Journal of Pediatric Surgery xxx (2014) xxx–xxx
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Journal of Pediatric Surgery journal homepage: www.elsevier.com/locate/jpedsurg
Helicopter versus ground emergency medical services for the transportation of traumatically injured children Camille L. Stewart a,b,⁎, Ryan R. Metzger c, Laura Pyle d, Joe Darmofal e, Eric Scaife c, Steven L. Moulton a,b a
University of Colorado School of Medicine, Department of Surgery, 12631 E. 17th Ave, C302, Aurora, CO 80045 Children’s Hospital Colorado, Division of Pediatric Surgery, 13123 E. 16th Ave, B232, Aurora, CO 80045 Primary Children's Hospital, Division of Pediatric Surgery, 100 N Mario Capecchi Dr, Suite 2600, Salt Lake City, UT 84113 d University of Colorado School of Medicine, Department of Pediatrics, 13001 E. 17th Place, C290, Aurora, CO 80045 e Children’s Hospital Colorado, Department of Transport & EMS Outreach and Education, 13123 E. 16th Ave, B245, Aurora, CO 80045 b c
a r t i c l e
i n f o
Article history: Received 6 September 2014 Accepted 8 September 2014 Available online xxxx Key words: Helicopter emergency medical services Pediatric trauma Air transport Resource utilization
a b s t r a c t Background: Helicopter emergency medical services (HEMS) are a common mode of transportation for pediatric trauma patients. We hypothesized that HEMS improve outcomes for traumatically injured children compared to ground emergency medical services (GEMS). Methods: We queried trauma registries of two level 1 pediatric trauma centers for children 0–17 years, treated from 2003 to 2013, transported by HEMS or GEMS, with known transport starting location and outcome. A geocoding service estimated travel distance and time. Multivariate regression analyses were performed to adjust for injury severity variables and travel distance/time. Results: We identified 14,405 traumatically injured children; 3870 (26.9%) transported by HEMS and 10,535 (73.1%) transported by GEMS. Transport type was not significantly associated with survival, ICU length of stay, or discharge disposition. Transport by GEMS was associated with a 68.6%–53.1% decrease in hospital length of stay, depending on adjustment for distance/time. Results were similar for children with severe injuries, and with propensity score matched cohorts. Of note, 862/3850 (22.3%) of HEMS transports had an ISS b10 and hospitalization b 1 day. Conclusions: HEMS do not independently improve outcomes for traumatically injured children, and 22.3% of children transported by HEMS are not significantly injured. These factors should be considered when requesting HEMS for transport of traumatically injured children. © 2014 Elsevier Inc. All rights reserved.
Helicopter emergency medical services (HEMS) are often used for the transportation of traumatically injured children. HEMS transport is faster and has a more experienced crew compared to ground emergency medical services (GEMS), but is significantly more expensive [1,2]. As the political and economic climates shift towards price conscious medical consumerism, the value of HEMS needs to be proven. Studies comparing HEMS to GEMS for traumatically injured adults are conflicting [3] , and there are no large-scale or multi-center studies examining this question in pediatric trauma patients. More than 25% of Americans are reliant on HEMS for access to a trauma center in under an hour [4], and treatment at a designated pediatric trauma center decreases mortality for traumatically injured children [5,6]. Thus, we hypothesized that HEMS would improve outcomes compared to GEMS for Abbreviations: HEMS, helicopter emergency medical services; GEMS, ground emergency medical services; LOS, length of stay; GIS, Geographic Information Systems. ⁎ Corresponding author at: University of Colorado School of Medicine, Department of Surgery, 12631 E. 17th Ave, C302, Aurora, CO 80045. Tel.: +1 256 694 1233. E-mail addresses: [email protected] (C.L. Stewart), [email protected] (R.R. Metzger), [email protected] (L. Pyle), [email protected] (J. Darmofal), [email protected] (E. Scaife), [email protected] (S.L. Moulton).
traumatically injured children. To study this, we combined patient data from two level-1 pediatric trauma centers, which are the only level-1 pediatric trauma centers in their respective states [7]. Experience has shown that case fatality rates for children are lower than adults [8], making a survival benefit difficult to detect in this population. For this reason we also compared the effect of HEMS on additional outcomes, including hospital length of stay (LOS), intensive care unit (ICU) LOS, and discharge disposition. 1. Methods After approval from both centers institutional review boards, we queried the trauma registries of two level 1 pediatric trauma centers for children 0–17 years old treated from January 2003 to January 2013, with transportation by either HEMS or GEMS, known transport starting location (either injury scene zip code for those transported directly from the scene, or address of transferring facility for those transported from another facility), and known outcome. Children with burns and those who were dead on arrival were excluded from analysis. A priori selected covariates included in the analysis were transport type, age, gender, trauma type (blunt or penetrating), referral status, Glasgow
http://dx.doi.org/10.1016/j.jpedsurg.2014.09.040 0022-3468/© 2014 Elsevier Inc. All rights reserved.
Please cite this article as: Stewart CL, et al, Helicopter versus ground emergency medical services for the transportation of traumatically injured children, J Pediatr Surg (2014), http://dx.doi.org/10.1016/j.jpedsurg.2014.09.040
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C.L. Stewart et al. / Journal of Pediatric Surgery xxx (2014) xxx–xxx
Coma Scale score (GCS), vital signs (including: heart rate (HR), respiratory rate (RR), and systolic blood pressure (SBP)), intubation status, injury severity score (ISS), estimated drive distance and time, and estimated flight distance and time. GCS and vital signs used in the analysis were from the location initiating the transport. The outcomes for comparison were survival, hospital LOS, ICU LOS, and discharge disposition. Discharge disposition was divided into discharge home without services, versus all other living dispositions, here called discharge with services. A geocoding service was used to estimate travel distance and time to the definitive treating hospital via HEMS or GEMS. The urban or rural status of the location initiating transport was determined using the 2013 census-based NCHS Urban–Rural Classification Scheme for Counties [9]. Data were available for all subjects, except where noted otherwise. 1.1. Theory/calculation 1.1.1. Geographic Information Systems estimates The DIGIT Lab at the University of Utah calculated all Geographic Information Systems (GIS) data. Addresses of transferring facilities were geocoded based upon street addresses using the default Esri ArcGIS geocoding service. Addresses that were not automatically matched were hand placed using reference maps and imagery to identify the hospital location. Because the exact location of injury was often unknown, the zip code in which the injury occurred was used to estimate travel distances/times for cases in which the patient was transported directly from the scene. Injury zip codes were matched to the centroid of the zip code geometry using Esri’s zip code data. Driving distances and times were calculated using Esri’s Network Analyst extension and the StreetMap USA network data set. It should be noted that speed limit data on the network road data set might be out of date due to recent increases in speed for some major highways and interstates. This would result in slightly longer travel times than if compared to Google maps. For comparison, the Euclidean distance from each point to its respective destination was also calculated in order to estimate flight distances, and flight times were calculated based on an estimated speed of 125 knots. 1.1.2. Statistical analysis In the first set of analyses, the entire dataset that resulted from the query of the trauma registries was included. However, because the more severely injured children were more likely to have been transported by HEMS, we attempted to account for the resulting bias in favor of GEMS by matching subjects on propensity scores and repeating the analysis in the matched dataset. Propensity scores for GEMS transport were based on a logistic model with GEMS transport as the outcome and GCS and ISS as predictors. In both the unmatched and matched analyses, nonparametric statistics were computed because most variables were not normally distributed. In the unmatched analyses, univariate analyses utilized logistic regression, linear regression, or the Kruskal Wallis test. In unmatched multivariate analyses, linear regression and logistic models were used. In the matched analyses, linear regression adjusted for propensity score, or mixed models with a propensity score random effect were used to account for matching. In all multivariate analyses, hospital LOS and ICU LOS were log-transformed (with 0.00001 added to any zero values before taking the log). Three versions of the multivariate models were tested. In the first version of the models, no adjustments for time or distance were made. In the second version, the models were adjusted for drive distance and time regardless of the transport type used for the patient. In the third and final version, the models were adjusted for travel distance and time (using drive distance/time for GEMS cases, and using Euclidean distance/flight time for HEMS cases). Chi-square and Kruskal–Wallis tests were used to determine differences between children transported from urban and rural counties.
Statistical differences were considered significant if the probability of a type I error was b5% (p b 0.05). All analyses were performed using SAS version 9.3.
