One year mortality of patients treated with naloxone for opioid overdose by emergency medical services

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.

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Characterizing Opioid Overdoses Using Emergency Medical Services Data

Public Health Reports ◽

10.1177/00333549211026802 ◽

2021 ◽

Vol 136 (1_suppl) ◽

pp. 62S-71S

Author(s):

Josie J. Sivaraman ◽

Scott K. Proescholdbell ◽

David Ezzell ◽

Meghan E. Shanahan

Keyword(s):

Machine Learning ◽

North Carolina ◽

Emergency Medical Services ◽

Expert Knowledge ◽

Case Definition ◽

Medical Services ◽

Opioid Overdose ◽

Machine Learning Classification ◽

Emergency Medical ◽

Definition Of

Objectives Tracking nonfatal overdoses in the escalating opioid overdose epidemic is important but challenging. The objective of this study was to create an innovative case definition of opioid overdose in North Carolina emergency medical services (EMS) data, with flexible methodology for application to other states’ data. Methods This study used de-identified North Carolina EMS encounter data from 2010-2015 for patients aged >12 years to develop a case definition of opioid overdose using an expert knowledge, rule-based algorithm reflecting whether key variables identified drug use/poisoning or overdose or whether the patient received naloxone. We text mined EMS narratives and applied a machine-learning classification tree model to the text to predict cases of opioid overdose. We trained models on the basis of whether the chief concern identified opioid overdose. Results Using a random sample from the data, we found the positive predictive value of this case definition to be 90.0%, as compared with 82.7% using a previously published case definition. Using our case definition, the number of unresponsive opioid overdoses increased from 3412 in 2010 to 7194 in 2015. The corresponding monthly rate increased by a factor of 1.7 from January 2010 (3.0 per 1000 encounters; n = 261 encounters) to December 2015 (5.1 per 1000 encounters; n = 622 encounters). Among EMS responses for unresponsive opioid overdose, the prevalence of naloxone use was 83%. Conclusions This study demonstrates the potential for using machine learning in combination with a more traditional substantive knowledge algorithm-based approach to create a case definition for opioid overdose in EMS data.

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Management of Suspected Opioid Overdose With Naloxone by Emergency Medical Services Personnel

10.23970/ahrqepccer193 ◽

2017 ◽

Cited By ~ 1

Author(s):

Roger Chou ◽

P. Todd Korthuis ◽

Dennis McCarty ◽

Phillip Coffin ◽

Jessica Griffin ◽

...

Keyword(s):

Emergency Medical Services ◽

Medical Services ◽

Opioid Overdose ◽

Emergency Medical ◽

Emergency Medical Services Personnel

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P016: Evaluating the impact of a novel mobile care team (MCT) on the prevalence of ambulatory care sensitive conditions presenting to emergency medical services in Nova Scotia

CJEM ◽

10.1017/cem.2016.192 ◽

2016 ◽

Vol 18 (S1) ◽

pp. S83-S83 ◽

Cited By ~ 1

Author(s):

D.R. Brown ◽

A. Carter ◽

J. Goldstein ◽

J. Jensen ◽

A. Travers ◽

...

Keyword(s):

