pennsylvania Overdose Information Network (ODIN). The ODIN is a centralized repository that contains information on drug overdoses victims including age, gender and race/ethnicity, naloxone administrations and survivorship, drug(s) suspected of causing the overdose, victim outcomes (e.g. hospitalizations and arrests) and average naloxone dosage per victim. Between group differences were tested using χ2 -tests of independence. Multivariate logistic regression was used to estimate the predicted probability of survivorship according to victim characteristics. All statistical analyses and mapping were performed using the R statistical programming environment.

RESULTS

About eighty-seven percent of drug overdose response victims were white, and seventy-one percent were between the ages of 20-39. White females were more likely to receive an overdose response compared to black or Hispanic females. A non-opioid was indicated more frequently in overdoses involving black victims compared to either whites or Latinos. Latinos and blacks were more likely to survive a drug overdose. However, following naloxone administration, no racial or ethnic differences in survivorship were noted. Differences in responsiveness to naloxone and transitions to care following the drug overdose event were also found. Finally, overdoses among Blacks and Latinos demonstrated a stronger spatial patterning across counties compared to whites.

CONCLUSIONS

This study found a significant, disparate impact of race/ethnicity on fatal drug overdoses when naloxone is not administered. Further, individuals who were administered naloxone and subsequently received medical care in a hospital experienced lower drug-related mortality, suggesting that first responders are critical intervention points for individuals in need of medical treatment following a drug overdose. However, while naloxone administration is a necessary first step in the recovery process, longitudinal pathways towards treatment are critical to stem the drug overdose crisis.

The Detection of Opioid Misuse and Heroin Use From Paramedic Response Documentation: Machine Learning for Improved Surveillance

Background

Timely, precise, and localized surveillance of nonfatal events is needed to improve response and prevention of opioid-related problems in an evolving opioid crisis in the United States. Records of naloxone administration found in prehospital emergency medical services (EMS) data have helped estimate opioid overdose incidence, including nonhospital, field-treated cases. However, as naloxone is often used by EMS personnel in unconsciousness of unknown cause, attributing naloxone administration to opioid misuse and heroin use (OM) may misclassify events. Better methods are needed to identify OM.

Objective

This study aimed to develop and test a natural language processing method that would improve identification of potential OM from paramedic documentation.

Methods

First, we searched Denver Health paramedic trip reports from August 2017 to April 2018 for keywords naloxone, heroin, and both combined, and we reviewed narratives of identified reports to determine whether they constituted true cases of OM. Then, we used this human classification as reference standard and trained 4 machine learning models (random forest, k-nearest neighbors, support vector machines, and L1-regularized logistic regression). We selected the algorithm that produced the highest area under the receiver operating curve (AUC) for model assessment. Finally, we compared positive predictive value (PPV) of the highest performing machine learning algorithm with PPV of searches of keywords naloxone, heroin, and combination of both in the binary classification of OM in unseen September 2018 data.

Results

In total, 54,359 trip reports were filed from August 2017 to April 2018. Approximately 1.09% (594/54,359) indicated naloxone administration. Among trip reports with reviewer agreement regarding OM in the narrative, 57.6% (292/516) were considered to include information revealing OM. Approximately 1.63% (884/54,359) of all trip reports mentioned heroin in the narrative. Among trip reports with reviewer agreement, 95.5% (784/821) were considered to include information revealing OM. Combined results accounted for 2.39% (1298/54,359) of trip reports. Among trip reports with reviewer agreement, 77.79% (907/1166) were considered to include information consistent with OM. The reference standard used to train and test machine learning models included details of 1166 trip reports. L1-regularized logistic regression was the highest performing algorithm (AUC=0.94; 95% CI 0.91-0.97) in identifying OM. Tested on 5983 unseen reports from September 2018, the keyword naloxone inaccurately identified and underestimated probable OM trip report cases (63 cases; PPV=0.68). The keyword heroin yielded more cases with improved performance (129 cases; PPV=0.99). Combined keyword and L1-regularized logistic regression classifier further improved performance (146 cases; PPV=0.99).

