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1.
J Am Coll Emerg Physicians Open ; 4(1): e12904, 2023 Feb.
Artículo en Inglés | MEDLINE | ID: covidwho-2253000

RESUMEN

Introduction: Exposure to patient death places healthcare workers at increased risk for burnout and traumatic stress, yet limited data exist exploring exposure to death among emergency medical services (EMS) clinicians. Our objective was to describe changes in EMS encounters involving on-scene death from 2018 to 2021. Methods: We retrospectively analyzed deidentified EMS records for 9-1-1 responses from the ESO Data Collaborative from 2018 to 2021. We identified cases where patient dispositions of death on scene, with or without attempted resuscitation, and without EMS transport. A non-parametric test of trend was used to assess for monotonic increase in agency-level encounters involving on-scene death and the proportion of EMS clinicians exposed to ≥1 on-scene death. Results: We analyzed records from 1109 EMS agencies. These agencies responded to 4,286,976 calls in 2018, 5,097,920 calls in 2019, 4,939,651 calls in 2020, and 5,347,340 calls in 2021.The total number of encounters with death on scene rose from 49,802 in 2018 to 60,542 in 2019 to 76,535 in 2020 and 80,388 in 2021. Agency-level annual counts of encounters involving death on scene rose from a median of 14 (interquartile range [IQR], 4-40) in 2018 to 2023 (IQR, 6-63) in 2021 (P-trend < 0.001). In 2018, 56% of EMS clinicians responded to a call with death on scene, and this number rose to 63% of EMS clinicians in 2021 (P-trend < 0.001). Conclusion: From 2018 to 2021, EMS clinicians were increasingly exposed to death. This trend may be driven by COVID-19 and its effects on the healthcare system and reinforces the need for evidence-based death notification training to support EMS clinicians.

2.
J Am Coll Emerg Physicians Open ; 2(4): e12483, 2021 Aug.
Artículo en Inglés | MEDLINE | ID: covidwho-1287347

RESUMEN

OBJECTIVE: The Rapid Emergency Medicine Score (REMS) has not been widely studied for use in predicting outcomes of COVID-19 patients encountered in the prehospital setting. This study aimed to determine whether the first prehospital REMS could predict emergency department and hospital dispositions for COVID-19 patients transported by emergency medical services. METHODS: This retrospective study used linked prehospital and hospital records from the ESO Data Collaborative for all 911-initiated transports of patients with hospital COVID-19 diagnoses from July 1 to December 31, 2020. We calculated REMS with the first recorded prehospital values for each component. We calculated area under the receiver operating curve (AUROC) for emergency department (ED) mortality, ED discharge, hospital mortality, and hospital length of stay (LOS). We determined optimal REMS cut-points using test characteristic curves. RESULTS: Among 13,830 included COVID-19 patients, median REMS was 6 (interquartile range [IQR]: 5-9). ED mortality was <1% (n = 80). REMS ≥9 predicted ED death (AUROC 0.79). One-quarter of patients (n = 3,419) were discharged from the ED with an optimal REMS cut-point of ≤5 (AUROC 0.72). Eighteen percent (n = 1,742) of admitted patients died. REMS ≥8 optimally predicted hospital mortality (AUROC 0.72). Median hospital LOS was 8.3 days (IQR: 4.1-14.8 days). REMS ≥7 predicted hospitalizations ≥3 days (AUROC 0.62). CONCLUSION: Initial prehospital REMS was modestly predictive of ED and hospital dispositions for patients with COVID-19. Prediction was stronger for outcomes more proximate to the first set of emergency medical services (EMS) vital signs. These findings highlight the potential value of first prehospital REMS for risk stratification of individual patients and system surveillance for resource planning related to COVID-19.

