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American Journal of Emergency Medicine

journal homepage: www. elsevier. com/ locate/ajem

Simple Triage Algorithm and Rapid treatment and Sort, Assess, Lifesaving, Interventions, Treatment, and Transportation mass casualty triage methods for sensitivity, specificity, and

predictive values?,??

Mary Colleen Bhalla, MD ^a,b,?, Jennifer Frey, PhD ^a, Cody Rider, DO ^a,

Michael Nord, DO ^a, Mitch Hegerhorst, DO ^a,c,1

^a Summa Akron City Hospital, Akron, OH

^b Northeast Ohio Medical University, Rootstown, OH 44272

^c Kadlec Medical Center, Richland, WA 99352

a r t i c l e i n f o

Article history:

Received 16 June 2015

Received in revised form 28 July 2015

Accepted 11 August 2015

a b s t r a c t

Objective: Two common mass casualty triage algorithms are Simple Triage Algorithm and Rapid Treatment (START) and Sort, Assess, Lifesaving, Interventions, Treatment, and Transportation (SALT). We sought to deter- mine the START and SALT efficacy in predicting clinical outcome by appropriate triage.

Methods: We performed a retrospective chart review of trauma Registry of patients from our emergency depart-

ment (ED). We applied the triage algorithms to 100 patient charts.

The end points categories were defined by patient outcomes and the need for intervention: minor/green, discharged without intervention other than minor ED procedure; delayed/yellow, patients get an intervention more than 12 hours after arrival to the ED; immediate/red, patients get an intervention less than 12 hours after arrival; dead/expectant/black, patients die within 48 hours after arrival.

Results: The mean age was 47 years (range, 17-92 years), and 72% were male. The mechanism of injury was 41% motor vehicle collision, 32% fall, and 16% penetrating trauma. Hospital outcome was 60% minor/green, 5% de- layed/yellow, 29% immediate/red, and 6% dead/black. The SALT method resulted in 5 patients overtriaged (95% confidence interval [CI], 1.6-11.2), 30 undertriaged (95% CI, 21.2-40), and 65 met triage level (95% CI, 54.8-

74.3). The START method resulted in 12 overtriage (95% CI, 6.4-20), 33 undertriaged (95% CI, 23.9-43.1), and

55 at triage level (95% CI, 44.7-65). Within triage levels, sensitivity ranged from 0% to 92%, specificity from 55% to 100%, positive predictive values from 10% to 100%, and negative predictive value from 65% to 97%.

Conclusion: Overall, neither SALT nor START was sensitive or specific for predicting clinical outcome.

(C) 2015

Introduction

Triage is defined as “the sorting of and allocation of treatment to pa- tients and especially battle and disaster victims according to a system of priorities designed to maximize the number of survivors” [1]. Although the word is clearly defined, the process of how to carry out triage is less well defined. As the definition states, “a system of priorities” will be

? No outside funding was provided.

?? Presented as a poster at the Society of Academic Emergency Medicine annual meeting, May 2015.

* Corresponding author at: Department of Emergency Medicine, Summa Akron City Hospital, 525 East Market St, Akron, OH 44304-1619. Tel.: +1 330 375 7530; fax: +1

330 375 7564.

E-mail addresses: [email protected] (M.C. Bhalla), [email protected] (J. Frey), [email protected] (C. Rider), [email protected] (M. Nord), [email protected] (M. Hegerhorst).

¹ Current location, formally with Summa Akron City Hospital.

needed to be applied, but how do we organize this system of priorities and how do we know it is effective? One such system, known as Simple Triage and Rapid Treatment (START) (Fig. 1), has been the standard tri- age algorithm since the 1980s when it was developed [2]. The START al- gorithm is appealing because it applies the same approach of evaluating airway, breathing, and circulation as taught in advanced trauma life support certification. However, there is not a single way to approach triage, and retrospective studies have shown that START is not nearly as sensitive and specific as it claims to be and also has significant overtriage [3]. A second algorithm for triage has more recently been developed, the Sort, Assess, Lifesaving Interventions, Treatment/ Transport algorithm, commonly known as SALT (Fig. 2A and B) [4]. This model has been endorsed by the American College of Emergency Physicians, American Trauma Society, and American College of Sur- geons Committee on Trauma [5]. The SALT model involves initial global sorting as well as basic lifesaving interventions such as controlling hem- orrhage, opening airway/rescue breaths, autoinjector antidotes, and chest compressions.

http://dx.doi.org/10.1016/j.ajem.2015.08.021

0735-6757/(C) 2015

All Walking Wounded Respirations

MINOR _NO

YES

Position Airway

Under 30/min Over 30/min

NO Respirations Respirations IMMEDIATE

DECEASED IMMEDIATE

Present

Over 2

Radial Pulse Absent

Perfusion Radial Pulse

Under 2

seconds

or Capillary Refill

seconds

Mental Status

Control Bleeding

IMMEDIATE

CAN NOT

Follow Commands

CAN

Follow Commands

IMMEDIATE DELAYED

Fig. 1. START triage method.