2. Results 2.1. Demographics We identified 14,405 children who met inclusion criteria for our study; a total of 3870 (26.9%) children were transported by HEMS and 10,535 (73.1%) were transported by GEMS. Descriptive statistics are reported in Table 1. The majority of children identified were young males with blunt injuries, normal vital signs, and minimal to moderate injury severity, who traveled less than 30 miles from the injury scene or referring facility. Of note, 862 children (22.3%) transported by HEMS had an ISS b10 and a hospital LOS ≤ 1 day. The initial data set had a disproportionate number of HEMS subjects with higher ISS scores (p b 0.001, Fig. 1), so we also evaluated a subgroup of children with an ISS N15 (Table 2, n = 2987), and a smaller subgroup of propensity score Table 1 Descriptive statistics of all children identified. Category
Gender (n missing = 1) Female Male Age (years) Very young (0–5) Young (6–14) Teenager (15–17) Trauma Type (n missing = 41) Blunt Penetrating Referral status No referral Clinic referral Hospital referral Injury Severity Score category (n missing = 95) Minimal to moderate (0–15) Major (16–24) Severe (N24) GCS (n missing = 3904) GCS = 15 GCS = 3–14 Age adjusted HR (n missing = 3816) Normal/Low High RR (n missing = 2817) Low b9 Normal/High ≥9 SBP (n missing = 5320) Hypotensive ≤ 80 Normotensive N80 Outcome Alive Dead Discharge disposition Discharged home without services Discharged with services Transferred N30 driving miles No Yes Hospital LOS ≤1 day and ISS b 10 (n missing = 95) No Yes
Transport type GEMS (N = 10,535)
HEMS (N = 3870)
N
N
%
%
Total (N = 14,405)
N
%
3724 35.35 1401 36.20 6811 64.65 2468 63.77
5125 35.58 9279 64.42
4728 44.88 1763 45.56 5037 47.81 1833 47.36 770 7.31 274 7.08
6491 45.06 6870 47.69 1044 7.25
10,257 97.36 3744 96.74 14,001 97.20 260 2.47 103 2.66 363 2.52 2498 23.71 1107 28.60 3605 25.03 433 4.11 52 1.34 485 3.37 7604 72.18 2711 70.05 10,315 71.61
9177 87.11 2146 55.45 11,323 78.60 969 9.20 921 23.80 1890 13.12 314 2.98 783 20.23 1097 7.62 6804 64.58 1701 43.95 744 7.06 1252 32.35
8505 59.04 1996 13.86
6739 63.97 2332 60.26 963 9.14 555 14.34
9071 62.97 1518 10.54
83 0.79 225 5.81 308 2.14 8448 80.19 2832 73.18 11,280 78.31 104 0.99 192 4.96 6120 58.09 2669 68.97
296 2.05 8789 61.01
10,473 99.41 3634 93.90 14,107 97.93 62 0.59 236 6.10 298 2.07 9849 93.49 3114 80.47 12,963 89.99 624
5.92
520 13.44
1144
7.94
7237 68.69 1162 30.03 3298 31.31 2708 69.97
8399 58.31 6006 41.69
4105 38.97 2988 77.21 6355 60.32 862 22.27
7093 49.24 7217 50.10
Please cite this article as: Stewart CL, et al, Helicopter versus ground emergency medical services for the transportation of traumatically injured children, J Pediatr Surg (2014), http://dx.doi.org/10.1016/j.jpedsurg.2014.09.040
C.L. Stewart et al. / Journal of Pediatric Surgery xxx (2014) xxx–xxx
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Table 3 Descriptive statistics of propensity score matched children. Category
Fig. 1. Box plot of injury severity score versus transport mode.
matched children based on GCS and ISS to further improve adjustment for injury severity (Table 3, n = 1446). To determine if there were outcome differences between HEMS and GEMS, we compared survival, hospital LOS, ICU LOS, and discharge disposition using multivariate regression analyses of these three data sets. Each data set was subject to three separate analyses that differed based on the adjustment for time and distance traveled. The first analysis was calculated without Table 2 Descriptive statistics of children with an injury severity score greater than 15. Transport
Gender Female Male Age Very young (0–5 years) Young (6–14 years) Teenager (15–17 years) Trauma Type (n missing = 16) Blunt Penetrating Referral status No referral Clinic referral Hospital referral ISS Major (16–24) Severe (N24) GCS (n missing = 747) GCS = 15 GCS = 3–14 Age Adjusted HR (n missing = 747) Normal/Low High RR (n missing = 634) Low b9 Normal/High ≥9 SBP (n missing = 991) Hypotensive ≤80 Normotensive N80 Outcome Alive Dead Discharge disposition Discharged home without services Discharged with services Transferred N30 driving miles No Yes
Total (N = 2987)
GEMS (N = 1283)
HEMS (N = 1704)
N
%
N
%
N
%
466 817
36.32 63.68
607 1097
35.62 64.38
1073 1914
35.92 64.08
692 510 81
53.94 39.75 6.31
793 794 117
46.54 46.60 6.87
1485 1304 198
49.72 43.66 6.63
1276 6
99.45 0.47
1661 28
97.48 1.64
2937 34
98.33 1.14
347 34 902
27.05 2.65 70.30
358 12 1334
21.01 0.70 78.29
705 46 2236
23.60 1.54 74.86
969 314
75.53 24.47
921 783
54.05 45.95
1890 1097
63.27 36.73
689 230
53.70 17.93
556 765
32.63 44.89
1245 995
41.68 33.31
802 147
62.51 11.46
1008 283
59.15 16.61
1810 430
60.60 14.40
56 990
4.36 77.16
196 1111
11.50 65.20
252 2101
8.44 70.34
46 686
3.59 53.47
152 1112
8.92 65.26
198 1798
6.63 60.19
1228 55
95.71 4.29
1481 223
86.91 13.09
2709 278
90.69 9.31
1024 204
79.81 15.90
1089 392
63.91 23.00
2113 596
70.74 19.95
848 435
66.10 33.90
488 1216
28.64 71.36
1336 1651
44.73 55.27
Gender Female Male Age Very young (0–5 years) Young (6–14 years) Teenager (15–17 years) Trauma Type (n missing = 7) Blunt Penetrating Referral status No referral Clinic referral Hospital referral ISS Minimal to moderate (0–15) Major (16–24) Severe (N24) GCS GCS = 15 GCS = 3–14 Age Adjusted HR (n missing = 208) Normal/Low High RR (n missing = 122) Low b9 Normal/High ≥9 SBP (n missing = 329) Hypotensive ≤80 Normotensive N80 Outcome Alive Dead Discharge disposition Discharged home without services Discharged with services Transferred N30 driving miles No Yes
Transport type
Total (N = 1446)
GEMS (N = 667)
HEMS (N = 779)
N
%
N
%
244 423
36.58 63.42
272 507
34.92 65.08
516 930
35.68 64.32
300 314 53
44.98 47.08 7.95
328 386 65
42.11 49.55 8.34
628 700 118
43.43 48.41 8.16
658 7
98.65 1.05
763 11
97.95 1.41
1421 18
98.27 1.24
216 11 440
32.38 1.65 65.97
199 3 577
25.55 0.39 74.07
415 14 1017
28.70 0.97 70.33
324 204 139
48.58 30.58 20.84
158 278 343
20.28 35.69 44.03
482 482 482
33.33 33.33 33.33
428 239
64.17 35.83
295 484
37.87 62.13
723 723
50.00 50.00
486 90
72.86 13.49
517 145
66.37 18.61
1003 235
69.36 16.25
22 617
3.30 92.50
88 597
11.30 76.64
110 1214
7.61 83.96
18 443
2.70 66.42
62 594
7.96 76.25
80 1037
5.53 71.72
650 17
97.45 2.55
697 82
89.47 10.53
1347 99
93.15 6.85
569 81
85.31 12.14
557 140
71.50 17.97
1126 221
77.87 15.28
454 213
68.07 31.93
229 550
29.40 70.60
683 763
47.23 52.77
N
%
adjustment for travel distance or time. The second analysis adjusted for drive distance and time, regardless if HEMS or GEMS was used for transportation. The third and final analysis adjusted for travel distance and time calculated based on whether HEMS or GEMS was utilized (flight estimates or driving estimates, respectively). 2.2. Analysis without adjusting for travel distances or times Multivariate regression analysis of the entire data set revealed that survival, ICU LOS, and discharge disposition were not significantly associated with transport type. Hospital LOS, however, was significantly associated with transport type (p b 0.001). Age (p b 0.001), GCS (p b 0.001), HR (p = 0.001), RR (p b 0.001), SBP (p b 0.001), and ISS (p b 0.001) were also independently associated with hospital LOS. Compared to HEMS, transport by GEMS was associated with a 68.6% decrease in hospital LOS. Multivariate regression analysis of the subset of children with an ISS N15 revealed that survival was not significantly associated with transport type. Hospital LOS was significantly associated with transport type (p b 0.001), in addition to age (p = 0.002), GCS (p = 0.001), HR (p b 0.001), RR (p b 0.001), and SBP (p b 0.001). Compared to HEMS, transport by GEMS was associated with a 61.0% decrease in hospital LOS. ICU LOS was also significantly associated with transport type (p = 0.05), in addition to referral status (p = 0.002), GCS (p b 0.001), HR (p = 0.002), RR (p = 0.003), and SBP (p = 0.001). Transport by
Please cite this article as: Stewart CL, et al, Helicopter versus ground emergency medical services for the transportation of traumatically injured children, J Pediatr Surg (2014), http://dx.doi.org/10.1016/j.jpedsurg.2014.09.040
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C.L. Stewart et al. / Journal of Pediatric Surgery xxx (2014) xxx–xxx