Conclusions

A machine learning application enhanced the effectiveness of finding OM among documented paramedic field responses. This approach to refining OM surveillance may lead to improved first-responder and public health responses toward prevention of overdoses and other opioid-related problems in US communities.

Identifying high-risk areas for nonfatal opioid overdose: a spatial case-control study using EMS run data

PURPOSE

The objective of our study was to incorporate stricter probable nonfatal opioid overdose case criteria, and advanced epidemiologic approaches to more reliably detect local clustering in nonfatal opioid overdose activity in EMS runs data.

METHODS

Data were obtained using emsCharts for our study area in southwestern Pennsylvania from 2007 to 2018. Cases were identified as emergency medical service (EMS) responses where naloxone was administered, and improvement was noted in patient records between initial and final Glasgow Coma Score. A subsample of all-cause EMS responses sites were used as controls and exact matched to cases on sex and 10-year-age category. Clustering was assessed using difference in Ripley's K function for cases and controls and Kulldorff scan statistics.

RESULTS

Difference in K functions indicated no significant difference in probable nonfatal overdose EMS runs across the study area compared to all-cause EMS runs. However, scan statistics did identify significant local clustering of probable nonfatal overdose EMS runs (maximum likelihood = 16.40, P = 0.0003).

CONCLUSIONS

Results highlight relevance of EMS data to detect community-level overdose activity and promote reliable use through stricter case definition criteria and advanced methodological approaches. Techniques examined have the potential to improve targeted delivery of neighborhood-level public health response activities using a near real-time data source.

Naloxone distribution and possession following a large-scale naloxone programme

AIMS

To examine uptake following a large-scale naloxone programme by estimating distribution rates since programme initiation and the proportion among a sample of high-risk individuals who had attended naloxone training, currently possessed or had used naloxone. We also estimated the likelihood of naloxone possession and use as a function of programme duration, individual descriptive and substance use indicators.

DESIGN

(1) Distribution data (June 2014-August 2017) and date of implementation for each city and (2) a cross-sectional study among a sample of illicit substance users interviewed September 2017.

SETTING

Seven Norwegian cities.

PARTICIPANTS

A total of 497 recruited users of illegal opioids and/or central stimulants.

MEASUREMENTS

Primary outcomes: naloxone possession and use. Random-intercepts logistic regression models (covariates: male, age, homelessness/shelter use, overdose, incarceration, opioid maintenance treatment, income sources, substance use indicators, programme duration).

FINDINGS

Overall, 4631 naloxone nasal sprays were distributed in the two pilot cities, with a cumulative rate of 495 per 100 000 population. In the same two cities, among high-risk individuals, 44% and 62% reported current naloxone possession. The possession rates of naloxone corresponded well to the duration of each participating city's distribution programme. Overall, in the six distributing cities, 58% reported naloxone training, 43% current possession and 15% naloxone use. The significant indicators for possession were programme duration [adjusted odds ratios (aOR) = 1.44, 95% confidence interval (CI = 0.82-2.37], female gender (aOR = 1.97, 95% CI = 1.20-3.24) and drug-dealing (aOR = 2.36, 95% CI = 1.42-3.93). The significant indicators for naloxone use were programme duration (aOR = 1.49 95%, CI = 1.15-1.92), homelessness/shelter use (aOR = 2.06, 95% CI = 1.02-4.17), opioid maintenance treatment (OMT) (aOR = 2.07, 95% CI = 1.13-3.78), drug-dealing (aOR = 2.40, 95% CI = 1.27-4.54) and heroin injecting (aOR = 2.13, 95% CI = 1.04-4.38).

CONCLUSIONS

A large-scale naloxone programme in seven Norwegian cities with a cumulative distribution rate of 495 per 100 000 population indicated good saturation in a sample of high-risk individuals, with programme duration in each city as an important indicator for naloxone possession and use.

Risks of fatal opioid overdose during the first year following nonfatal overdose

BACKGROUND

Little is known about risk factors for repeated opioid overdose and fatal opioid overdose in the first year following nonfatal opioid overdose.