3.
EClinicalMedicine ; 34: 100815, 2021 Apr.
Artículo en Inglés | MEDLINE | ID: covidwho-1171237

RESUMEN

BACKGROUND: Though variable, many major metropolitan cities reported profound and unprecedented increases in out-of-hospital cardiac arrest (OHCA) in early 2020. This study examined the relative magnitude of those increases and their relationship to COVID-19 prevalence. METHODS: EMS (9-1-1 system) medical directors for 50 of the largest U.S. cities agreed to provide the aggregate, de-identified, pre-existing monthly tallies of OHCA among adults (age >18 years) occurring between January and June 2020 within their respective jurisdictions. Identical comparison data were also provided for corresponding time periods in 2018 and 2019.  Equivalent data were obtained from the largest cities in Italy, United Kingdom and France, as well as Perth, Australia and Auckland, New Zealand. FINDINGS: Significant OHCA escalations generally paralleled local prevalence of COVID-19. During April, most U.S. cities (34/50) had >20% increases in OHCA versus 2018-2019 which reflected high local COVID-19 prevalence. Thirteen observed 1·5-fold increases in OHCA and three COVID-19 epicenters had >100% increases (2·5-fold in New York City). Conversely, cities with lesser COVID-19 impact observed unchanged (or even diminished) OHCA numbers. Altogether (n = 50), on average, OHCA cases/city rose 59% during April (p = 0·03). By June, however, after mitigating COVID-19 spread, cities with the highest OHCA escalations returned to (or approached) pre-COVID OHCA numbers while cities minimally affected by COVID-19 during April (and not experiencing OHCA increases), then had marked OHCA escalations when COVID-19 began to surge locally. European, Australian, and New Zealand cities mirrored the U.S. experience. INTERPRETATION: Most metropolitan cities experienced profound escalations of OHCA generally paralleling local prevalence of COVID-19.  Most of these patients were pronounced dead without COVID-19 testing. FUNDING: No funding was involved. Cities provided de-identified aggregate data collected routinely for standard quality assurance functions.

4.
Prehosp Emerg Care ; 25(1): 16-27, 2021.
Artículo en Inglés | MEDLINE | ID: covidwho-651431

RESUMEN

BACKGROUND: Few studies have examined the prehospital presentation, assessment, or treatment of patients diagnosed with coronavirus disease 2019 (COVID-19). The objective of this preliminary report is to describe prehospital encounters for patients with a COVID-19 hospital diagnosis and/or COVID-19 EMS suspicion versus those with neither a hospital diagnosis nor EMS suspicion of the disease. METHODS: This case series evaluated electronic patient care records from EMS agencies participating in a large national bi-directional data exchange. All records for 9-1-1 responses between March 1 and April 19, 2020, resulting in transport to a hospital, with at least one ICD-10 outcome returned via the data exchange were included. Hospital ICD-10 codes used to determine COVID-19 diagnoses included B97.2, B97.21, B97.29, B34.2, and U07.1. COVID-19 EMS suspicion was defined as a documented EMS primary or secondary impression of COVID-19, or indication of COVID-19 suspicion in the prehospital free-text narrative. Comparisons were stratified by COVID-19 hospital diagnosis and COVID-19 EMS suspicion. Descriptive and comparative statistics are presented. RESULTS: There were 84,540 EMS patient records with linked hospital ICD-10 codes included. Of those, 814 (1%) patients had a COVID-19 hospital diagnosis. Overall, COVID-19 EMS suspicion was documented for 3,204 (4%) patients. A COVID-19 EMS suspicion was documented for 636 (78%) of hospital diagnosed COVID-19 patients. Those with COVID-19 hospital diagnoses were more likely to present with tachycardia, tachypnea, hypoxia, and fever during the EMS encounter. EMS responses for patients diagnosed with COVID-19 were also more likely to originate from a skilled nursing/assisted living facility. EMS PPE (eye protection, mask, or gown) use was more frequently documented on records of patients who had hospital diagnosed COVID-19. CONCLUSION: In this large sample of prehospital encounters, EMS COVID-19 suspicion demonstrated sensitivity of 78% and positive predictive value of 20% compared with hospital ICD-10 codes. These data indicate that EMS suspicion alone is insufficient to determine appropriate utilization of PPE.


Asunto(s)
COVID-19/diagnóstico , Servicios Médicos de Urgencia , Adolescente , Adulto , Anciano , Anciano de 80 o más Años , COVID-19/complicaciones , Niño , Femenino , Fiebre/etiología , Humanos , Hipoxia/etiología , Masculino , Persona de Mediana Edad , Estudios Retrospectivos , SARS-CoV-2 , Adulto Joven
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