GEMS was associated with a 13.6% decrease in ICU LOS compared to HEMS. Discharge disposition was also significantly associated with transport type (p = 0.02) and GCS (p b 0.0001). The odds of being discharged with services were significantly lower when transported by GEMS compared to HEMS (OR 0.64, 95% CI 0.45–0.92). Multivariate regression analysis of the propensity score matched data set revealed that survival, ICU LOS, and discharge disposition were not significantly associated with transport type. Hospital LOS was significantly associated with transport type (p = 0.01), in addition to referral status (p = 0.02), HR (p = 0.02), RR (p = 0.02), and SBP (p = 0.05). Compared to HEMS, transport by GEMS was associated with a 44.9% decrease in hospital LOS. 2.3. Analysis using drive distances and times Multivariate regression analysis of the entire data set, and using only driving estimates, showed that survival, ICU LOS, and discharge disposition were not significantly associated with transport type. Hospital LOS was significantly associated with transport type (p b 0.001), as well as age (p = 0.001), referral status (p b 0.001), GCS (p b 0.001), HR (p = 0.001), RR (p = 0.002), SBP (p b 0.001), ISS (p b 0.001), estimated drive distance (p b 0.001), and estimated drive time (p b 0.001). GEMS transport was associated with a 53.1% reduction in the hospital LOS compared to HEMS. Multivariate regression analysis of the subset of children with an ISS N 15 showed that survival and ICU LOS were not significantly associated with transport type. Hospital LOS was significantly associated with transport type (p b 0.001), in addition to age (p = 0.002), GCS (p = 0.001), HR (p b 0.001), RR (p b 0.001), and SBP (p b 0.001). Transport by GEMS was associated with a 59.7% reduction in the hospital LOS compared to HEMS. Discharge disposition was significantly associated with transport type (p = 0.02) and GCS (p b 0.001). The odds of being discharged with services were significantly lower when transported by GEMS compared to HEMS (OR 0.66, 95% CI 0.45–0.95). Multivariate regression analysis of the propensity score matched data set revealed that survival, hospital LOS, ICU LOS and discharge disposition were not significantly associated with transport type. 2.4. Analysis using travel distances and times Multivariate regression analysis of the entire data set using travel distances/times corresponding to the transport type utilized for each case revealed that survival, ICU LOS, and discharge disposition were not significantly associated with transport type. Hospital LOS was significantly associated with transport type (p b 0.001), in addition to age (p b 0.001), referral status (p = 0.005), GCS (p b 0.001), HR (p = 0.001), RR (p = 0.002), SBP (p b 0.001), ISS (p b 0.001), and travel distance (p = 0.04). Transport by GEMS was associated with a 65.3% decrease in hospital LOS compared to HEMS. Multivariate regression analysis of the subset of children with an ISS N 15 revealed that survival, ICU LOS, and discharge disposition were not significantly associated with transport type. Hospital LOS was significantly associated with transport type, in addition to age (p = 0.002), GCS (p = 0.001), HR (p b 0.001), RR (p b 0.001), and SBP (p b 0.001). Transport by GEMS was associated with a 61.4% decrease hospital LOS compared to HEMS. Multivariate regression analysis of the propensity score matched data set revealed that survival, hospital LOS, ICU LOS and discharge disposition were not significantly associated with transport type. 2.5. Additional analysis In order to determine whether there was any benefit derived from HEMS at greater drive distances or times, the interaction of transport type was tested with drive distances and times categorized as b 75th percentile versus ≥ 75th percentile, b90th percentile versus ≥ 90th
percentile, and b 95th percentile versus ≥95th percentile for hospital LOS and ICU LOS, since drive distance and time were significantly associated with these outcomes. None of the interactions were significant, indicating that the effect of GEMS versus HEMS was not significantly different by drive distance or time. We also examined the urban/rural status of the county where transport was initiated to determine if this had a significant effect on transport mode. We found that 2395 (16.6%) of children were transported from a rural county. HEMS transport was used more frequently for children in rural counties than children in urban counties (44.7% versus 23.8%, p b 0.001). Children in rural counties also had longer transportation distances compared to children in urban counties (median distance 96.5 miles versus 18.4 miles, p b 0.001). We attempted to test whether children transported from rural places were more likely to be transported by HEMS compared to children being transported from urban places independent of other variables using an adjusted multivariate logistic regression model. However, the model would not converge because urban/rural status and transport distance were highly collinear. 3. Discussion In this study we compared outcomes of pediatric trauma patients based on their transportation via either HEMS or GEMS to a level 1 pediatric trauma center. This multi-center study is the largest of its kind, and one of very few studies to address this issue. Previous studies of smaller pediatric trauma cohorts used TRISS analysis of expected outcomes, and showed improved survival for HEMS with W-statistics ranging from 1.1 to 5.0 (the magnitude of the survival difference from that predicted per 100 patients treated) [10,11]. A study using the national trauma data bank also showed improved survival for pediatric patients with traumatic brain injuries who were transported by HEMS [12]. In this study we were able to more directly compare these two transportation modes to investigate a range of traumatic injuries. We approached this work with the assumption that transport mode is selected based primarily on two factors — injury severity and the distance/time for travel. Our data allowed for injury severity to be accounted for in a variety of ways, including GCS, vital signs at the time of transport, intubation status, and ISS. Interestingly, we found that 862 children (22.3%) transported by HEMS had an ISS b 10 and a hospital LOS ≤ 1 day. This suggests that poor resource utilization is common, and corroborates several previous studies demonstrating that HEMS is often used for children with minor injuries [11,13,14]. The second factor, distance and time for travel, was more difficult to address. These variables are missing from a large number of subjects in trauma registries [15]. Since we knew the initial and final locations for each child included in our study, we used a geocoding service to estimate these values so that they could be included in the analysis. We then performed statistical analysis using three different versions of our multivariate models, varying the adjustment for distance and time travelled. In the first version, we did not adjust for distance or time travelled. The results of this analysis were thought to represent differences between HEMS and GEMS including speed and/or something intrinsic to the transport mode itself, such as ability to provide care. In the second version, we adjusted for drive distance and time, regardless of which transport mode was actually used. The results of this analysis were thought to represent differences between HEMS and GEMS based on speed of transportation. In the third and final version, we adjusted for travel distance and time. For children who were transported by HEMS, this adjusted for Euclidean distance and flight time, and for children who were transported by GEMS, this adjusted for drive distance and drive time. The results of this analysis were thought to represent differences between HEMS and GEMS relating to factors intrinsic to the transport mode itself, but not differences related to speed. When examining all children in our data set, there were no differences in survival, ICU LOS, or discharge
Please cite this article as: Stewart CL, et al, Helicopter versus ground emergency medical services for the transportation of traumatically injured children, J Pediatr Surg (2014), http://dx.doi.org/10.1016/j.jpedsurg.2014.09.040
C.L. Stewart et al. / Journal of Pediatric Surgery xxx (2014) xxx–xxx
disposition identified between HEMS and GEMS in any of the regression model versions we tested. GEMS, however, was consistently associated with a shorter hospital LOS, ranging from 53.1% to 68.6% shorter stay compared to HEMS. To ensure that we could detect a potential benefit of HEMS at extreme distances and travel times, we also tested for interactions with transport type comparing subjects in the upper 5%–25% for these variables. No significant interactions were found. While factors related to injury severity were known and adjusted for in the multivariate regression analysis, the retrospective nature of our study produced a significant distortion of the data, as seen in Fig. 1. The 25th percentile of ISS for HEMS was approximately the same as the 75th percentile for GEMS, with limited over-lap. Further, the vast majority (78.6%) of children in our study were not severely injured. There were 2987 children with an ISS N 15, and only 1097 with an ISS N24, at which point the risk of fatality significantly increases [16]. Thus, we were concerned that our initial analyses may have been insufficient to completely adjust for injury severity. We attempted to improve our adjustment for injury severity in two ways. First, we performed additional analysis on subset of subjects with an ISS N15, a method that has been used in multiple adult studies [3]. We again found that GEMS was consistently associated with a shorter hospital LOS. We also found that GEMS may be associated with decreased ICU LOS, and improved