Primary Care ◽

Ambulatory Care ◽

Emergency Medical Services ◽

Care Provider ◽

Primary Care Provider ◽

Care Team ◽

Medical Services ◽

Ambulatory Care Sensitive Conditions ◽

Emergency Medical ◽

One Year

Introduction: Hospitalization due to ambulatory care sensitive conditions (ACSC) is a proxy measure for access to primary care. Emergency medical services (EMS) are increasingly called when primary care cannot be accessed. A novel paramedic-nurse EMS Mobile Care Team (MCT) was implemented in an under-serviced community. The MCT responds in a non-transport unit to bookings from EMS, emergency and primary care and to low-acuity 911 calls in a defined geographic region. Our objective was to compare the prevalence of ACSC in ground ambulance (GA) responses before and after the introduction of the MCT. Methods: A cross-sectional analysis of GA and MCT patients with ACSC (determined by chief complaint, clinical impression, treatment protocol and medical history) one year pre- and one year post-MCT implementation was conducted for the period Oct. 1, 2012 to Sept. 30, 2014. Demographics were described. Predictors of ACSC were identified via logistic regression. Prevalence was compared with chi-squared analysis. Results: There were 975 calls pre- and 1208 GA/95 MCT calls post-MCT. ACSC in GA patients pre- and post-MCT was similar: n=122, 12.5% vs. n=185, 15.3%; p=0.06. ACSC in patients seen by EMS (GA plus MCT) increased in the post-period: 122 (12.5%) vs. 204 (15.7%) p=0.04. Pre vs post, GA calls differed by sex (p=0.007) but not age (65.38 ± 15.12 vs. 62.51 ± 20.48; p=0.16). Post-MCT, prevalence of specific ACSC increased for GA: hypertension (p<0.001) and congestive heart failure (p=0.04). MCT patients with ACSC were less likely to have a primary care provider compared to GA (90.2% and 87.6% vs. 63.2%; p=0.003, p=0.004). Conclusion: The prevalence of ACSC did not decrease for GA with the introduction of the MCT, but ACSC in the overall patient population served by EMS increased. It is possible more patients with ACSC call or are referred to EMS for the new MCT service. Given that MCT patients were less likely to have a primary care provider this may represent an increase in access to care, or a shift away from other emergency/episodic care. These associations must be further studied to inform the ideal utility of adding such services to EMS and healthcare systems.

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Using Emergency Medical Services Data to Monitor Nonfatal Opioid Overdoses in Real Time

Public Health Reports ◽

10.1177/00333549211018989 ◽

2021 ◽

Vol 136 (1_suppl) ◽

pp. 40S-46S

Author(s):

Benjamin D. Hallowell ◽

Laura C. Chambers ◽

Jason Rhodes ◽

Melissa Basta ◽

Samara Viner-Brown ◽

...

Keyword(s):

Public Health ◽

Emergency Medical Services ◽

Real Time ◽

Rhode Island ◽

Keyword Search ◽

Case Definition ◽

Outbreak Detection ◽

Medical Services ◽

Opioid Overdose ◽

Emergency Medical

Objective No case definition exists that allows public health authorities to accurately identify opioid overdoses using emergency medical services (EMS) data. We developed and evaluated a case definition for suspected nonfatal opioid overdoses in EMS data. Methods To identify suspected opioid overdose–related EMS runs, in 2019 the Rhode Island Department of Health (RIDOH) developed a case definition using the primary impression, secondary impression, selection of naloxone in the dropdown field for medication given, indication of medication response in a dropdown field, and keyword search of the report narrative. We developed the case definition with input from EMS personnel and validated it using an iterative process of random medical record review. We used naloxone administration in consideration with other factors to avoid misclassification of opioid overdoses. Results In 2018, naloxone was administered during 2513 EMS runs in Rhode Island, of which 1501 met our case definition of a nonfatal opioid overdose. Based on a review of 400 randomly selected EMS runs in which naloxone was administered, the RIDOH case definition accurately identified 90.0% of opioid overdoses and accurately excluded 83.3% of non–opioid overdose–related EMS runs. Use of the case definition enabled analyses that identified key patterns in overdose locations, people who experienced repeat overdoses, and the creation of hotspot maps to inform outbreak detection and response. Practice Implications EMS data can be an effective tool for monitoring overdoses in real time and informing public health practice. To accurately identify opioid overdose–related EMS runs, the use of a comprehensive case definition is essential.

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Abstract 5: Prevalence, Characteristics, and Accuracy of Stroke Diagnosis for Scene Transports to a Comprehensive Stroke Center by Helicopter Emergency Medical Services: A One Year Retrospective Evaluation

Air Medical Journal ◽

10.1016/j.amj.2019.05.006 ◽

2019 ◽

Vol 38 (4) ◽

pp. 260

Author(s):

Ekta Panjrolia ◽

Anne Jackson ◽

Stacie Stevens ◽

Lorie Selleck ◽

V. Ramana Feeser ◽

...