METHODS

We identified a national retrospective longitudinal cohort of patients aged 18-64 years in the Medicaid program who received a clinical diagnosis of nonfatal opioid overdose. Repeated overdoses and fatal opioid overdoses were measured with the Medicaid record and the National Death Index. Rates of repeat overdose per 1000 person-years and fatal overdose per 100,000 person-years were determined. Hazard ratios of repeated opioid overdose and fatal opioid overdose were estimated by Cox proportional hazards.

RESULTS

Nearly two-thirds (64.8%) of the patients with nonfatal overdoses (total n = 75,556) had filled opioid prescriptions in the 180 days before initial overdose. During the 12 months after nonfatal overdose, the rate of repeat overdose was 295.0 per 1000 person-years and that of fatal opioid overdose was 1154 per 100,000 person-years. After controlling for age, sex, race/ethnicity, and region, the hazard of fatal opioid overdose was increased for patients who had filled a benzodiazepine prescription in the 180 days prior to their initial overdose (HR = 1.71, 95%CI: 1.46-1.99), whose initial overdose involved heroin (HR = 1.57, 95%CI:1.30-1.89), or who required mechanical ventilation at the initial overdose (HR = 1.86, 95%CI = 1.50-2.31).

CONCLUSIONS

Adults treated for opioid overdose frequently have repeated opioid overdoses in the following year. They are also at high risk of fatal opioid overdose throughout this period, which underscores the importance of efforts to engage and maintain patients in evidence-based opioid treatments following nonfatal overdose.

Causes of Death After Nonfatal Opioid Overdose

Importance

A recent increase in patients presenting with nonfatal opioid overdoses has focused clinical attention on characterizing their risks of premature mortality.

Objective

To describe all-cause mortality rates, selected cause-specific mortality rates, and standardized mortality rate ratios (SMRs) of adults during their first year after nonfatal opioid overdose.

Design, Setting, and Participants

This US national longitudinal study assesses a cohort of patients aged 18 to 64 years who were Medicaid beneficiaries and experienced nonfatal opioid overdoses. The Medicaid data set included the years 2001 through 2007. Death record information was obtained from the National Death Index. Data analysis occurred from October 2017 to January 2018.

Main Outcomes and Measures

Crude mortality rates per 100 000 person-years were determined in the first year after nonfatal opioid overdose. Standardized mortality rate ratios (SMR) were estimated for all-cause and selected cause-specific mortality standardized to the general population with respect to age, sex, and race/ethnicity.

Results

The primary cohort included 76 325 adults and 66 736 person-years of follow-up. During the first year after nonfatal opioid overdose, there were 5194 deaths, the crude death rate was 778.3 per 10 000 person-years, and the all-cause SMR was 24.2 (95% CI, 23.6-24.9). The most common immediate causes of death were substance use-associated diseases (26.2%), diseases of the circulatory system (13.2%), and cancer (10.3%). For every cause examined, SMRs were significantly elevated, especially with respect to drug use-associated diseases (SMR, 132.1; 95% CI, 125.6-140.0), HIV (SMR, 45.9; 95% CI, 39.5-53.0), chronic respiratory diseases (SMR, 41.1; 95% CI, 36.0-46.8), viral hepatitis (SMR, 30.6; 95% CI, 22.9-40.2), and suicide (SMR, 25.9; 95% CI, 22.6-29.6), particularly including suicide among females (SMR, 47.9; 95% CI, 39.8-52.3).

Conclusions and Relevance

In a US national cohort of adults who had experienced a nonfatal opioid overdose, a marked excess of deaths was attributable to a wide range of substance use-associated, mental health, and medical conditions, underscoring the importance of closely coordinating the substance use, mental health, and medical care of this patient population.

Cracking the Code: Using Data to Combat the Opioid Crisis

The goal of this article is to understand the value of data and to call for efforts to explore improved data sharing and collection among local, state, and federal agencies. It discusses the data available and existing barriers to sharing it. It also looks at examples of data sharing initiatives and analysis, such as mapping and visualization tools. The article then examines relevant regulations and calls for reforms. Finally, the article considers objections, including privacy interests, data security, and the costs and benefits of data sharing initiatives.