odds of being discharged home without services. Second, we used propensity score matching based on ISS and GCS. This method has been used in other studies [12], and was developed for observational studies in which subjects are more likely to be assigned to a certain treatment based on a variable related to outcome [17]. This method eliminated nearly all associations of outcome with transport type. The one exception was in models that did not include distance or time adjustment, in which GEMS continued to be associated with a decreased hospital LOS. Taken together, our results do not support our original hypothesis. HEMS transportation does not appear to independently improve outcomes including survival, hospital LOS, ICU LOS, or discharge disposition for traumatically injured children. Our results suggest that the decreased speed of GEMS is not enough to negatively affect these outcomes. Further, since GEMS is slower than HEMS, this implies that superior care may be provided to traumatically injured children who are transported by GEMS. Few studies directly compare care delivered to patients while being transported by HEMS or GEMS. It is, however, expected that differences exist because of differing levels of crew experience. In the United States, HEMS paramedics require a minimum of 3 years experience in advanced life support, and respiratory therapists require 3 years of clinical experience. By comparison, both basic and advanced life support emergency medical technicians work on GEMS, and no pre-requisite experience is required for GEMS crews [18]. It has been suggested that HEMS crews are better suited to care for trauma patients because of their increased experience and advanced airway management skills [19]. Studies comparing the pre-hospital care philosophies of “stay and stabilize” versus “scoop and run” may, however, demonstrate the opposite. Liberman et al. compared cities in Canada with different GEMS crew compositions and found that treatment by advanced life support staff with a “stay and stabilize” approach increased the odds of mortality by 21% compared basic life support staff which used a “scoop and run” methodology [20]. Further, on-scene times are increased for HEMS compared to GEMS transports, likely because more interventions are being made in the pre-hospital setting [21,22]. It has been reported that HEMS crews are more likely to intubate patients and give more fluids compared to GEMS, but these additional interventions do not improve survival or neurologic outcome [21]. Other studies have suggested that these types of pre-hospital interventions may result in harm. It has been reported that pre-hospital and early intravenous fluid administration negatively affects outcomes in severely injured adults [23–25]. Pediatric endotracheal intubation can be a difficult skill to acquire and maintain, since children require this intervention less frequently than adults. A
5
randomized controlled trial comparing pre-hospital pediatric endotracheal intubation to bag valve mask ventilation showed no difference in survival or neurologic outcome [26]. In this same study, 43% of intubation attempts were unsuccessful [26]. Another study showed that children in need of immediate airway intervention had high rates of intubation related complications, the majority of which were related to field intubation attempts [27]. These complications were associated with transport delays and longer hospital LOS [27]. Thus, it may be that HEMS were not associated with improved outcomes in this study because the time benefit was lost by increased on scene times, or that HEMS crews were in some cases performing unnecessary interventions. Further study regarding these factors in the transport of pediatric trauma patients is needed. Another reason we have may have seen decreased hospital LOS with GEMS transports is because GEMS were often used for shorter transports. In our study, 69% of GEMS transports were less than 30 miles, as compared to only 30% of HEMS transports. We also found that HEMS were used more often for transports from rural counties. GEMS patients’ homes may have been closer to the hospital, with guardians likely present soon after the child’s arrival. These factors could have simplified and possibly expedited the discharge process. Delayed discharge has been reported to affect more than 20% of adult trauma admits, and is not associated with injury severity [28,29]. Social and systems related issues were some of the problems cited as causes for delayed discharge [28]. In our study the median hospital LOS was one day for GEMS transports, compared to two days for HEMS transports. Some children transported by HEMS with minor injuries may have been hospitalized a day longer than children transported by GEMS simply because their trip home was longer and was better started in the morning. This is a non-modifiable factor, however, it would again suggest that these children did not initially require the additional speed and expertise that HEMS offers. 4. Conclusions Based on these results, we recommend careful consideration prior to utilization of HEMS for the transport of traumatically injured children. Since we did not observe an improvement in outcomes for traumatically injured children transported by HEMS, we suggest using GEMS for the majority of these children. This is barring situations where HEMS are the only practical method for transportation. An example of this is in rural areas, where the number of GEMS units is limited, and taking an ambulance out of service for a prolonged period could pose a danger to the community should it be needed during that transport. This may explain the higher rate of HEMS use from rural counties. Overall, however, we believe that resource stewardship mandates increased use of GEMS for pediatric trauma patients since no demonstrable benefit from HEMS could be shown. Funding This study was jointly funded by the Divisions of Pediatric Surgery at Children’s Hospital Colorado and Primary Children’s Hospital. Acknowledgments We gratefully acknowledge Phoebe B. McNeally, Ph.D., from the DIGIT lab at the University of Utah, for performing the geocoding work on this study. We also thank Lucinda Giblin for her assistance with the trauma registry at Children’s Hospital Colorado. References [1] Delgado MK, Staudenmayer KL, Wang NE, et al. Cost-effectiveness of helicopter versus ground emergency medical services for trauma scene transport in the United States. Ann Emerg Med 2013;62:351–64.
Please cite this article as: Stewart CL, et al, Helicopter versus ground emergency medical services for the transportation of traumatically injured children, J Pediatr Surg (2014), http://dx.doi.org/10.1016/j.jpedsurg.2014.09.040
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[2] Taylor C, Jan S, Curtis K, et al. The cost-effectiveness of physician staffed Helicopter Emergency Medical Service (HEMS) transport to a major trauma centre in NSW, Australia. Injury 2012;43:1843–9. [3] Galvagno Jr SM, Thomas S, Stephens C, et al. Helicopter emergency medical services for adults with major trauma. Cochrane Database Syst Rev 2013;3:1–49 [CD009228]. [4] Branas CC, MacKenzie EJ, Williams JC, et al. Access to trauma centers in the United States. JAMA 2005;293:2626–33. [5] Wang NE, Saynina O, Vogel LD, et al. The effect of trauma center care on pediatric injury mortality in California, 1999 to 2011. J Trauma Acute Care Surg 2013;75: 704–16. [6] Potoka DA, Schall LC, Gardner MJ, et al. Impact of pediatric trauma centers on mortality in a statewide system. J Trauma 2000;49:237–45. [7] American College of Surgeons. Verified trauma centers. last updated 3/24/2014, accessed 5/14/2014 http://www.facs.org/trauma/verified.html. [8] Incidents by age (Table 11), Committee on Trauma, American College of Surgeons. NTDB annual/pediatric report 2013. Chicago, IL: The American College of Surgeons; 2013. [9] Ingram DD, Franco SJ. 2013 NCHS urban–rural classification scheme for counties. Vital Health Stat 2014;166:1–73. [10] Larson JT, Dietrich AM, Abdessalam SF, et al. Effective use of the air ambulance for pediatric trauma. J Trauma 2004;56:89–93. [11] Moront M, Gotschall CS, Eichelberger MR. Helicopter transport of injured children: system effectiveness and triage criteria. J Pediatr Surg 1996;8:1183–8. [12] Missios S, Bekelis K. Transport mode to level I and II trauma centers and survival of pediatric patients with traumatic brain injury. J Neurotrauma 2014;31:1321–8. [13] Eckstein M, Jantos T, Kelly N, et al. Helicopter transport of pediatric trauma patients in an urban emergency medical services system: a critical analysis. J Trauma 2002; 53:340–4. [14] Knofsky M, Burns Jr JB, Chesire D, et al. Pediatric trauma patients are more likely to be discharged from the emergency department after arrival by helicopter emergency medical services. J Trauma Acute Care Surg 2013;74:917–20. [15] Ryb GE, Dischinger P, Cooper C, et al. Does helicopter transport improve outcomes independently of emergency medical system time? J Trauma Acute Care Surg 2013;74:149–54.