The nature of mass causality incidents (MCIs) does not allow for ran- domized studies to compare the START and SALT triage algorithms. There is limited literature directly comparing the 2 triage algorithms when applying them to the same patient. One study evaluated the effi- cacy of START triage to predict mortality but did not assess the correla- tion with other outcomes [6]. The goal for this pilot study is to retrospectively apply the START and SALT triage methods to patients presenting to our level I trauma center as surgical or Trauma activations and evaluate the accuracy based on patient outcomes and interventions required. Our hypothesis is that START and SALT triage methods are sensitive and specific and predict clinical outcome.

A

Walk

Assess 3rd

Step 1: SORT

Still / Obvious Life Threat

Assess1st

Wave/Purposeful Movement

Assess 2nd

Methods

Study design

We applied the START and SALT triage algorithms to patient data from our trauma registry to assess the sensitivity and specificity of the algo- rithms. This study was approved by the local institutional review board.

Study setting and population

We performed a retrospective chart review of trauma patients, in 2013, who presented for evaluation at our level I Midwestern trauma center, starting on January 1, 2013. The emergency department (ED) has more than 80000 adult patient visits per year from a large trauma catchment area. We collected data from the first 100 charts with com- plete data available from the first health care encounter either emergen- cy medical service (EMS) or ED, if self-transported. Patients transferred from other hospitals or freestanding EDs were excluded from the study. Our trauma registry is collected as part of our membership in the North- eastern Ohio Regional Trauma Network.

B

Step 2: Assess

Lifesaving Interventions:

• • • Control majorhemorrhage
    • Open airway (if child, consider 2 rescue breaths)
    • chest decompression

Breathing?

Yes

No

Dead

Minimal

Yes

Study protocol

We collected demographic data on age, sex, and trauma mechanism. Mechanism categories were defined as motor vehicle collision, fall, pen- etrating trauma, pedestrian/bicycle struck, and industrial accident.

The START triage (Fig. 1) review included determining from review if patient could walk, which would triage them as green. If unable to walk, respirations reported less than 30 breaths per minute and systolic

• • • Auto injector antidotes
    • Obeys commands or makes purposeful movements?
    • Hasperipheral pulse?
    • Not in respiratory distress?
    • Major hemorrhage is controlled?

Any No

Likely to

All

Yes

Minor injuries only?

No

Delayed

Blood pressure greater than 80 mm Hg (correlating with radial pulse or normal cap refill), and patient was following commands, pa- tient was triaged as yellow. If there is any abnormality in the aforemen- tioned group with respirations, BP, and ability to follow commands, patient was triaged as red. If patient was apneic, they were triaged as black/expectant.

The SALT triage (Fig. 2) breaks triage into 2 steps. Sorting is first, in

Expectant

No

survive given current

resources?

Yes

Immediate

which patients who can walk are assessed last, those who cannot walk but can wave/purposefully respond are assess second, and those patients who are still/unresponsive are immediately seen. Assess and lifesaving treatment is next. Patients are triaged as green if they can obey commands or make purposeful movements, have a peripheral

Fig. 2. A and B, SALT triage method.

pulse, are not in respiratory distress, do not have a hemorrhage, and

Table 1

Triage outcomes

Triage category Clinical features

Minor/green tag Discharged from the ED or hospital without intervention other than minor ED procedure (splint/sling, observation, suture)

Delayed/yellow tag Patients get an intervention (group together:

surgery, blood product transfusion, chest tube, angio procedure) sometime after the first 12 h after arrival to the ED

Immediate/red tag Patients get an intervention (group together:

surgery, blood product transfusion, chest tube, angio procedure) sometime within the first 12 h after arrival to the ED

Fall

32%

Other

10%

Motor Vehicle Collision

41%

Dead/expectant/black tag Patients die within 48 h after arrival to the ED

or have a Cerebral Performance Category Scale of 4 or 5 upon discharge

Pedestrian or Bike

1%

Penetrating Trauma

16%

Fig. 3. Mechanisms of injury.

only present with minor injuries. This obviously required more inter- pretation from the chart. Patients are yellow if they meet all of the green criteria, but injuries are not considered minor. If the answer is no to any of the green criteria and the patient is likely to survive given resources (Hemorrhage control, chest compressions, autoinjector anti- dotes, and opening airway), then the patient is triaged as red.

