The effect of emergency medical system transport time on in route clinical decline in a rural system

Burden of Non-Protocolized Patient Transport Outside of Response Area on a Rural Emergency Medical Services System

OBJECTIVES

Transport destination decisions by prehospital personnel depend on a combination of protocols, judgment, patient acuity, and patient preference. Non-protocolized transport outside the service area may result in unnecessary time out of service and inappropriate resource utilization. Scant research exists regarding clinician rationale for destination decisions.

METHODS

We retrospectively reviewed one year of scene transports by a single rural, hospital-based emergency medical services (EMS) system. We collected dispatch, patient demographic, primary impression, and transport data from prehospital records and matched them to emergency department (ED) data. We characterized rationale for transport decisions and compared rates of hospital admission and specialist consultation in the ED as surrogates for decision appropriateness.

RESULTS

We reviewed 2,223 patient transports, 281 of which were transported out of the service area. The most common reasons for out-of-area transport were patient preference NOT related to prior medical care (40%) and clinician judgment (24%). Admit rates were highest for per protocol (85%) and patient preference related to prior medical care (67%) groups and lowest for no explanation (41%) and clinician judgment (47%) groups. Rates of in person specialist consultation in the ED were highest in per protocol (69%) and clinician judgment (47%) groups and lowest in no explanation (23%) and patient preference NOT related to prior medical care (30%) groups. Clinician judgment was less predictive of admission and specialist consultation for non-trauma and pediatric patients than for all patients. Median time out of service was more than twice as long for out-of-area transports (140 min) compared to patients transported to the nearest facility (62 min). For out-of-area transports discharged from the ED without specialty consultation (n = 104), ambulances traveled an additional 52 miles/patient compared to theoretical transport to nearest facility.

CONCLUSIONS

Unit out of service time more than doubled for non-protocolized transports outside of the service area and rationale for destination decisions variably predicted admission and specialist consultation rates. Patient preference NOT related to prior medical care and, in pediatric and non-trauma populations, clinician judgment, were less predictive of admission and specialist consultation. Transport guidelines should balance rationale for transport destination and patient characteristics with resource preservation, especially in low-resource systems.

Access to Trauma Care in a Rural State: A Descriptive Geographic and Demographic Analysis

BACKGROUND

Montana is a rural state with limited access to higher-level trauma care; it also has higher injury fatality rates compared with the rest of the country.

OBJECTIVES

The purpose of this study was to utilize Geographic Information System methodology to assess proximity to trauma care and identify the demographic characteristics of regions without trauma access.

METHODS

Maptitude® Geographic Information System software (Caliper Corporation, Newton, MA) was used to identify regions in Montana within 60 min of trauma care; this included access to a Level II or Level III trauma center with general surgery capabilities and access to any level of trauma care. Demographic characteristics are reported to identify population groups lacking access to trauma care.

RESULTS

Of the 1.1 million residents of Montana, 63% of residents live within 60 driving min of a higher-level trauma center, and 83% of residents live within 60 driving min of any level of trauma center. Elderly residents over age 65 years of age and American Indians had reduced access to both higher-level trauma care and any level trauma care.

CONCLUSIONS

Prompt access to trauma care is significantly lower in Montana than in other parts of the country, with dramatic disparities for American Indians. In a rural state, it is important to ensure that all hospitals are equipped to provide some level of trauma care to reduce these disparities.

Clinical Impact of Prolonged Helicopter Emergency Travel Times in a Rural Trauma System

BACKGROUND

In the United States, healthcare organizations utilize helicopter emergency medical services (HEMS), which are well-established and integral to trauma and emergency medical transport. HEMS expedites critical resources to trauma patients at the initial scene of the accident, which typically falls outside of the effective service area of ground transportation.

METHODS

This is a single-center study of trauma registry data, inclusive years July 1, 2016, to September 26, 2021. The inclusion criteria were all adult ICU patients (≥18 years) traveling by air. An initial bivariate analysis was used to describe differences in HEMS vs rendezvous (ground + HEMS) mode of arrival. A multivariate linear regression was calculated to predict elapsed transport times on predictor variables to determine the clinical impact of prolonged transport times.