Keyword(s):

Emergency Medical Services ◽

Medical Services ◽

Retrospective Evaluation ◽

Helicopter Emergency Medical Services ◽

Emergency Medical ◽

Stroke Diagnosis ◽

Comprehensive Stroke Center ◽

Stroke Center ◽

One Year

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Psychological Resilience towards COVID-19 amongst Emergency Medical Professionals in Pune (India)

Journal of Pharmaceutical Research International ◽

10.9734/jpri/2021/v33i42a32379 ◽

2021 ◽

pp. 17-24

Author(s):

Parag Rishipathak ◽

Shrimathy Vijayraghavan ◽

Anand Hinduja

Keyword(s):

Emergency Medical Services ◽

Well Being ◽

Medical Services ◽

Medical Professionals ◽

Psychological Resilience ◽

Breaking Bad ◽

Stressful Environment ◽

Emergency Medical ◽

Work Routine ◽

One Year

Aim: The surge of COVID 19 infection across the globe has put tremendous pressure on Healthcare Professionals worldwide. Emergency Medical Professionals are first responders and hence bear the brunt of exposure to the virus as well as dealing with critically ill patients. The aim of the study is to assess psychological resilience towards COVID 19 amongst Emergency Medical Professionals. Study Design: Descriptive Study. Place and Duration of Study: Symbiosis Centre for Health Skills, Pune in April 2021. Methodology: The study was conducted amongst 120 Emergency Medical Professionals in Pune, India. The data was collected during the month of April 2021. Professionals who have completed Post Graduate Diploma in Emergency Medical Services and working in COVID centres for at least one year were included in the study. A 38-item questionnaire was developed for frontline Emergency Medical Professionals and included questions adapted from the tools which are available in public domain. Results and Discussion: Working in a stressful environment along with continuous fear of self-exposure and risk of transmission to family members affects the efficacy and productivity of Emergency Medical Services Professionals. Debriefing, training for effective ‘breaking bad news’ stress management workshops and counselling sessions should be integrated into their work routine to enhance their psychological capacity. Conclusion: The findings indicate that even after a year of serving COVID 19 patients, Emergency Medical Professionals demonstrate a high degree of resilience. Yet there are areas requiring improvement which need to be focussed upon immediately in the interest of the mental well-being of Emergency Medical Professionals.

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Emergency Medical Services and Syndromic Surveillance: A Comparison With Traditional Surveillance and Effects on Timeliness

Public Health Reports ◽

10.1177/00333549211018673 ◽

2021 ◽

Vol 136 (1_suppl) ◽

pp. 72S-79S

Author(s):

Peter J. Rock ◽

Dana Quesinberry ◽

Michael D. Singleton ◽

Svetla Slavova

Keyword(s):

Public Health ◽

Time Series ◽

Emergency Medical Services ◽

Syndromic Surveillance ◽

Surveillance Data ◽

Medical Services ◽

Opioid Overdose ◽

Billing Data ◽

Public Health Response ◽

Emergency Medical

Objective Traditional public health surveillance of nonfatal opioid overdose relies on emergency department (ED) billing data, which can be delayed substantially. We compared the timeliness of 2 new data sources for rapid drug overdose surveillance—emergency medical services (EMS) and syndromic surveillance—with ED billing data. Methods We used data on nonfatal opioid overdoses in Kentucky captured in EMS, syndromic surveillance, and ED billing systems during 2018-2019. We evaluated the time-series relationships between EMS and ED billing data and syndromic surveillance and ED billing data by calculating cross-correlation functions, controlling for influences of autocorrelations. A case example demonstrates the usefulness of EMS and syndromic surveillance data to monitor rapid changes in opioid overdose encounters in Kentucky during the COVID-19 epidemic. Results EMS and syndromic surveillance data showed moderate-to-strong correlation with ED billing data on a lag of 0 ( r = 0.694; 95% CI, 0.579-0.782; t = 9.73; df = 101; P < .001; and r = 0.656; 95% CI, 0.530-0.754; t = 8.73; df = 101; P < .001; respectively) at the week-aggregated level. After the COVID-19 emergency declaration, EMS and syndromic surveillance time series had steep increases in April and May 2020, followed by declines from June through September 2020. The ED billing data were available for analysis 3 months after the end of a calendar quarter but closely followed the trends identified by the EMS and syndromic surveillance data. Conclusion Data from EMS and syndromic surveillance systems can be reliably used to monitor nonfatal opioid overdose trends in Kentucky in near–real time to inform timely public health response.

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