Heroin and pharmaceutical opioid overdose events: Emergency medical response characteristics

BACKGROUND

Emergency Medical Services (EMS) data may provide insight into opioid overdose incidence, clinical characteristics, and medical response. This analysis describes patient characteristics, clinical features, and EMS response to opioid overdoses, comparing heroin and pharmaceutical opioid (PO) overdoses, using a structured opioid overdose case criteria definition.

METHODS

A case series study was conducted. EMS medical staff screened cases for possible overdoses and study staff categorized the likelihood of opioid overdose. Medical form data were abstracted. Patient characteristics, clinical presentation, and medical response to heroin and PO-involved overdoses were compared with bi-variate test statistics.

RESULTS

We identified 229 definite or probable opioid overdose cases over six months: heroin in 98 (43%) cases (10 also involved PO), PO without heroin in 85 (37%) cases, and 46 (20%) that could not be categorized and were excluded from analyses. Heroin overdose patients were younger than PO (median age 33 v 41 (p<0.05)), more often male (80% v 61% (p=<0.01)), intubated less (8% v 22%, p<0.01) and more likely to be administered naloxone (72% v 51%, p<0.01). No significant differences were found between heroin and PO overdoses for initial respiratory rate, Glasgow Coma Scale score, or co-ingestants, but heroin users were more likely to have miotic pupils (p<0.01).

CONCLUSIONS

While heroin and PO events presented similarly, heroin-involved cases were more likely to receive naloxone and less likely to be intubated. Standardized case definitions and data documentation could aid opioid overdose surveillance as well as provide data for measuring the impact of professional and lay interventions.

Multiple Naloxone Administrations Among Emergency Medical Service Providers is Increasing

BACKGROUND

Opioid overdoses are at epidemic levels in the United States. Emergency Medical Service (EMS) providers may administer naloxone to restore patient breathing and prevent respiratory arrest. There was a need for contemporary data to examine the number of naloxone administrations in an EMS encounter.

METHODS

Using data from the National Emergency Medical Services Information System, we examined data from 2012-5 to determine trends in patients receiving multiple naloxone administrations (MNAs). Logistic regression including demographic, clinical, and operational information was used to examine factors associated with MNA.

RESULTS

Among all events where naloxone was administered only 16.7% of the 911 calls specifically identified the medical emergency as a drug ingestion or poisoning event. The percentage of patients receiving MNA increased from 14.5% in 2012 to 18.2% in 2015, which represents a 26% increase in MNA in 4 years. Patients aged 20-29 had the highest percentage of MNA (21.1%). Patients in the Northeast and the Midwest had the highest relative MNA (Chi Squared = 539.5, p < 0.01 and Chi Squared = 351.2, p < 0.01, respectively). The logistic regression model showed that the adjusted odds ratios (aOR) for MNA were greatest among people who live in the Northeast (aOR = 1.18, 95% CI = 1.13-1.22) and for men (aOR = 1.13, 95% CI = 1.10-1.16), but lower for suburban and rural areas (aOR = 0.76, 95% CI = 0.72-0.80 and aOR = 0.85, 95% CI = 0.80-0.89) and lowest for wilderness areas (aOR = 0.76, 95% CI = 0.68-0.84). Higher adjusted odds of MNA occurred when an advanced life support (ALS 2) level of service was provided compared to basic life support (BLS) ambulances (aOR = 2.15, 95% CI = 1.45-3.16) and when the dispatch complaint indicated there was a drug poisoning event (aOR = 1.12, 95% CI = 1.09-1.16). Reported layperson naloxone administration prior to EMS arrival was rare (1%).

CONCLUSION

This study shows that frequency of MNA is growing over time and is regionally dependent. MNA may be a barometer of the potency of the opioid involved in the overdose. The increase in MNA provides support for a dosage review. Better identification of opioid related events in the dispatch system could lead to a better match of services with patient needs.

Circumstances surrounding non-fatal opioid overdoses attended by ambulance services

INTRODUCTION AND AIMS

Opioid overdose fatalities are a significant concern globally. Non-fatal overdoses have been described as a strong predictor for future overdoses, and are often attended by the ambulance services. This paper explores characteristics associated with non-fatal overdoses and aims to identify possible trends among these events in an urban area in Norway.