When reviewing charts, we considered a systolic BP less than 80 mm Hg to be an equivalent finding to absent radial pulse/delayed capillary refill [7]. We considered “minor injuries” to mean minor abrasions or lacerations, contusions, sprains, or strains. We considered documenta- tion of ambulation at scene by EMS as able to walk. The START triage di- vides patients by a respiratory rate less than 30 or greater than 30 breaths per minute. We changed this to less than 30 or 30 or higher breaths per minute. Using information obtained from EMS reports and ED triage notes, patients were triaged using SALT and START criteria, re- spectively. This was often with limited information, as would be expect- ed if one was triaging during a disaster scenario. Two different researchers reviewed the prehospital and ED triage notes, and if a dis- crepancy in the interpretation occurred, it went to a third researcher. The EMS records were used primarily for the triage determination, and the ED triage notes were used if there was missing data or if the pa- tient came in by private vehicle.

Measurements

Our initial triage category was compared with the patients’ eventual hospital outcomes. We designated different levels of treatment received while in the hospital to correspond with different triage categories so there could be a shared variable (Table 1).

Sample size calculation

We collected data on 100 patient encounters for a 95% confidence in- terval (CI) of 10% for SALT and START sensitivity and specificity.

Data analysis

We entered data into REDcap (Nashville, TN) and use STATA statisti- cal software (StataCorp LP, College Station, TX) for analysis. We provide descriptive statistics for demographic data. We present sensitivity, spec- ificity, negative predictive values, and positive predictive values with 95% CIs.

Results

Patient characteristics

The mean age was 47 years (range, 17-92 years), and 72% were male. The most common mechanism of injury was motor vehicle collision (41%) (Table 2; Fig. 3). Both SALT and START triaged more than half of the patients as minor (Fig. 4). Hospital outcome was 60% minor/green, 5% delayed/yellow, 29% immediate/red, and 6% dead/black (Fig. 4).

Main results

The START method resulted in 12 overtriage (95% CI, 6.4-20), 33

undertriaged (95% CI, 23.9-43.1), and 55 at triage level (95% CI, 44.7-

65). The overall sensitivity was 55% (44.7-65), and specificity was 85% (80.4-88.9). The SALT method resulted in 5 patients overtriaged (95% CI, 1.6-11.2), 30 undertriaged (95% CI, 21.2-40), and 65 met triage

level (95% CI, 54.8-74.3). The overall sensitivity was 65% (95% CI, 54.8-

74.2), and specificity was 88.3% (95% CI, 84.1-91.7). Within all triage levels, sensitivity ranged from 0% to 92%; and specificity, from 55% to 100%. The positive predictive values ranged from 10% to 100% and neg- ative predictive value from 65% to 97% (Tables 3 and 4).

Dead or Expectant/Black

Table 2

Results–triage START vs SALT

Immediate/Red

29%

Minor/Green

60%

6%

Fig. 4. Hospital outcomes.

	START	SALT
Minor/green	66%	76%	Delayed/Yellow
Delayed/yellow	22%	10%	5%
Immediate/red	9%	11%
Dead or expectant/black	3%	3%

Table 3 Results START
	Sensitivity (n, 95% CI)	Specificity (n, 95% CI)	Positive predictive value (n, 95% CI)	Negative predictive value (n, 95% CI)
Minor/green	80% (48/60, 67.7-89.2)	55% (22/40, 38.5-70.7)	72.4% (48/66, 60.4-83)	79.2% (22/34, 46.5-80.3)
Delayed/yellow	0% (0/5, 0-52.2)	76.8% (73/95, 67.1-84.9)	0% (0/22, 0-15.4)	93.6% (73/78, 85.7-97.9)
Immediate/red	13.8% (4/29, 3.9-31.7)	93% (66/71, 84.3-97.7)	44.4% (4/9, 13.7-78.8)	72.5% (66/91, 62.2-81.4)
Dead or Expectant/black	50% (3/6, 11.8-88.2)	100% (94/94, 96.2-100)	100% (3/3, 29.2-100)	96.9% (94/97, 91.2-99.4)
Overall	55% (55/100, 44.7-65)	85% (255/300, 80.4-88.9)	NA	NA

Discussion

Both triage algorithms were compared with each patient’s hospital outcome, to approximate the algorithms’ ability to appropriately deter- mine each patient’s need for intervention. Both Triage systems did triage the majority of patients correctly: START 55% and SALT 65%. Although they did have notable specificity, START 85% and SALT 88%, they lacked sensitivity. Both the START and SALT algorithms were noted to have poor sensitivity for appropriately identifying the severity of injury in pa- tients and subsequent need for intervention. The largest inaccuracy of the triage systems’ flaws was in the “red” or critically ill category. Mean- ing, the most severely injured patients who did receive treatment with- in 12 hours of arrival were often not triaged appropriately, of which most were undertriaged. The SALT system was less likely to overtriage, but both would frequently undertriage. The positive and negative pre- dictive values for death were good for START and SALT. Although these triage algorithms did not seem to give promising results, it may be that other systems would do no better in this type of evaluation.

