Trial to End Ambulance Diversion in Boston: Report from the Conference of the Boston Teaching Hospitals Consortium

AbstractIntroduction: Annual ambulance diversion hours in Boston increased more than six-fold from 1997 to 2006. Although interventions and best practices were implemented, there was no reduction in the number of diversion hours.Objectives: A consortium of Boston teaching hospitals instituted a two-week moratorium on citywide diversion from 02 October 2006 to 15 October 2006. The hypothesis was that there would be no significant difference in measures of hospital and emergency medical services (EMS) efficiency compared with the two weeks immediately prior.Methods: A total of nine hospitals and the municipal emergency medical services in Boston submitted data for analysis. The following mean daily hospital measures were studied: (1) emergency department volume; (2) number of emergency department admissions; (3) length of stay (LOS) for all patients; and (4) number of elopements. Mean EMS at-hospital time by destination and the percent of all Boston EMS transports to each hospital destination were calculated. The median differences (MD) were calculated as “before” minus “during” the study period and were compared with paired, Wilcoxon, non-parametric tests. Additional mean EMS measures for all destinations included: (1) to hospital time; (2) number of responses with transport initiated per day; (3) incident entry to arrival; and (4) at-hospital time.Results: The LOS for admitted patients (MD = 0.30 hours; IQR 0.10,1.30; p = 0.03) and number of daily admissions (MD = -1.50 patients; IQR -1.50, -0.10; p = 0.04) were significantly different statistically. The results for LOS for all patients, LOS for discharged patients, ED volume, EMS time at hospital by destination, number of elopements, and percent of Boston EMS transports to each hospital revealed no statistically significant differences. The difference between the study and control periods for mean EMS to hospital time, at-hospital time, and incident entry to arrival was a maximum of 0.6 minutes. The vast majority of EMS respondents to an online survey believed that the “no diversion” policy should be made routine practice.Conclusions: The LOS for admitted patients decreased by 18 minutes, and the number of admissions increased by 1.5 patients per day during the study period. The “no diversion” policy resulted in minimal changes in EMS efficiency and operations. Diversion was temporarily eliminated in a major city without significant detrimental changes in ED, hospital, or EMS efficiency.

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EMS Heroin Overdoses with Refusal to Transport & Impacts on ED Overdose Surveillance

Online Journal of Public Health Informatics ◽

10.5210/ojphi.v11i1.9917 ◽

2019 ◽

Vol 11 (1) ◽

Cited By ~ 1

Author(s):

Peter Rock ◽

Michael Singleton

Keyword(s):