DESIGN AND METHODS

This is a retrospective analysis of non-fatal overdoses from Bergen ambulance services from 2012 to 2013. Demographic, temporal and geographic data were explored.

RESULTS

During the two years, 463 non-fatal opioid overdoses were attended by ambulance services. Ambulance call-outs occurred primarily during the late afternoon and evening hours of weekdays. Summer months had more overdoses than other seasons, with a peak in August. Overdoses were nearly twice as likely to occur in a public location in August (risk ratio 1.92, P = 0.042). Ambulance response times were more likely to be longer to private locations, and these victims were more likely to be treated and left at the scene. There was no difference in arrival time for drug-related and non-drug related dispatch.

DISCUSSION AND CONCLUSIONS

The temporal patterns suggest that non-fatal overdoses occur during non-recreational time periods. The longer ambulance response time and disposition for private addresses indicate potential opportunities for peer interventions. Our analysis describes circumstances surrounding non-fatal overdoses and can be useful in guiding relevant, targeted prevention interventions. [Madah-Amiri D, Clausen T, Myrmel L, Brattebø G, Lobmaier P. Circumstances surrounding non-fatal opioid overdoses attended by ambulance services. Drug Alcohol Rev 2017;36:288-294].

Evaluating the impact of a national naloxone programme on ambulance attendance at overdose incidents: a controlled time-series analysis

BACKGROUND AND AIMS

It has been suggested that distributing naloxone to people who inject drugs (PWID) will lead to fewer attendances by emergency medical services at opioid-related overdose incidents if peer administration of naloxone was perceived to have resuscitated the overdose victim successfully. This study evaluated the impact of a national naloxone programme (NNP) on ambulance attendance at opioid-related overdose incidents throughout Scotland. Specifically, we aimed to answer the following research questions: is there evidence of an association between ambulance call-outs to opioid-related overdose incidents and the cumulative number of 'take-home naloxone' (THN) kits in issue; and is there evidence of an association between ambulance call-outs to opioid-related overdose incidents in early adopter (pilot) or later adopting (non-pilot) regions and the cumulative number of THN kits issued in those areas?

DESIGN

Controlled time-series analysis.

SETTING

Scotland, UK, 2008-15.

PARTICIPANTS

Pre-NNP implementation period for the evaluation was defined as 1 April 2008 to 31 March 2011 and the post-implementation period as 1 April 2011 to 31 March 2015. In total, 3721 ambulance attendances at opioid-related overdose were recorded for the pre-NNP implementation period across 158 weeks (mean 23.6 attendances per week) and 5258 attendances across 212 weeks in the post-implementation period (mean 24.8 attendances per week).

INTERVENTION

Scotland's NNP; formally implemented on 1 April 2011.

MEASUREMENTS

Primary outcome measure was weekly incidence (counts) of call-outs to opioid-related overdoses at national and regional Health Board level. Data were acquired from the Scottish Ambulance Service (SAS). Models were adjusted for opioid replacement therapy using data acquired from the Information Services Division on monthly sums of all dispensed methadone and buprenorphine in the study period. Models were adjusted further for a control group: weekly incidence (counts) of call-outs to heroin-related overdose in the London Borough area acquired from the London Ambulance Service.

FINDINGS

There was no significant association between SAS call-outs to opioid-related overdose incidents and THN kits in issue for Scotland as a whole (coefficient 0.009, 95% confidence intervals = -0.01, 0.03, P = 0.39). In addition, the magnitude of association between THN kits and SAS call-outs did not differ significantly between pilot and non-pilot regions (interaction test, P = 0.62).

CONCLUSIONS

The supply of take-home naloxone kits through a National Naloxone Programme in Scotland was not associated clearly with a decrease in ambulance attendance at opioid-related overdose incidents in the 4-year period after it was implemented in April 2011.