RESULTS

There were 242 patients identified in the analysis, with 87 (36%) traveling by HEMS and 155 (64%) traveling by rendezvous. A significant regression equation was found (F(29,198) = 2.39, P < .01), with an R2 of .26. As the transport time increased by 10.67 minutes, the shock index ratio (SIR) increased by one unit (P = .04). Conversely, for each unit increase in Glasgow Coma Scores (GCS), flight time decreased by 1.03 minutes (P < .01). Rendezvous transport times were on average eight minutes longer than HEMS alone (P < .01).

CONCLUSIONS

Those with prolonged travel times were likely to travel by rendezvous with presentation of lower GCS and higher SIR upon arrival, despite equivocal injury patterns and severity. This research highlights the need for a helicopter auto-launch program to expedite helicopter travel times in distant locations to the only Level I trauma center in the region.

Direct Trauma Center Access by Helicopter Emergency Medical Services is Associated With Improved Survival After Severe Injury

OBJECTIVE

Evaluate the association of survival with helicopter transport directly to a trauma center compared with ground transport to a non-trauma center (NTC) and subsequent transfer.

SUMMARY BACKGROUND DATA

Helicopter transport improves survival after injury. One potential mechanism is direct transport to a trauma center when the patient would otherwise be transported to an NTC for subsequent transfer.

METHODS

Scene patients 16 years and above with positive physiological or anatomic triage criteria within PTOS 2000-2017 were included. Patients transported directly to level I/II trauma centers by helicopter were compared with patients initially transported to an NTC by ground with a subsequent helicopter transfer to a level I/II trauma center. Propensity score matching was used to evaluate the association between direct helicopter transport and survival. Individual triage criteria were evaluated to identify patients most likely to benefit from direct helicopter transport.

RESULTS

In all, 36,830 patients were included. Direct helicopter transport was associated with a nearly 2-fold increase in odds of survival compared with NTC ground transport and subsequent transfer by helicopter (aOR 2.78; 95% CI 2.24-3.44, P <0.01). Triage criteria identifying patients with a survival benefit from direct helicopter transport included GCS≤13 (1.71; 1.22-2.41, P <0.01), hypotension (2.56; 1.39-4.71, P <0.01), abnormal respiratory rate (2.30; 1.36-3.89, P <0.01), paralysis (8.01; 2.03-31.69, P <0.01), hemothorax/pneumothorax (2.34; 1.36-4.05, P <0.01), and multisystem trauma (2.29; 1.08-4.84, P =0.03).

CONCLUSIONS

Direct trauma center access is a mechanism driving the survival benefit of helicopter transport. First responders should consider helicopter transport for patients meeting these criteria who would otherwise be transported to an NTC.

Redefining trauma deserts: novel technique to accurately map prehospital transport time

Background

Prehospital transport time has been directly related to mortality for hemorrhaging trauma patients. 'Trauma deserts' were previously defined as being outside of a 5-mile radial distance of an urban trauma center. We postulated that the true 'desert' should be based on transport time rather than transport distance.

Methods

Using the Chicagoland area that was used to describe 'trauma deserts,' a sequential process to query a commercial travel optimization product to map transport times over coordinates that covered the entire urban area at a particular time of day. This produces a heat map representing prehospital transport times. Travel times were then limited to 15 minutes to represent a temporally based map of transport capabilities. This was repeated during high and low traffic times and for centers across the city.

Results

We demonstrated that the temporally based map for transport to a trauma center in an urban center differs significantly from the radial distance to the trauma center. Primary effects were proximity to highways and the downtown area. Transportation to centers were significantly different when time was considered instead of distance (p<0.001). We were further able to map variations in traffic patterns and thus transport times by time of day. The truly 'closest' trauma center by time changed based on time of day and was not always the closest hospital by distance.

Discussion

As the crow flies is not how the ambulance drives. This novel technique of dynamically mapping transport times can be used to create accurate trauma deserts in an urban setting with multiple trauma centers. Further, this technique can be used to quantify the potential benefit or detriment of adding or removing firehouses or trauma centers.