Emergency Department ◽

Emergency Medical Services ◽

Syndromic Surveillance ◽

Emergency Department Visits ◽

Medical Services ◽

Opioid Overdose ◽

Billing Data ◽

Heroin Overdose ◽

Emergency Medical ◽

Significant Difference

ObjectiveThe aim of this project was to explore changing patterns in patient refusal to transport by emergency medical services for classified heroin overdoses and possible implications on heroin overdose surveillance in Kentucky.IntroductionAs a Centers for Disease Control and Prevention Enhanced State Opioid Overdose Surveillance (ESOOS) funded state, Kentucky started utilizing Emergency Medical Services (EMS) data to increase timeliness of state data on drug overdose events in late 2016. Using developed definitions of heroin overdose for EMS emergency runs, Kentucky analyzed the patterns of refused/transported EMS runs for both statewide and local jurisdictions. Changes in EMS transportation patterns of heroin overdoses can have a dramatic impact on other surveillance systems, such as emergency department (ED) claims data or syndromic surveillance (SyS) data.MethodsAs part of the ESOOS grant, Kentucky receives all emergency-only EMS runs monthly from Kentucky Board for Emergency Medical Services, Kentucky State Ambulance Reporting System data. Heroin cases were classified based on text and medications (Narcan) administered, with comparisons to historic data discussed elsewhere (Rock & Singleton, 2018). Transportation classifications are based on EMS standard elements defining treatment with transportation vs refusal to transport to hospital and canceled runs were excluded. Initial analysis included trend analysis at state and local levels, as well as demographic comparisons of refusal vs transported heroin overdose encounters.ResultsStatewide trends in EMS heroin overdoses with refusal transport significantly increased from 5% (n=42) in 2016 quarter three to 22% (n=290) in 2018 quarter two (Fig 1). Initial demographic analysis does not show any significant difference between refusals/transported for age, gender, or race. However, there are significant differences among geographic regions in Kentucky with heroin encounter refusal proportion ranging from 3%-48% in 2018 quarter two. Specifically, one urban area (Fig 2) shows the change in proportion of refusal increasing from 15% (n=23) in 2016 quarter three to 47% (n=110) in 2018 quarter two. In this geographic area, combined refused/transported EMS heroin overdoses compared to traditional ED data demonstrates opposing heroin overdose patterns for the same local with EMS showing and increasing trend overtime and ED showing a decreasing trend (Fig 3).ConclusionsTraditional public health surveillance for heroin overdose has historically relied on ED billing data, though agencies are starting to use syndromic surveillance, too (Vivolo-Kantor et al., 2016). These systems share similar underlying ED data, albeit with different components, quality, and limitations. However, in terms of the overdose epidemic, both are limited to only heroin overdoses that result in ED hospital encounters. The recent drastic increase in refused transport can have significant impacts on heroin surveillance. Jurisdictions relying on SyS or ED data for monitoring overdose patterns and/or evaluating interventions may be significantly underestimating acute overdose occurrence in the population. This analysis highlights the importance of this preclinical data source in surveillance of the heroin epidemic.ReferencesRock, P. J., & Singleton, M. D. (2018). Assessing Definitions of Heroin Overdose in ED & EMS Data Using Hospital Billing Data, 10(1), 2579.Vivolo-Kantor, A. M., Seth, P., Gladden, ; R Matthew, Mattson, C. L., Baldwin, G. T., Kite-Powell, A., & Coletta, M. A. (2016). Morbidity and Mortality Weekly Report Vital Signs: Trends in Emergency Department Visits for Suspected Opioid Overdoses — United States, 67(9), 279–285. Retrieved from https://www.cdc.gov/mmwr/volumes/67/wr/pdfs/mm6709e1-H.pdf

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Characteristics of Prehospital Electrocardiogram Use in North Carolina Using a Novel Linkage of Emergency Medical Services and Emergency Department Data

Prehospital Emergency Care ◽

10.1080/10903127.2019.1597230 ◽

2019 ◽

Vol 23 (6) ◽

pp. 772-779 ◽

Cited By ~ 1

Author(s):

Jessica K. Zègre-Hemsey ◽

Josephine Asafu-Adjei ◽

Antonio Fernandez ◽

Jane Brice

Keyword(s):

Emergency Department ◽

North Carolina ◽

Emergency Medical Services ◽

Medical Services ◽

Emergency Department Data ◽

Emergency Medical

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Feedback to Emergency Medical Services Providers: The Good, the Bad, and the Ignored

Prehospital and Disaster Medicine ◽

10.1017/s1049023x00037444 ◽

1997 ◽

Vol 12 (2) ◽

pp. 74-77 ◽

Cited By ~ 3

Author(s):

Elisabeth F. Mock ◽

Keith D. Wrenn ◽

Seth W. Wright ◽

T. Chadwick Eustis ◽

Corey M. Slovis

Keyword(s):