Use of Naloxone by Emergency Medical Services during Opioid Drug Overdose Resuscitation Efforts

Naloxone administration is an important component of resuscitation attempts by emergency medical services (EMS) for opioid drug overdoses. However, EMS providers must first recognize the possibility of opioid overdose in clinical encounters. As part of a public health response to an outbreak of opioid overdoses in Rhode Island, we examined missed opportunities for naloxone administration and factors potentially influencing EMS providers' decision to administer naloxone. We reviewed medical examiner files on all individuals who died of an opioid-related drug overdose in Rhode Island from January 1, 2012 through March 31, 2014, underwent attempted resuscitation by EMS providers, and had records available to assess for naloxone administration. We evaluated whether these individuals received naloxone as part of their resuscitation efforts and compared patient and scene characteristics of those who received naloxone to those who did not receive naloxone via chi-square, t-test, and logistic regression analyses. One hundred and twenty-four individuals who underwent attempted EMS resuscitation died due to opioid overdose. Naloxone was administered during EMS resuscitation attempts in 82 (66.1%) of cases. Females were nearly three-fold as likely not to receive naloxone as males (OR 2.9; 95% CI 1.2-7.0; p-value 0.02). Additionally, patients without signs of potential drug abuse also had a greater than three-fold odds of not receiving naloxone (OR 3.3; 95% CI 1.2-9.2; p-value 0.02). Older individuals, particularly those over age 50, were more likely not to receive naloxone than victims younger than age 30 (OR 4.8; 95% CI 1.3-17.4; p-value 0.02). Women, older individuals, and those patients without clear signs of illicit drug abuse, were less likely to receive naloxone in EMS resuscitation attempts. Heightened clinical suspicion for opioid overdose is important given the recent increase in overdoses among patients due to prescription opioids.

Prehospital Naloxone Administration as a Public Health Surveillance Tool: A Retrospective Validation Study

BACKGROUND

Abuse or unintended overdose (OD) of opiates and heroin may result in prehospital and emergency department (ED) care. Prehospital naloxone use has been suggested as a surrogate marker of community opiate ODs. The study objective was to verify externally whether prehospital naloxone use is a surrogate marker of community opiate ODs by comparing Emergency Medical Services (EMS) naloxone administration records to an independent database of ED visits for opiate and heroin ODs in the same community.

METHODS

A retrospective chart review of prehospital and ED data from July 2009 through June 2013 was conducted. Prehospital naloxone administration data obtained from the electronic medical records (EMRs) of a large private EMS provider serving a metropolitan area were considered a surrogate marker for suspected opiate OD. Comparison data were obtained from the regional trauma/psychiatric ED that receives the majority of the OD patients. The ED maintains a de-identified database of narcotic-related visits for surveillance of narcotic use in the metropolitan area. The ED database was queried for ODs associated with opiates or heroin. Cross-correlation analysis was used to test if prehospital naloxone administration was independent of ED visits for opiate/heroin ODs.

RESULTS

Naloxone was administered during 1,812 prehospital patient encounters, and 1,294 ED visits for opiate/heroin ODs were identified. The distribution of patients in the prehospital and ED datasets did not differ by gender, but it did differ by race and age. The frequency of naloxone administration by prehospital providers varied directly with the frequency of ED visits for opiate/heroin ODs. A monthly increase of two ED visits for opiate-related ODs was associated with an increase in one prehospital naloxone administration (cross-correlation coefficient [CCF]=0.44; P=.0021). A monthly increase of 100 ED visits for heroin-related ODs was associated with an increase in 94 prehospital naloxone administrations (CCF=0.46; P=.0012).

CONCLUSIONS

Frequency of naloxone administration by EMS providers in the prehospital setting varied directly with frequency of opiate/heroin OD-related ED visits. The data correlated both for short-term frequency and longer term trends of use. However, there was a marked difference in demographic data suggesting neither data source alone should be relied upon to determine which populations are at risk within the community.

Characteristics and trends of emergency patients with drug overdose in Osaka

Aim

Drug overdose is an important issue in emergency medicine. However, studies covering overdose patients transported by ambulance have not been sufficiently carried out. We attempted to clarify problems of suspected drug overdose patients transported by ambulance.

Methods

This is a prospective population-based cohort study. Data were collected by emergency medical service crews in Osaka City, Japan, between January 1998 and December 2010.