Prehospital characteristics of COVID-19 patients transported by emergency medical service and the predictors of a prehospital sudden deterioration in Addis Ababa, Ethiopia

Background

Severally ill COVID-19 patients may require urgent transport to a specialized facility for advanced care. Prehospital transport is inherently risky; the patient’s health may deteriorate, and potentially fatal situations may arise. Hence, early detection of clinically worsening patients in a prehospital setting may enable selecting the best receiving facility, arranging for swift transportation, and providing the most accurate and timely therapies. The incidence and predictors of abrupt prehospital clinical deterioration among critically ill patients in Ethiopia are relatively limited.

Study objectives

This study was conducted to determine the incidence of sudden clinical deterioration during prehospital transportation and its predictors.

Methods

A prospective cohort study of 591 COVID-19 patients transported by a public EMS in Addis Ababa. For data entry, Epi data V4.2 and SPSS V 25 were used for analysis. To control the effect of confounders, the candidate variables for multivariable analysis were chosen using a p 0.25 inclusion threshold from the bivariate analysis. A statistically significant association was declared at adjusted relative risk (ARR) ≠ 1 with a 95 % confidence interval (CI) and a p value < 0.05 after adjusting for potential confounders.

Results

The incidence of prehospital sudden clinical deterioration in this study was 10.8%. The independent predictors of prehospital sudden clinical deterioration were total prehospital time [ARR 1.03 (95%; CI 1.00–1.06)], queuing delays [ARR 1.03 (95%; CI 1.00–1.06)], initial prehospital respiratory rate [ARR 1.07 (95% CI 1.01–1.13)], and diabetic mellitus [ARR 1.06 (95%; CI 1.01–1.11)].

Conclusion

In the current study, one in every ten COVID-19 patients experienced a clinical deterioration while an EMS provider was present. The factors that determined rapid deterioration were total prehospital time, queueing delays, the initial respiratory rate, and diabetes mellitus. Queueing delays should be managed in order to find a way to decrease overall prehospital time. According to this finding, more research on prehospital intervention and indicators of prehospital clinical deterioration in Ethiopia is warranted.

Do new trauma centers provide needed or redundant access? A nationwide analysis

BACKGROUND

Our prior research has demonstrated that increasing the number of trauma centers (TCs) in a state does not reliably improve state-level injury-related mortality. We hypothesized that many new TCs would serve populations already served by existing TCs, rather than in areas without ready TC access. We also hypothesized that new TCs would also be less likely to serve economically disadvantaged populations.

METHODS

All state-designated adult TCs registered with the American Trauma Society in 2014 and 2019 were mapped using ArcGIS Pro (ESRI Inc., Redlands, CA). Trauma centers were grouped as Level 1 or 2 (Lev12) or Level 3, 4 or 5 (Lev345). We also obtained census tract-level data (73,666 tracts), including population counts and percentage of population below the federal poverty threshold. Thirty-minute drive-time areas were created around each TC. Census tracts were considered "served" if their geographic centers were located within a 30-minute drive-time area to any TC. Data were analyzed at the census tract level.

RESULTS

A total of 2,140 TCs were identified in 2019, with 256 new TCs and 151 TC closures. Eighty-two percent of new TCs were Levels 3 to 5. Nationwide, coverage increased from 75.3% of tracts served in 2014 to 78.1% in 2019, representing an increased coverage from 76.0% to 79.4% of the population. New TC served 17,532 tracts, of which 87.3% were already served. New Lev12 TCs served 9,100 tracts, of which 91.2% were already served; new Lev345 TCs served 15,728 tracts, of which 85.9% were already served. Of 2,204 newly served tracts, those served by Lev345 TCs had higher mean percentage poverty compared with those served by Lev12 TCs (15.7% vs. 13.2% poverty, p < 0.05).

DISCUSSION

Overall, access to trauma care has been improving in the United States. However, the majority of new TCs opened in locations with preexisting access to trauma care. Nationwide, Levels 3, 4, and 5 TCs have been responsible for expanding access to underserved populations.