Emergency Department ◽

Emergency Medical Services ◽

Emergency Medical Service ◽

Medical Service ◽

Service Providers ◽

Medical Services ◽

Emergency Medical Service System ◽

Constructive Feedback ◽

Emergency Medical ◽

Emergency Medical Service Provider

AbstractHypothesis:To determine the type and frequency of immediate unsolicited feedback received by emergency medical service (EMS) providers from patients or their family members and emergency department (ED) personnel.Methods:Prospective, observational study of 69 emergency medical services providers in an urban emergency medical service system and 12 metropolitan emergency departments. Feedback was rated by two medical student observers using a prospectively devised original scale.Results:In 295 encounters with patients or family, feedback was rated as follows: 1) none in 224 (76%); 2) positive in 51 (17%); 3) negative in 19 (6%); and 4) mixed in one (<1%). Feedback from 254 encounters with emergency department personnel was rated as: 1) none in 185 (73%); 2) positive in 46 (18%); 3) negative in 21 (8%); and 4) mixed in 2 (1%). Patients who had consumed alcohol were more likely to give negative feedback than were patients who had not consumed alcohol. Feedback from emergency department personnel occurred more often when the emergency medical service provider considered the patient to be critically ill.Conclusion:The two groups provided feedback to emergency medical service providers in approximately one quarter of the calls. When feedback was provided, it was positive more than twice as often as it was negative. Emergency physicians should give regular and constructive feedback to emergency medical services providers more often than currently is the case.

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

Public Health Reports ◽

10.1177/00333549211012400 ◽

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.

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Abstract WP261: Non-English-preferring Patients Have No Differences in Stroke Symptom Recognition or Emergency Care Time Metrics

Stroke ◽

10.1161/str.48.suppl_1.wp261 ◽

2017 ◽

Vol 48 (suppl_1) ◽

Author(s):

Shaw Natsui ◽

Khawja A Siddiqui ◽

Betty L Erfe ◽

Nicte I Mejia ◽

Lee H Schwamm ◽

...

Keyword(s):

Emergency Medical Services ◽

Emergency Care ◽

Medical Services ◽

Similar Response ◽

Language Preference ◽

Emergency Department Care ◽

Hospital Arrival ◽

Stroke Symptom ◽

Emergency Medical ◽

Significant Difference

Introduction: The influence of patients’ language preference on the delivery of acute ischemic stroke (AIS) care in the pre-hospital and in-hospital emergency care settings is scarcely known. We hypothesize that stroke knowledge differences may be associated with non-English preferring (NEP) patients having slower time from symptom discovery to hospital presentation and less engagement of emergency medical services (EMS) than English preferring (EP) patients. Language barriers may also interfere with the delivery of time-sensitive emergency department care. Objectives: To identify whether language preference is associated with differences in patients’ time from stroke symptom discovery to hospital arrival, activation of emergency medical services, door-to-imaging time (DIT), and door-to-needle (DTN) time. Methods: We identified consecutive AIS patients presenting to a single urban, tertiary, academic center between 01/2003-04/2014. Data was abstracted from the institution’s Research Patient Data Registry and Get with the Guidelines-Stroke Registry. Bivariate and regression models evaluated the relationship between language preference and: 1) time from symptom onset to hospital arrival, 2) use of EMS, 3) DIT, and 4) DTN time. Results: Of 3,190 AIS patients who met inclusion/exclusion criteria, 9.4% were NEP (n=300). Time from symptom discovery to arrival, and EMS utilization were not significantly different between NEP and EP patients in unadjusted or adjusted analyses (overall median time 157 minutes, IQR 55-420; EMS utilization: 65% vs. 61.3% p=0.21). There was no significant difference between NEP and EP patients in DIT or in likelihood of DIT ≤ 25 minutes in unadjusted or adjusted analyses (overall median 59 minutes, IQR 29-127; DIT ≤ 25 minutes 24.3% vs. 21.3% p=0.29). There was also no significant different in DTN time or in likelihood of DTN ≤ 60 minutes in unadjusted or adjusted analyses (overall median 53 minutes, IQR 36-73; DTN ≤ 60 minutes 62.5% vs. 58.2% p=0.60). Conclusion: Non-English-preferring patients have similar response to stroke symptoms as reflected by EMS utilization and time from symptom discovery to hospital arrival. Similarly, NEP patients have no differences in in-hospital AIS care metrics of DIT and DTN time.

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