[16] Incidents and case fatality rate by injury severity score (Fig. 17), Committee on Trauma, American College of Surgeons. NTDB annual/pediatric report 2013. Chicago, IL: The American College of Surgeons; 2013. [17] Dehejia RH, Wahba S. Propensity score-matching methods for non-experimental causal studies. Rev Econ Stat 2002;84(1):151–61. [18] Commission on Accreditation of Medical Transport Systems. Accreditation standards9th ed. ; 2012. [19] Butler DP, Anwar I, Willett K. Is it the H or the EMS in HEMS that has an impact on trauma patient mortality? A systematic review of the evidence. Emerg Med J 2010; 27:692–701. [20] Liberman M, Mulder D, Lavoie A, et al. Multicenter Canadian study of prehospital trauma care. Ann Surg 2003;237:153–60. [21] Bulger EM, Guffey D, Guyette FX, et al. Impact of prehospital mode of transport after severe injury: a multicenter evaluation from the Resuscitation Outcomes Consortium. J Trauma Acute Care Surg 2012;72:567–73. [22] Ringburg AN, Spanjersberg WR, Frankema SP. Helicopter emergency medical services (HEMS): impact on on-scene times. J Trauma 2007;63:258–62. [23] Sampalis JS, Tamim H, Denis R, et al. Ineffectiveness of on-site intravenous lines: is prehospital time the culprit? J Trauma 1997;43:608–15. [24] Bickell WH, Wall Jr MJ, Pepe PE, et al. Immediate versus delayed fluid resuscitation for hypotensive patients with penetrating torso injuries. N Engl J Med 1994;331:1105–9. [25] Kasotakis G, Sideris A, Yang Y, et al. Aggressive early crystalloid resuscitation adversely affects outcomes in adult blunt trauma patients: an analysis of the Glue Grant database. J Trauma Acute Care Surg 2013;74:1215–21. [26] Gausche M, Lewis RJ, Stratton SJ, et al. Effect of out-of-hospital pediatric endotracheal intubation on survival and neurological outcome: a controlled clinical trial. JAMA 2000;283:783–90. [27] Ehrlich PF, Seidman PS, Atallah O, et al. Endotracheal intubations in rural pediatric trauma patients. J Pediatr Surg 2004;39:1376–80. [28] Brasel KJ, Rasmussen J, Cauley C, et al. Reasons for delayed discharge of trauma patients. J Surg Res 2002;107:223–6. [29] Hwabejire JO, Kaafarani HM, Imam AM, et al. Excessively long hospital stays after trauma are not related to the severity of illness: let's aim to the right target! JAMA Surg 2013;148:956–61.
Please cite this article as: Stewart CL, et al, Helicopter versus ground emergency medical services for the transportation of traumatically injured children, J Pediatr Surg (2014), http://dx.doi.org/10.1016/j.jpedsurg.2014.09.040
Contents lists available at ScienceDirect
Journal of Pediatric Surgery journal homepage: www.elsevier.com/locate/jpedsurg
Helicopter versus ground emergency medical services for the transportation of traumatically injured children Camille L. Stewart a,b,⁎, Ryan R. Metzger c, Laura Pyle d, Joe Darmofal e, Eric Scaife c, Steven L. Moulton a,b a
University of Colorado School of Medicine, Department of Surgery, 12631 E. 17th Ave, C302, Aurora, CO 80045 Children’s Hospital Colorado, Division of Pediatric Surgery, 13123 E. 16th Ave, B232, Aurora, CO 80045 Primary Children's Hospital, Division of Pediatric Surgery, 100 N Mario Capecchi Dr, Suite 2600, Salt Lake City, UT 84113 d University of Colorado School of Medicine, Department of Pediatrics, 13001 E. 17th Place, C290, Aurora, CO 80045 e Children’s Hospital Colorado, Department of Transport & EMS Outreach and Education, 13123 E. 16th Ave, B245, Aurora, CO 80045 b c
a r t i c l e
i n f o
Article history: Received 6 September 2014 Accepted 8 September 2014 Available online xxxx Key words: Helicopter emergency medical services Pediatric trauma Air transport Resource utilization
a b s t r a c t Background: Helicopter emergency medical services (HEMS) are a common mode of transportation for pediatric trauma patients. We hypothesized that HEMS improve outcomes for traumatically injured children compared to ground emergency medical services (GEMS). Methods: We queried trauma registries of two level 1 pediatric trauma centers for children 0–17 years, treated from 2003 to 2013, transported by HEMS or GEMS, with known transport starting location and outcome. A geocoding service estimated travel distance and time. Multivariate regression analyses were performed to adjust for injury severity variables and travel distance/time. Results: We identified 14,405 traumatically injured children; 3870 (26.9%) transported by HEMS and 10,535 (73.1%) transported by GEMS. Transport type was not significantly associated with survival, ICU length of stay, or discharge disposition. Transport by GEMS was associated with a 68.6%–53.1% decrease in hospital length of stay, depending on adjustment for distance/time. Results were similar for children with severe injuries, and with propensity score matched cohorts. Of note, 862/3850 (22.3%) of HEMS transports had an ISS b10 and hospitalization b 1 day. Conclusions: HEMS do not independently improve outcomes for traumatically injured children, and 22.3% of children transported by HEMS are not significantly injured. These factors should be considered when requesting HEMS for transport of traumatically injured children. © 2014 Elsevier Inc. All rights reserved.
Helicopter emergency medical services (HEMS) are often used for the transportation of traumatically injured children. HEMS transport is faster and has a more experienced crew compared to ground emergency medical services (GEMS), but is significantly more expensive [1,2]. As the political and economic climates shift towards price conscious medical consumerism, the value of HEMS needs to be proven. Studies comparing HEMS to GEMS for traumatically injured adults are conflicting [3] , and there are no large-scale or multi-center studies examining this question in pediatric trauma patients. More than 25% of Americans are reliant on HEMS for access to a trauma center in under an hour [4], and treatment at a designated pediatric trauma center decreases mortality for traumatically injured children [5,6]. Thus, we hypothesized that HEMS would improve outcomes compared to GEMS for Abbreviations: HEMS, helicopter emergency medical services; GEMS, ground emergency medical services; LOS, length of stay; GIS, Geographic Information Systems. ⁎ Corresponding author at: University of Colorado School of Medicine, Department of Surgery, 12631 E. 17th Ave, C302, Aurora, CO 80045. Tel.: +1 256 694 1233. E-mail addresses: [email protected] (C.L. Stewart), [email protected] (R.R. Metzger), [email protected] (L. Pyle), [email protected] (J. Darmofal), [email protected] (E. Scaife), [email protected] (S.L. Moulton).