Results

Drug overdose cases increased annually from 1,136 in 1998 to 1,822 in 2010 (P < 0.0001 for trend). In these cases, the dominant age range was between 16 and 40 years and the age distribution did not change over time. The age of non-overdose cases increased (P < 0.0001 for trend), with patients aged ≥66 years becoming most common in recent years, reflecting the aging of society. Males comprised most non-overdose patients, but the percentage of females increased annually (P < 0.0001 in trend). Females comprised approximately 70% in overdose cases annually throughout the study period. The duration from the emergency call to the arrival at the hospital for overdose patients has increased markedly in recent years. It also takes more time to obtain acceptance from hospitals to care for patients of suspected overdose.

Conclusion

The characteristics of drug overdose patients are clearly different from those of non-overdose patients. Recent trends of drug overdose patients indicate the accelerated burden on emergency medical services system.

Urban overdose hotspots: a 12-month prospective study in Dublin ambulance services

BACKGROUND

Opioid overdose (OD) is the primary cause of death among drug users globally. Personal and social determinants of overdose have been studied before, but the environmental factors lacked research attention. Area deprivation or presence of addiction clinics may contribute to overdose.

OBJECTIVES

The objective of the study is to examine the baseline incidence of all new ODs in an ambulance service and their relationship with urban deprivation and presence of addiction services.

METHODS

A prospective chart review of prehospital advanced life support patients was performed on confirmed OD calls. Demographic, geographic, and clinical information, that is, presentation, treatment, and outcomes, was collected for each call. The census data were used to calculate deprivation. Geographical information software mapped the urban deprivation and addiction services against the overdose locations.

RESULTS

There were 469 overdoses, 13 of which were fatal; most were male (80%), of a young age (32 years), with a high rate of repeated overdoses (26%) and common polydrug use (9.6%). Most occurred in daytime (275) and on the streets (212). Overdoses were more likely in more affluent areas (r = .15; P < .05) and in a 1000-m radius of addiction services. Residential overdoses were in more deprived areas than street overdoses (mean difference, 7.8; t170 = 3.99; P < .001). Street overdoses were more common in the city center than suburbs (χ(2)(1) = 33.04; P < .001).

CONCLUSIONS

The identified clusters of increased incidence-urban overdose hotspots-suggest a link between environment characteristics and overdoses. This highlights a need to establish overdose education and naloxone distribution in the overdose hotspots.

EMS runs for suspected opioid overdose: implications for surveillance and prevention

BACKGROUND

Opioid (including prescription opiate) abuse and overdose rates in the United States have surged in the past decade. The dearth and limitations of opioid abuse and overdose surveillance systems impede the development of interventions to address this epidemic. Objective. We explored evidence to support the validity of emergency medical services (EMS) data on naloxone administration as a possible proxy for estimating incidence of opioid overdose.

METHODS

We reviewed data from Baltimore City Fire Department EMS patient records matched with dispatch records over a 13-month time period (2008-2009) based on 2008 Census data. We calculated incidence rates and patient demographic and temporal patterns of naloxone administration, and examined patient evaluation data associated with naloxone administration. Results were compared with the demographic distributions of the EMS patient and city populations and with prior study findings.

RESULTS

Of 116,910 EMS incidents during the study period for patients aged 15 years and older, EMS providers administered naloxone 1,297 times (1.1% of incidents), an average of 100 administrations per month. The overall incidence was 1.87 administrations per 1,000 residents per year. Findings indicated that naloxone administration peaked in the summer months (31% of administrations), on weekends (32%), and in the late afternoon (4:00-5:00 pm [8%]); and there was a trend toward peaking in the first week of the month. The incidence of suspected opioid overdose was highest among male patients, white patients, and those in the 45-54-year age group. Findings on temporal patterns were comparable with findings from prior studies. Demographic patterns of suspected opioid overdose were similar to medical examiner reports of demographic patterns of fatal drug- or alcohol-related overdoses in Baltimore in 2008-2009 (88% of which involved opioids). The findings on patient evaluation data suggest some inconsistencies with previously recommended clinical indications of opioid overdose.

CONCLUSIONS

While our findings suggest limitations of EMS naloxone administration data as a proxy indicator of opioid overdose, the results provide partial support for using these data for estimating opioid overdose incidence and suggest ways to improve such data. The study findings have implications for an EMS role in conducting real-time surveillance and treatment and prevention of opioid abuse and overdose.

