Dataset Information

Accuracy of prehospital transport time estimation.

ABSTRACT: Estimates of prehospital transport times are an important part of emergency care system research and planning; however, the accuracy of these estimates is unknown. The authors examined the accuracy of three estimation methods against observed transport times in a large cohort of prehospital patient transports.This was a validation study using prehospital records in King County, Washington, and southwestern Pennsylvania from 2002 to 2006 and 2005 to 2011, respectively. Transport time estimates were generated using three methods: linear arc distance, Google Maps, and ArcGIS Network Analyst. Estimation error, defined as the absolute difference between observed and estimated transport time, was assessed, as well as the proportion of estimated times that were within specified error thresholds. Based on the primary results, a regression estimate was used that incorporated population density, time of day, and season to assess improved accuracy. Finally, hospital catchment areas were compared using each method with a fixed drive time.The authors analyzed 29,935 prehospital transports to 44 hospitals. The mean (± standard deviation [±SD]) absolute error was 4.8 (±7.3) minutes using linear arc, 3.5 (±5.4) minutes using Google Maps, and 4.4 (±5.7) minutes using ArcGIS. All pairwise comparisons were statistically significant (p < 0.01). Estimation accuracy was lower for each method among transports more than 20 minutes (mean [±SD] absolute error was 12.7 [±11.7] minutes for linear arc, 9.8 [±10.5] minutes for Google Maps, and 11.6 [±10.9] minutes for ArcGIS). Estimates were within 5 minutes of observed transport time for 79% of linear arc estimates, 86.6% of Google Maps estimates, and 81.3% of ArcGIS estimates. The regression-based approach did not substantially improve estimation. There were large differences in hospital catchment areas estimated by each method.Route-based transport time estimates demonstrate moderate accuracy. These methods can be valuable for informing a host of decisions related to the system organization and patient access to emergency medical care; however, they should be employed with sensitivity to their limitations.

SUBMITTER: Wallace DJ

PROVIDER: S-EPMC4251659 | biostudies-literature | 2014 Jan

REPOSITORIES: biostudies-literature

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Accuracy of prehospital transport time estimation.

Wallace David J DJ Kahn Jeremy M JM Angus Derek C DC Martin-Gill Christian C Callaway Clifton W CW Rea Thomas D TD Chhatwal Jagpreet J Kurland Kristen K Seymour Christopher W CW

Academic emergency medicine : official journal of the Society for Academic Emergency Medicine 20140101 1

<h4>Objectives</h4>Estimates of prehospital transport times are an important part of emergency care system research and planning; however, the accuracy of these estimates is unknown. The authors examined the accuracy of three estimation methods against observed transport times in a large cohort of prehospital patient transports.<h4>Methods</h4>This was a validation study using prehospital records in King County, Washington, and southwestern Pennsylvania from 2002 to 2006 and 2005 to 2011, respec ...[more]

PMID: 24552519

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Project description:Background and purposeAcute stroke treatment outcomes are predicated on reperfusion timeliness which can be improved by better prehospital stroke identification. We aimed to assess the effect of interactive emergency medical services (EMS) training on stroke recognition and prehospital care performance in a very high-risk cardiovascular risk population in Lithuania.MethodsWe conducted a single-center interrupted time-series study between March 1, 2019 and March 15, 2020. Two-hour small-group interactive stroke training sessions were organized for 166 paramedics serving our stroke network. We evaluated positive predictive value (PPV) and sensitivity for stroke including transient ischemic attack identification, onset-to-door time, and hospital-based outcomes during 6-months prior and 3.5 months after the training. The study outcomes were compared between EMS providers in urban and suburban areas.ResultsIn total, 677 suspected stroke cases and 239 stroke chameleons (median age 75 years, 54.8% women) were transported by EMS. After the training, we observed improved PPV for stroke recognition (79.8% vs. 71.8%, p = 0.017) and a trend of decreased in-hospital mortality (7.8% vs. 12.3, p = 0.070). Multivariable logistic regression models adjusted for age, gender, EMS location, and stroke subtype showed an association between EMS stroke training and improved odds of stroke identification (adjusted odds ratio [aOR] 1.6 [1.1-2.3]) and onset-to-door ≤ 90 min (aOR 1.6 [1.1-2.5]). The improvement of PPV was observed in urban EMS (84.9% vs. 71.2%, p = 0.003), but not in the suburban group (75.0% vs. 72.6%, p = 0.621).ConclusionsThe interactive EMS training was associated with a robust improvement of stroke recognition, onset to hospital transport time, and a trend of decreased in-hospital mortality. Adapted training strategies may be needed for EMS providers in suburban areas. Future studies should evaluate the long-term effects of the EMS training and identify optimal retraining intervals.