traumatically injured children. To study this, we combined patient data from two level-1 pediatric trauma centers, which are the only level-1 pediatric trauma centers in their respective states [7]. Experience has shown that case fatality rates for children are lower than adults [8], making a survival benefit difficult to detect in this population. For this reason we also compared the effect of HEMS on additional outcomes, including hospital length of stay (LOS), intensive care unit (ICU) LOS, and discharge disposition. 1. Methods After approval from both centers institutional review boards, we queried the trauma registries of two level 1 pediatric trauma centers for children 0–17 years old treated from January 2003 to January 2013, with transportation by either HEMS or GEMS, known transport starting location (either injury scene zip code for those transported directly from the scene, or address of transferring facility for those transported from another facility), and known outcome. Children with burns and those who were dead on arrival were excluded from analysis. A priori selected covariates included in the analysis were transport type, age, gender, trauma type (blunt or penetrating), referral status, Glasgow
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Please cite this article as: Stewart CL, et al, Helicopter versus ground emergency medical services for the transportation of traumatically injured children, J Pediatr Surg (2014), http://dx.doi.org/10.1016/j.jpedsurg.2014.09.040
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C.L. Stewart et al. / Journal of Pediatric Surgery xxx (2014) xxx–xxx
Coma Scale score (GCS), vital signs (including: heart rate (HR), respiratory rate (RR), and systolic blood pressure (SBP)), intubation status, injury severity score (ISS), estimated drive distance and time, and estimated flight distance and time. GCS and vital signs used in the analysis were from the location initiating the transport. The outcomes for comparison were survival, hospital LOS, ICU LOS, and discharge disposition. Discharge disposition was divided into discharge home without services, versus all other living dispositions, here called discharge with services. A geocoding service was used to estimate travel distance and time to the definitive treating hospital via HEMS or GEMS. The urban or rural status of the location initiating transport was determined using the 2013 census-based NCHS Urban–Rural Classification Scheme for Counties [9]. Data were available for all subjects, except where noted otherwise. 1.1. Theory/calculation 1.1.1. Geographic Information Systems estimates The DIGIT Lab at the University of Utah calculated all Geographic Information Systems (GIS) data. Addresses of transferring facilities were geocoded based upon street addresses using the default Esri ArcGIS geocoding service. Addresses that were not automatically matched were hand placed using reference maps and imagery to identify the hospital location. Because the exact location of injury was often unknown, the zip code in which the injury occurred was used to estimate travel distances/times for cases in which the patient was transported directly from the scene. Injury zip codes were matched to the centroid of the zip code geometry using Esri’s zip code data. Driving distances and times were calculated using Esri’s Network Analyst extension and the StreetMap USA network data set. It should be noted that speed limit data on the network road data set might be out of date due to recent increases in speed for some major highways and interstates. This would result in slightly longer travel times than if compared to Google maps. For comparison, the Euclidean distance from each point to its respective destination was also calculated in order to estimate flight distances, and flight times were calculated based on an estimated speed of 125 knots. 1.1.2. Statistical analysis In the first set of analyses, the entire dataset that resulted from the query of the trauma registries was included. However, because the more severely injured children were more likely to have been transported by HEMS, we attempted to account for the resulting bias in favor of GEMS by matching subjects on propensity scores and repeating the analysis in the matched dataset. Propensity scores for GEMS transport were based on a logistic model with GEMS transport as the outcome and GCS and ISS as predictors. In both the unmatched and matched analyses, nonparametric statistics were computed because most variables were not normally distributed. In the unmatched analyses, univariate analyses utilized logistic regression, linear regression, or the Kruskal Wallis test. In unmatched multivariate analyses, linear regression and logistic models were used. In the matched analyses, linear regression adjusted for propensity score, or mixed models with a propensity score random effect were used to account for matching. In all multivariate analyses, hospital LOS and ICU LOS were log-transformed (with 0.00001 added to any zero values before taking the log). Three versions of the multivariate models were tested. In the first version of the models, no adjustments for time or distance were made. In the second version, the models were adjusted for drive distance and time regardless of the transport type used for the patient. In the third and final version, the models were adjusted for travel distance and time (using drive distance/time for GEMS cases, and using Euclidean distance/flight time for HEMS cases). Chi-square and Kruskal–Wallis tests were used to determine differences between children transported from urban and rural counties.
Statistical differences were considered significant if the probability of a type I error was b5% (p b 0.05). All analyses were performed using SAS version 9.3.
2. Results 2.1. Demographics We identified 14,405 children who met inclusion criteria for our study; a total of 3870 (26.9%) children were transported by HEMS and 10,535 (73.1%) were transported by GEMS. Descriptive statistics are reported in Table 1. The majority of children identified were young males with blunt injuries, normal vital signs, and minimal to moderate injury severity, who traveled less than 30 miles from the injury scene or referring facility. Of note, 862 children (22.3%) transported by HEMS had an ISS b10 and a hospital LOS ≤ 1 day. The initial data set had a disproportionate number of HEMS subjects with higher ISS scores (p b 0.001, Fig. 1), so we also evaluated a subgroup of children with an ISS N15 (Table 2, n = 2987), and a smaller subgroup of propensity score Table 1 Descriptive statistics of all children identified. Category
Gender (n missing = 1) Female Male Age (years) Very young (0–5) Young (6–14) Teenager (15–17) Trauma Type (n missing = 41) Blunt Penetrating Referral status No referral Clinic referral Hospital referral Injury Severity Score category (n missing = 95) Minimal to moderate (0–15) Major (16–24) Severe (N24) GCS (n missing = 3904) GCS = 15 GCS = 3–14 Age adjusted HR (n missing = 3816) Normal/Low High RR (n missing = 2817) Low b9 Normal/High ≥9 SBP (n missing = 5320) Hypotensive ≤ 80 Normotensive N80 Outcome Alive Dead Discharge disposition Discharged home without services Discharged with services Transferred N30 driving miles No Yes Hospital LOS ≤1 day and ISS b 10 (n missing = 95) No Yes
Transport type GEMS (N = 10,535)
HEMS (N = 3870)
N
N
%
%
Total (N = 14,405)
N
%
3724 35.35 1401 36.20 6811 64.65 2468 63.77
5125 35.58 9279 64.42
4728 44.88 1763 45.56 5037 47.81 1833 47.36 770 7.31 274 7.08
6491 45.06 6870 47.69 1044 7.25
10,257 97.36 3744 96.74 14,001 97.20 260 2.47 103 2.66 363 2.52 2498 23.71 1107 28.60 3605 25.03 433 4.11 52 1.34 485 3.37 7604 72.18 2711 70.05 10,315 71.61
9177 87.11 2146 55.45 11,323 78.60 969 9.20 921 23.80 1890 13.12 314 2.98 783 20.23 1097 7.62 6804 64.58 1701 43.95 744 7.06 1252 32.35
8505 59.04 1996 13.86
6739 63.97 2332 60.26 963 9.14 555 14.34
9071 62.97 1518 10.54
83 0.79 225 5.81 308 2.14 8448 80.19 2832 73.18 11,280 78.31 104 0.99 192 4.96 6120 58.09 2669 68.97
296 2.05 8789 61.01
10,473 99.41 3634 93.90 14,107 97.93 62 0.59 236 6.10 298 2.07 9849 93.49 3114 80.47 12,963 89.99 624
5.92
520 13.44
1144
7.94
7237 68.69 1162 30.03 3298 31.31 2708 69.97
8399 58.31 6006 41.69
4105 38.97 2988 77.21 6355 60.32 862 22.27
7093 49.24 7217 50.10
Please cite this article as: Stewart CL, et al, Helicopter versus ground emergency medical services for the transportation of traumatically injured children, J Pediatr Surg (2014), http://dx.doi.org/10.1016/j.jpedsurg.2014.09.040
C.L. Stewart et al. / Journal of Pediatric Surgery xxx (2014) xxx–xxx
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Table 3 Descriptive statistics of propensity score matched children. Category
Fig. 1. Box plot of injury severity score versus transport mode.