Ambulance demand: random events or predicable patterns?

BACKGROUND

Occupational, social and recreational routines follow temporal patterns, as does the onset of certain acute medical diseases and injuries. It is not known if the temporal nature of injury and disease transfers into patterns that can be observed in ambulance demand. This review examines eligible study findings that reported temporal (time of day, day of week and seasonal) patterns in ambulance demand.

METHODS

Electronic searches of Medline and Cumulative Index of Nursing and Allied Health Literature were conducted for papers published between 1980 and 2011. In addition, hand searching was conducted for unpublished government and ambulance service documents and reports for the same period.

RESULTS

38 studies examined temporal patterns in ambulance demand. Six studies reported trends in overall workload and 32 studies reported trends in a subset of ambulance demand, either as a specific case type or demographic group. Temporal patterns in overall demand were consistent between jurisdictions for time of day but varied for day of week and season. When analysed by case type, all jurisdictions reported similar time of day patterns, most jurisdictions had similar day of week patterns except for out-of-hospital cardiac arrest and similar seasonal patterns, except for trauma. Temporal patterns in case types were influenced by age and gender.

CONCLUSIONS

Temporal patterns are present in ambulance demand and importantly these populations are distinct from those found in hospital datasets suggesting that variation in ambulance demand should not be inferred from hospital data alone. Case types seem to have similar temporal patterns across jurisdictions; thus, research where demand is broken down into case types would be generalisable to many ambulance services. This type of research can lead to improvements in ambulance service deliverables.

Use of geographic information systems to determine new helipad locations and improve timely response while mitigating risk of helicopter emergency medical services operations

INTRODUCTION

Traumatic injury is a leading cause of morbidity and mortality, but these can be minimized by timely transport to definite care. Helicopter emergency medical services (HEMS) provide timely transport and can influence survival. However, accident analyses indicate that landing at an unsecured landing zone (LZ), particularly at night, increases the risk of aviation accidents. To ensure safety, some HEMS operations land only at designated, secured LZs.

OBJECTIVE

This study utilized geographic information systems (GISs) to compare locations of scene call requests and secure LZs. The goal was to determine the optimal placement of new helipads as a strategy to improve access while mitigating the risk of aviation accidents.

METHODS

Call request data from a large air medical transport service were used to determine the geographic locations of all requests for scene responses in 2006. Request locations were compared with the locations of existing helipads, and straight-line distances between scene and helipad were determined using the GIS application. The application was then used to determine potential locations for new helipads.

RESULTS

During the study period, 748 requests for scene calls and 269 helipads were available. There were 476 (52.4%) requests at least 10 kilometers from a helipad and 356 (36.6%) requests at least 15 kilometers from a helipad. One particular region, Southwestern Ontario, was identified as having the highest number of requests >15 kilometers from the closest helipad.

CONCLUSION

GISs can be used to determine potential locations for new helipad construction using historical call request data. This evidence-based approach can improve HEMS access while mitigating operational risk.

Endogenous opiates and behavior: 2006

This paper is the 29th consecutive installment of the annual review of research concerning the endogenous opioid system, now spanning 30 years of research. It summarizes papers published during 2006 that studied the behavioral effects of molecular, pharmacological and genetic manipulation of opioid peptides, opioid receptors, opioid agonists and opioid antagonists. The particular topics that continue to be covered include the molecular-biochemical effects and neurochemical localization studies of endogenous opioids and their receptors related to behavior (Section 2), and the roles of these opioid peptides and receptors in pain and analgesia (Section 3); stress and social status (Section 4); tolerance and dependence (Section 5); learning and memory (Section 6); eating and drinking (Section 7); alcohol and drugs of abuse (Section 8); sexual activity and hormones, pregnancy, development and endocrinology (Section 9); mental illness and mood (Section 10); seizures and neurological disorders (Section 11); electrical-related activity and neurophysiology (Section 12); general activity and locomotion (Section 13); gastrointestinal, renal and hepatic functions (Section 14); cardiovascular responses (Section 15); respiration and thermoregulation (Section 16); and immunological responses (Section 17).