Project description:Survival after major trauma is considered to be time dependent. Efficient prehospital care with rapid transport is the norm in developed countries, which is not available in many lower middle and low-income countries. The aim of this study was to assess the effect of prehospital time and primary treatment given on survival of major trauma patients in a setting without prehospital care.This prospective observational study was carried out in a university hospital in Mumbai, from January to December 2014. The hospital has a trauma service but no organized prehospital care or defined interhospital transfer protocols. All patients with life- and/or limb-threatening injuries were included in the study. Injury time and arrival time were noted and the interval was defined as "prehospital time" for the directly arriving patients and as "time to tertiary care" for those transferred. Primary outcome measure was in-hospital death (or discharge).Of 1181 patients, 352 were admitted directly from the trauma scene and 829 were transferred from other hospitals. In-hospital mortality was associated with age, mechanism and mode of injury, shock, Glasgow Coma Score <9, Injury Severity Score ≥16, need for intubation, and ventilatory support on arrival; but neither with prehospital time nor with time to tertiary care. Transferred patients had a significantly higher mortality (odds ratio = 1.869, 95% confidence interval = 1.233-2.561, P = 0.005) despite fewer patients with severe injury. Two hundred and ninety-four (35%) of these needed airway intervention while 108 (13%) needed chest tube insertion on arrival to the trauma unit suggesting inadequate care at primary facility.Mortality is not associated with prehospital time but with transfers from primary care; probably due to deficient care. To improve survival after major trauma, enhancement of resources for resuscitation and capacity building of on-duty doctors in primary centers should be a priority in countries with limited resources.

Project description:INTRODUCTION:Increased out-of-hospital time is associated with worse outcomes in trauma. Sparse literature exists comparing prehospital scene and transport time management intervals between adult and pediatric trauma patients. National Emergency Medical Services guidelines recommend that trauma scene time be less than 10 minutes. The objective of this study was to examine prehospital time intervals in adult and pediatric trauma patients. METHODS:We performed a retrospective cohort study of blunt and penetrating trauma patients in a five-county region in North Carolina using prehospital records. We included patients who were transported emergency traffic directly from the scene by ground ambulance to a Level I or Level II trauma center between 2013-2018. We defined pediatric patients as those less than 16 years old. Urbanicity was controlled for using the Centers for Medicare and Medicaid's Ambulance Fee Schedule. We performed descriptive statistics and linear mixed-effects regression modeling. RESULTS:A total of 2179 records met the study criteria, of which 2077 were used in the analysis. Mean scene time was 14.2 minutes (95% confidence interval [CI], 13.9-14.5) and 35.3% (n = 733) of encounters had a scene time of 10 minutes or less. Mean transport time was 17.5 minutes (95% CI, 17.0-17.9). Linear mixed-effects regression revealed that scene times were shorter for pediatric patients (p<0.0001), males (p=0.0016), penetrating injury (p<0.0001), and patients with blunt trauma in rural settings (p=0.005), and that transport times were shorter for males (p = 0.02), non-White patients (p<0.0001), and patients in urban areas (p<0.0001). CONCLUSION:This study population largely missed the 10-minute scene time goal. Demographic and patient factors were associated with scene and transport times. Shorter scene times occurred with pediatric patients, males, and among those with penetrating trauma. Additionally, suffering blunt trauma while in a rural environment was associated with shorter scene time. Males, non-White patients, and patients in urban environments tended to have shorter transport times. Future studies with outcomes data are needed to identify factors that prolong out-of-hospital time and to assess the impact of out-of-hospital time on patient outcomes.

Project description:Background and objectivesTo assess the accuracy of baseline CT perfusion (CTP) ischemic core estimates.MethodsFrom SELECT (Optimizing Patient Selection for Endovascular Treatment in Acute Ischemic Stroke), a prospective multicenter cohort study of imaging selection, patients undergoing endovascular thrombectomy who achieved complete reperfusion (modified Thrombolysis In Cerebral Ischemia score 3) and had follow-up diffusion-weighted imaging (DWI) available were evaluated. Follow-up DWI lesions were coregistered to baseline CTP. The difference between baseline CTP core (relative cerebral blood flow [rCBF] <30%) volume and follow-up infarct volume was classified as overestimation (core ≥10 mL larger than infarct), adequate, or underestimation (core ≥25 mL smaller than infarct) and spatial overlap was evaluated.ResultsOf 101 included patients, median time from last known well (LKW) to imaging acquisition was 138 (82-244) minutes. The median baseline ischemic core estimate was 9 (0-31.9) mL and median follow-up infarct volume was 18.4 (5.3-68.7) mL. All 6/101 (6%) patients with overestimation of the subsequent infarct volume were imaged within 90 minutes of LKW and achieved rapid reperfusion (within 120 minutes of CTP). Using rCBF <20% threshold to estimate ischemic core in patients presenting within 90 minutes eliminated overestimation. Volumetric correlation between the ischemic core estimate and follow-up imaging improved as LKW time to imaging acquisition increased: Spearman ρ <90 minutes 0.33 (p = 0.049), 90-270 minutes 0.63 (p < 0.0001), >270 minutes 0.86 (p < 0.0001). Assessment of the spatial overlap between baseline CTP ischemic core lesion and follow-up infarct demonstrated that a median of 3.2 (0.0-9.0) mL of estimated core fell outside the subsequent infarct. These regions were predominantly in white matter.DiscussionSignificant overestimation of irreversibly injured ischemic core volume was rare, was only observed in patients who presented within 90 minutes of LKW and achieved reperfusion within 120 minutes of CTP acquisition, and occurred primarily in white matter. Use of a more conservative (rCBF <20%) threshold for estimating ischemic core in patients presenting within 90 minutes eliminated all significant overestimation cases.Trial registration informationClinicalTrials.gov: NCT03876457.

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Accuracy of prehospital transport time estimation.

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Accuracy of prehospital transport time estimation.

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