matched children based on GCS and ISS to further improve adjustment for injury severity (Table 3, n = 1446). To determine if there were outcome differences between HEMS and GEMS, we compared survival, hospital LOS, ICU LOS, and discharge disposition using multivariate regression analyses of these three data sets. Each data set was subject to three separate analyses that differed based on the adjustment for time and distance traveled. The first analysis was calculated without Table 2 Descriptive statistics of children with an injury severity score greater than 15. Transport
Gender Female Male Age Very young (0–5 years) Young (6–14 years) Teenager (15–17 years) Trauma Type (n missing = 16) Blunt Penetrating Referral status No referral Clinic referral Hospital referral ISS Major (16–24) Severe (N24) GCS (n missing = 747) GCS = 15 GCS = 3–14 Age Adjusted HR (n missing = 747) Normal/Low High RR (n missing = 634) Low b9 Normal/High ≥9 SBP (n missing = 991) Hypotensive ≤80 Normotensive N80 Outcome Alive Dead Discharge disposition Discharged home without services Discharged with services Transferred N30 driving miles No Yes
Total (N = 2987)
GEMS (N = 1283)
HEMS (N = 1704)
N
%
N
%
N
%
466 817
36.32 63.68
607 1097
35.62 64.38
1073 1914
35.92 64.08
692 510 81
53.94 39.75 6.31
793 794 117
46.54 46.60 6.87
1485 1304 198
49.72 43.66 6.63
1276 6
99.45 0.47
1661 28
97.48 1.64
2937 34
98.33 1.14
347 34 902
27.05 2.65 70.30
358 12 1334
21.01 0.70 78.29
705 46 2236
23.60 1.54 74.86
969 314
75.53 24.47
921 783
54.05 45.95
1890 1097
63.27 36.73
689 230
53.70 17.93
556 765
32.63 44.89
1245 995
41.68 33.31
802 147
62.51 11.46
1008 283
59.15 16.61
1810 430
60.60 14.40
56 990
4.36 77.16
196 1111
11.50 65.20
252 2101
8.44 70.34
46 686
3.59 53.47
152 1112
8.92 65.26
198 1798
6.63 60.19
1228 55
95.71 4.29
1481 223
86.91 13.09
2709 278
90.69 9.31
1024 204
79.81 15.90
1089 392
63.91 23.00
2113 596
70.74 19.95
848 435
66.10 33.90
488 1216
28.64 71.36
1336 1651
44.73 55.27
Gender Female Male Age Very young (0–5 years) Young (6–14 years) Teenager (15–17 years) Trauma Type (n missing = 7) Blunt Penetrating Referral status No referral Clinic referral Hospital referral ISS Minimal to moderate (0–15) Major (16–24) Severe (N24) GCS GCS = 15 GCS = 3–14 Age Adjusted HR (n missing = 208) Normal/Low High RR (n missing = 122) Low b9 Normal/High ≥9 SBP (n missing = 329) Hypotensive ≤80 Normotensive N80 Outcome Alive Dead Discharge disposition Discharged home without services Discharged with services Transferred N30 driving miles No Yes
Transport type
Total (N = 1446)
GEMS (N = 667)
HEMS (N = 779)
N
%
N
%
244 423
36.58 63.42
272 507
34.92 65.08
516 930
35.68 64.32
300 314 53
44.98 47.08 7.95
328 386 65
42.11 49.55 8.34
628 700 118
43.43 48.41 8.16
658 7
98.65 1.05
763 11
97.95 1.41
1421 18
98.27 1.24
216 11 440
32.38 1.65 65.97
199 3 577
25.55 0.39 74.07
415 14 1017
28.70 0.97 70.33
324 204 139
48.58 30.58 20.84
158 278 343
20.28 35.69 44.03
482 482 482
33.33 33.33 33.33
428 239
64.17 35.83
295 484
37.87 62.13
723 723
50.00 50.00
486 90
72.86 13.49
517 145
66.37 18.61
1003 235
69.36 16.25
22 617
3.30 92.50
88 597
11.30 76.64
110 1214
7.61 83.96
18 443
2.70 66.42
62 594
7.96 76.25
80 1037
5.53 71.72
650 17
97.45 2.55
697 82
89.47 10.53
1347 99
93.15 6.85
569 81
85.31 12.14
557 140
71.50 17.97
1126 221
77.87 15.28
454 213
68.07 31.93
229 550
29.40 70.60
683 763
47.23 52.77
N
%
adjustment for travel distance or time. The second analysis adjusted for drive distance and time, regardless if HEMS or GEMS was used for transportation. The third and final analysis adjusted for travel distance and time calculated based on whether HEMS or GEMS was utilized (flight estimates or driving estimates, respectively). 2.2. Analysis without adjusting for travel distances or times Multivariate regression analysis of the entire data set revealed that survival, ICU LOS, and discharge disposition were not significantly associated with transport type. Hospital LOS, however, was significantly associated with transport type (p b 0.001). Age (p b 0.001), GCS (p b 0.001), HR (p = 0.001), RR (p b 0.001), SBP (p b 0.001), and ISS (p b 0.001) were also independently associated with hospital LOS. Compared to HEMS, transport by GEMS was associated with a 68.6% decrease in hospital LOS. Multivariate regression analysis of the subset of children with an ISS N15 revealed that survival was not significantly associated with transport type. Hospital LOS was significantly associated with transport type (p b 0.001), in addition to age (p = 0.002), GCS (p = 0.001), HR (p b 0.001), RR (p b 0.001), and SBP (p b 0.001). Compared to HEMS, transport by GEMS was associated with a 61.0% decrease in hospital LOS. ICU LOS was also significantly associated with transport type (p = 0.05), in addition to referral status (p = 0.002), GCS (p b 0.001), HR (p = 0.002), RR (p = 0.003), and SBP (p = 0.001). Transport by
Please cite this article as: Stewart CL, et al, Helicopter versus ground emergency medical services for the transportation of traumatically injured children, J Pediatr Surg (2014), http://dx.doi.org/10.1016/j.jpedsurg.2014.09.040
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GEMS was associated with a 13.6% decrease in ICU LOS compared to HEMS. Discharge disposition was also significantly associated with transport type (p = 0.02) and GCS (p b 0.0001). The odds of being discharged with services were significantly lower when transported by GEMS compared to HEMS (OR 0.64, 95% CI 0.45–0.92). Multivariate regression analysis of the propensity score matched data set revealed that survival, ICU LOS, and discharge disposition were not significantly associated with transport type. Hospital LOS was significantly associated with transport type (p = 0.01), in addition to referral status (p = 0.02), HR (p = 0.02), RR (p = 0.02), and SBP (p = 0.05). Compared to HEMS, transport by GEMS was associated with a 44.9% decrease in hospital LOS. 2.3. Analysis using drive distances and times Multivariate regression analysis of the entire data set, and using only driving estimates, showed that survival, ICU LOS, and discharge disposition were not significantly associated with transport type. Hospital LOS was significantly associated with transport type (p b 0.001), as well as age (p = 0.001), referral status (p b 0.001), GCS (p b 0.001), HR (p = 0.001), RR (p = 0.002), SBP (p b 0.001), ISS (p b 0.001), estimated drive distance (p b 0.001), and estimated drive time (p b 0.001). GEMS transport was associated with a 53.1% reduction in the hospital LOS compared to HEMS. Multivariate regression analysis of the subset of children with an ISS N 15 showed that survival and ICU LOS were not significantly associated with transport type. Hospital LOS was significantly associated with transport type (p b 0.001), in addition to age (p = 0.002), GCS (p = 0.001), HR (p b 0.001), RR (p b 0.001), and SBP (p b 0.001). Transport by GEMS was associated with a 59.7% reduction in the hospital LOS compared to HEMS. Discharge disposition was significantly associated with transport type (p = 0.02) and GCS (p b 0.001). The odds of being discharged with services were significantly lower when transported by GEMS compared to HEMS (OR 0.66, 95% CI 0.45–0.95). Multivariate regression analysis of the propensity score matched data set revealed that survival, hospital LOS, ICU LOS and discharge disposition were not significantly associated with transport type. 2.4. Analysis using travel distances and times Multivariate regression analysis of the entire data set using travel distances/times corresponding to the transport type utilized for each case revealed that survival, ICU LOS, and discharge disposition were not significantly associated with transport type. Hospital LOS was significantly associated with transport type (p b 0.001), in addition to age (p b 0.001), referral status (p = 0.005), GCS (p b 0.001), HR (p = 0.001), RR (p = 0.002), SBP (p b 0.001), ISS (p b 0.001), and travel distance (p = 0.04). Transport by GEMS was associated with a 65.3% decrease in hospital LOS compared to HEMS. Multivariate regression analysis of the subset of children with an ISS N 15 revealed that survival, ICU LOS, and discharge disposition were not significantly associated with transport type. Hospital LOS was significantly associated with transport type, in addition to age (p = 0.002), GCS (p = 0.001), HR (p b 0.001), RR (p b 0.001), and SBP (p b 0.001). Transport by GEMS was associated with a 61.4% decrease hospital LOS compared to HEMS. Multivariate regression analysis of the propensity score matched data set revealed that survival, hospital LOS, ICU LOS and discharge disposition were not significantly associated with transport type. 2.5. Additional analysis In order to determine whether there was any benefit derived from HEMS at greater drive distances or times, the interaction of transport type was tested with drive distances and times categorized as b 75th percentile versus ≥ 75th percentile, b90th percentile versus ≥ 90th
percentile, and b 95th percentile versus ≥95th percentile for hospital LOS and ICU LOS, since drive distance and time were significantly associated with these outcomes. None of the interactions were significant, indicating that the effect of GEMS versus HEMS was not significantly different by drive distance or time. We also examined the urban/rural status of the county where transport was initiated to determine if this had a significant effect on transport mode. We found that 2395 (16.6%) of children were transported from a rural county. HEMS transport was used more frequently for children in rural counties than children in urban counties (44.7% versus 23.8%, p b 0.001). Children in rural counties also had longer transportation distances compared to children in urban counties (median distance 96.5 miles versus 18.4 miles, p b 0.001). We attempted to test whether children transported from rural places were more likely to be transported by HEMS compared to children being transported from urban places independent of other variables using an adjusted multivariate logistic regression model. However, the model would not converge because urban/rural status and transport distance were highly collinear. 