In the ED, we have many tools to guide us in our decision making and ample resources at most times to deal with trauma patients who come in one at a time. Patients are seen immediately upon arrival with the blood bank, radiology, and laboratory already alerted. We can use ultrasound and computed tomographic scan to rapidly identify dangerous conditions. We have serial vital signs and constant nursing supervision for critically ill patients so we can make changes immedi- ately as the need arises.

Of specific concern was the undertriage of both methods. In an MCI, undertriage may mean an underestimation of resources needed and may delay care for some. As MCI are rare events, overtriaging and expecting patients to be more ill and require more resources than they eventually use would not necessarily be excessively taxing on the system. In a system that uses the incident command model, having extra staff or physicians on hand than was absolutely needed can be eas- ily remedied. It may be that neither of these triage methods should be used and instead an alternative triage method should be developed based on further research. A recent study using a trauma database to identify patients who would be triaged with START as green/minor who died found that the accuracy improved by simply making elderly patients yellow [8].

The largest limitation is that this is a retrospective study and infor- mation had to be interpreted from EMS run reports and initial triage notes. First-hand visualization of the patient could not be considered in retrospectively assigning patients through triage. It is possible in the future to design a study in which patients are enrolled as they

enter the ED for trauma evaluation or are enrolled by EMS, but it would require extensive training of providers for accurate data collec- tion. With the advent of prehospital electronic records, it may be possi- ble to build in a research study to their documentation that is triggered by a trauma diagnosis. Enrolling them in this method may still not test the triage methods fully as asking someone who is part of a mass casu- alty event to walk is very different from asking a patient from an isolated traumatic incidence to walk.

The study is also limited by its sample size and demographic. The large majority of the patients (41%) were blunt trauma (motor vehicle crash) mechanisms, which may not accurately represent patients need- ing triaged after a mass casualty event such as a large explosion with primary to quaternary blast type injuries. A future study would be more reliable if it were to remove retrospective limitations. Such would be the case if patients in a disaster occurred at some sort of major event where medical professionals are volunteering and there is an established protocol of which triage criteria are to be used (ie, as commonly arranged at concerts, marathons, sporting events, large pub- lic gatherings, etc) and then patients could be followed through defini- tive treatment as done in our study and more formally compared. A study applying START, Manchester Sieve, and CareFlight triage systems to patient data from the transport bombings in London in 2005 found that missing data hindered their study [9]. They also found that triage tags from more than 1 manufacturer came in on patients and concluded that respondents were using their own supplies as well as official equip- ment [9]. The nature of disaster makes studying the response difficult.

A future study that included more penetrating trauma, more yellow and black category patients, and more elderly or included children could allow for subgroup analysis of the accuracy of the triage methods on dif- ferent patient populations. It may be that 1 triage system is better than another for specific types of Mass casualty events. It also may be that 1 triage system is better than another for different size mass casualty events. A mass casualty event such as a shooting may overwhelm local resources for a few hours, whereas a natural disaster with loss of infra- structure may overwhelm resources for days. Only the SALT method takes into account likelihood to survive given current resources and the use of lifesaving interventions.

Conclusion

Neither SALT nor START algorithm was appropriately sensitive for determining a victim’s level of triage, especially in the critically injured who would require immediate intervention. Both START and SALT tri- age algorithms did have high specificity for predicting death.

Table 4

Results SALT

	Sensitivity (n, 95% CI)	Specificity (n, 95% CI)	Positive predictive value (n, 95% CI)	Negative predictive value (n, 95% CI)
Minor/green	91.7% (55/60, 81.6-97.2)	47.5% (19/40, 31.5-63.8)	72.4% (55/76, 60.9-82)	79.2% (19/24, 57.9- 92.9)
Delayed/yellow	20% (1/5, 0.1-71.6)	90.5% (86/95, 82.8-95.6)	10% (1/10, 0.3-44.5)	95.6% (86/90, 89-98.8)
Immediate/red	20.7% (6/29, 8-39.7)	93% (66/71, 84-97.7)	54.5% (6/11, 23.3-83.3)	74.2% (66/89, 63.8-82.9)
Dead or expectant/black	50% (3/6, 11.8-88.2)	100% (94/94, 96.2-100)	100% (3/3, 29.2-100)	96.9% (94/97, 91.2-99.4)
Overall	65% (65/100, 54.8-74.2)	88.3% (265/300, 84.1-91.7)	NA	NA

Acknowledgments

We would like to thank the Summa Akron City Hospital Department of Surgery, Trauma Division for their assistance in data collection and project development.

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