LEVEL OF EVIDENCE

Prognostic and Epidemiologic; Level IV.

Effects of mode and time of EMS transport on the rate and distribution of dead on arrival among trauma population transported to ACSCOT-verified trauma centers in the United States

BACKGROUND

Unintentional injury remains the leading cause of death for adults worldwide. We aimed to investigate the rates and distribution of dead on arrival (DOA) patients according to emergency medical services (EMS) mode of transport (MoT), EMS transport time (TT), injury severity score (ISS), and type of injury.

METHODS

This retrospective study utilized de-identified incident-based data from the American College of Surgeons Trauma Quality Improvement Program Participant Use File (ACS-TQIP PUF) dataset (2013-2018) to study Adult DOA patients. DOA was defined according to the data point, "arrived with no signs of life and did not recover". Patients with unknown vitals and patients with no EMS vitals at the scene (HR = 0, RR = 0, and SBP = 0) were excluded to identify DOAs who died during transport. The DOAs included for analysis were sorted into three groups based on injury severity score [low (ISS < 15), intermediate (ISS = 15-24), and severe (ISS ≥ 25)] and subdivided according to injury type (blunt vs. penetrating), EMS Mode of transport and transport times. Statistical significance was defined as p < 0.05.

RESULTS

The majority of the evaluated 6030 adult DOA patients were male (73.3%) and 18-64 years of age (79.6%). Most patients sustained blunt injuries (58.2%), and the most common mechanism of injury was motor vehicle collisions (MVCs). Patients who traveled by helicopter EMS (HEMS) experienced less deaths than those traveling by ground EMS (GEMS) despite transporting more severely injured patients over longer time intervals. Median HEMS TTs were greater than their GEMS counterparts for blunt and penetrating injuries across all ISS groups but were associated with fewer deaths.

CONCLUSION

Helicopter emergency medical service use with intermediate and severely injured patients with penetrating injuries is associated with a reduced number of DOAs. Future studies should prospectively investigate EMS performance to confirm the findings identified in this retrospective analysis. Additionally, other factors affecting pre-hospital EMS performance (e.g., geographic variations, weather-related characteristics, in-flight interventions/procedures) should be investigated. Finally, the results of this study highlight the need for standardized HEMS utilization triage criteria.

Association of Prehospital Step 1 Vital Sign Criteria and Vital Sign Decline with Increased Emergency Department and Hospital Death

BACKGROUND

This study analyzed data from the 2017 American College of Surgeons National Trauma Data Bank to examine the effects of pre-hospital Field Triage Decision Scheme Step 1 vital sign criteria (S1C) and vital sign decline on subsequent emergency department (ED) and hospital death in emergency medical services (EMS) transported trauma victims.

STUDY DESIGN

Patient and injury characteristics, transport time, and ED and hospital disposition were collected. S1C (respiratory rate [RR]<10, RR>29 breaths/min, systolic blood pressure [SBP]<90 mmHg, Glasgow Coma Scale [GCS]<14) were recorded at the injury scene and hospital arrival. Decline was defined as a change ≥ 1 standard deviation (SD) into or within an S1C range. S1C and decline were analyzed relative to ED and hospital death using logistic regression.

RESULTS

Of 333,213 included patients, 54,849 (16.5%) met Step 1 criteria at the scene, and 21,566 (6.9%) declined en route. The ED death rate was 0.4% (n = 1,188), and the hospital death/hospice rate was 4.0% (11,624 of 287,675). Patients who met S1C at the scene or who declined were more likely to require longer hospital lengths of stay, ICU admission, and surgical intervention. S1C and decline patients had higher odds of death in both the ED (S1C odds ratio [OR] 15.1, decline OR 2.4, p values < 0.001) and hospital (S1C OR 4.8, decline OR 2.0, p values < 0.001) after adjusting for patient demographics, transport time and mode, injury severity, and injury mechanism. Each S1C and decline measure was independently predictive of death.

CONCLUSIONS

This study quantifies the mortality risks associated with individual S1C and validates their use as an indicator for injury severity and pre-hospital triage tool.