3. Discussion In this study we compared outcomes of pediatric trauma patients based on their transportation via either HEMS or GEMS to a level 1 pediatric trauma center. This multi-center study is the largest of its kind, and one of very few studies to address this issue. Previous studies of smaller pediatric trauma cohorts used TRISS analysis of expected outcomes, and showed improved survival for HEMS with W-statistics ranging from 1.1 to 5.0 (the magnitude of the survival difference from that predicted per 100 patients treated) [10,11]. A study using the national trauma data bank also showed improved survival for pediatric patients with traumatic brain injuries who were transported by HEMS [12]. In this study we were able to more directly compare these two transportation modes to investigate a range of traumatic injuries. We approached this work with the assumption that transport mode is selected based primarily on two factors — injury severity and the distance/time for travel. Our data allowed for injury severity to be accounted for in a variety of ways, including GCS, vital signs at the time of transport, intubation status, and ISS. Interestingly, we found that 862 children (22.3%) transported by HEMS had an ISS b 10 and a hospital LOS ≤ 1 day. This suggests that poor resource utilization is common, and corroborates several previous studies demonstrating that HEMS is often used for children with minor injuries [11,13,14]. The second factor, distance and time for travel, was more difficult to address. These variables are missing from a large number of subjects in trauma registries [15]. Since we knew the initial and final locations for each child included in our study, we used a geocoding service to estimate these values so that they could be included in the analysis. We then performed statistical analysis using three different versions of our multivariate models, varying the adjustment for distance and time travelled. In the first version, we did not adjust for distance or time travelled. The results of this analysis were thought to represent differences between HEMS and GEMS including speed and/or something intrinsic to the transport mode itself, such as ability to provide care. In the second version, we adjusted for drive distance and time, regardless of which transport mode was actually used. The results of this analysis were thought to represent differences between HEMS and GEMS based on speed of transportation. In the third and final version, we adjusted for travel distance and time. For children who were transported by HEMS, this adjusted for Euclidean distance and flight time, and for children who were transported by GEMS, this adjusted for drive distance and drive time. The results of this analysis were thought to represent differences between HEMS and GEMS relating to factors intrinsic to the transport mode itself, but not differences related to speed. When examining all children in our data set, there were no differences in survival, ICU LOS, or discharge
Please cite this article as: Stewart CL, et al, Helicopter versus ground emergency medical services for the transportation of traumatically injured children, J Pediatr Surg (2014), http://dx.doi.org/10.1016/j.jpedsurg.2014.09.040
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disposition identified between HEMS and GEMS in any of the regression model versions we tested. GEMS, however, was consistently associated with a shorter hospital LOS, ranging from 53.1% to 68.6% shorter stay compared to HEMS. To ensure that we could detect a potential benefit of HEMS at extreme distances and travel times, we also tested for interactions with transport type comparing subjects in the upper 5%–25% for these variables. No significant interactions were found. While factors related to injury severity were known and adjusted for in the multivariate regression analysis, the retrospective nature of our study produced a significant distortion of the data, as seen in Fig. 1. The 25th percentile of ISS for HEMS was approximately the same as the 75th percentile for GEMS, with limited over-lap. Further, the vast majority (78.6%) of children in our study were not severely injured. There were 2987 children with an ISS N 15, and only 1097 with an ISS N24, at which point the risk of fatality significantly increases [16]. Thus, we were concerned that our initial analyses may have been insufficient to completely adjust for injury severity. We attempted to improve our adjustment for injury severity in two ways. First, we performed additional analysis on subset of subjects with an ISS N15, a method that has been used in multiple adult studies [3]. We again found that GEMS was consistently associated with a shorter hospital LOS. We also found that GEMS may be associated with decreased ICU LOS, and improved odds of being discharged home without services. Second, we used propensity score matching based on ISS and GCS. This method has been used in other studies [12], and was developed for observational studies in which subjects are more likely to be assigned to a certain treatment based on a variable related to outcome [17]. This method eliminated nearly all associations of outcome with transport type. The one exception was in models that did not include distance or time adjustment, in which GEMS continued to be associated with a decreased hospital LOS. Taken together, our results do not support our original hypothesis. HEMS transportation does not appear to independently improve outcomes including survival, hospital LOS, ICU LOS, or discharge disposition for traumatically injured children. Our results suggest that the decreased speed of GEMS is not enough to negatively affect these outcomes. Further, since GEMS is slower than HEMS, this implies that superior care may be provided to traumatically injured children who are transported by GEMS. Few studies directly compare care delivered to patients while being transported by HEMS or GEMS. It is, however, expected that differences exist because of differing levels of crew experience. In the United States, HEMS paramedics require a minimum of 3 years experience in advanced life support, and respiratory therapists require 3 years of clinical experience. By comparison, both basic and advanced life support emergency medical technicians work on GEMS, and no pre-requisite experience is required for GEMS crews [18]. It has been suggested that HEMS crews are better suited to care for trauma patients because of their increased experience and advanced airway management skills [19]. Studies comparing the pre-hospital care philosophies of “stay and stabilize” versus “scoop and run” may, however, demonstrate the opposite. Liberman et al. compared cities in Canada with different GEMS crew compositions and found that treatment by advanced life support staff with a “stay and stabilize” approach increased the odds of mortality by 21% compared basic life support staff which used a “scoop and run” methodology [20]. Further, on-scene times are increased for HEMS compared to GEMS transports, likely because more interventions are being made in the pre-hospital setting [21,22]. It has been reported that HEMS crews are more likely to intubate patients and give more fluids compared to GEMS, but these additional interventions do not improve survival or neurologic outcome [21]. Other studies have suggested that these types of pre-hospital interventions may result in harm. It has been reported that pre-hospital and early intravenous fluid administration negatively affects outcomes in severely injured adults [23–25]. Pediatric endotracheal intubation can be a difficult skill to acquire and maintain, since children require this intervention less frequently than adults. A
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randomized controlled trial comparing pre-hospital pediatric endotracheal intubation to bag valve mask ventilation showed no difference in survival or neurologic outcome [26]. In this same study, 43% of intubation attempts were unsuccessful [26]. Another study showed that children in need of immediate airway intervention had high rates of intubation related complications, the majority of which were related to field intubation attempts [27]. These complications were associated with transport delays and longer hospital LOS [27]. Thus, it may be that HEMS were not associated with improved outcomes in this study because the time benefit was lost by increased on scene times, or that HEMS crews were in some cases performing unnecessary interventions. Further study regarding these factors in the transport of pediatric trauma patients is needed. Another reason we have may have seen decreased hospital LOS with GEMS transports is because GEMS were often used for shorter transports. In our study, 69% of GEMS transports were less than 30 miles, as compared to only 30% of HEMS transports. We also found that HEMS were used more often for transports from rural counties. GEMS patients’ homes may have been closer to the hospital, with guardians likely present soon after the child’s arrival. These factors could have simplified and possibly expedited the discharge process. Delayed discharge has been reported to affect more than 20% of adult trauma admits, and is not associated with injury severity [28,29]. Social and systems related issues were some of the problems cited as causes for delayed discharge [28]. In our study the median hospital LOS was one day for GEMS transports, compared to two days for HEMS transports. Some children transported by HEMS with minor injuries may have been hospitalized a day longer than children transported by GEMS simply because their trip home was longer and was better started in the morning. This is a non-modifiable factor, however, it would again suggest that these children did not initially require the additional speed and expertise that HEMS offers. 4. Conclusions Based on these results, we recommend careful consideration prior to utilization of HEMS for the transport of traumatically injured children. Since we did not observe an improvement in outcomes for traumatically injured children transported by HEMS, we suggest using GEMS for the majority of these children. This is barring situations where HEMS are the only practical method for transportation. An example of this is in rural areas, where the number of GEMS units is limited, and taking an ambulance out of service for a prolonged period could pose a danger to the community should it be needed during that transport. This may explain the higher rate of HEMS use from rural counties. Overall, however, we believe that resource stewardship mandates increased use of GEMS for pediatric trauma patients since no demonstrable benefit from HEMS could be shown. Funding This study was jointly funded by the Divisions of Pediatric Surgery at Children’s Hospital Colorado and Primary Children’s Hospital. Acknowledgments We gratefully acknowledge Phoebe B. McNeally, Ph.D., from the DIGIT lab at the University of Utah, for performing the geocoding work on this study. We also thank Lucinda Giblin for her assistance with the trauma registry at Children’s Hospital Colorado. References [1] Delgado MK, Staudenmayer KL, Wang NE, et al. Cost-effectiveness of helicopter versus ground emergency medical services for trauma scene transport in the United States. Ann Emerg Med 2013;62:351–64.
Please cite this article as: Stewart CL, et al, Helicopter versus ground emergency medical services for the transportation of traumatically injured children, J Pediatr Surg (2014), http://dx.doi.org/10.1016/j.jpedsurg.2014.09.040
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