Skip to main content

Development of outcomes for evaluating emergency care triage: a Delphi approach



Triage is used as standard of care for prioritization and identification of time-critical patients in the emergency department (ED) globally, but it is unclear what outcomes should be used to evaluate triage. Currently used outcomes do not include important time-critical diagnoses and conditions.


We used 18 Swedish triage experts to collect and assess outcomes for the evaluation of 5-level triage systems. The experts suggested 68 outcomes which were then tested through a modified Delphi approach in three rounds. The outcomes aimed to identify correctly prioritized red patients (in need of a resuscitation team), and orange patients (other time critical conditions). Consensus was pre-defined as 70% dichotomized (positive/negative) concordance.


Diagnoses, interventions, mortality, level of care and lab results were included in the outcomes. Positive consensus was reached for 49 outcomes and negative consensus for 7 outcomes, with an 83% response rate. The five most approved outcomes were the interventions Percutaneous coronary intervention, Surgical airway and Massive transfusion together with the diagnoses Tension pneumothorax and Intracerebral hemorrhage that received specific interventions. The outcomes with the clearest disapproval included Admittance to a ward, Treatment with antihistamines and The ordering of a head computed tomography scan. The outcomes were considered valid only if occurring in or from the ED.


This study proposes a standard of 49 outcomes divided into two sets tied to red and orange priority respectively, to be used when evaluating 5-level priority triage systems; Lund Outcome Set for Evaluation of Triage (LOSET). The proposed outcomes include diagnoses, interventions and laboratory results. Before widespread implementation of LOSET, prospective testing is needed, preferably at multiple sites.


The use of triage in the emergency department [ED] is generally motivated by the need of identifying and treating patients with time-critical conditions [1] and by patient safety concerns stemming from waiting times [2]. However, no clear consensus exists for what outcomes to use when evaluating ED triage [3]. Reduction of short-term mortality has been described as a primary reason for triage by both designers of triage systems [4] and their users [5], but a review [3] noted that only 12 out of 66 triage validation studies used mortality as a reference outcome. Other outcomes that have been evaluated include death in the ED, admittance to the intensive care unit [ICU] or to a ward [3], need for an emergency procedure, and specific lactate levels [6].

Another problem is that many triage validation studies are based on outcomes that do not include the identification of time-critical conditions. Missing a time-critical condition (e.g. anaphylactic shock) will thereby not be considered a failure if death and/or ICU admission were avoided due to timely treatment. [3].

Previous validation studies for adults have considered triage to be a one-dimensional problem where all patients with untoward outcomes ideally should be categorized to the highest triage category [red priority] [3]. This is neither reasonable nor consistent with how triage systems intentionally assign some time-critical conditions that do not need a full resuscitation team to the second highest priority [orange priority], such as suspected testicular torsion [7, 8]. However outside of pediatric triage [9], the two highest priorities have not been evaluated separately.

The aim of this study was to develop a set of outcomes that could be used for evaluating 5-level ED priority triage systems.



A modified Delphi approach [10] was used. The Delphi method is an iterative process of repeated questionnaires that are bundled with the results of the previous rounds to a panel of experts with the goal of finding consensus. The items to be assessed in the Delphi rounds were gathered in initial interviews with the experts in round one, and from the published literature. The Delphi approach has successfully been used when seeking consensus in emergency care [11], and when assessing questions related to triage [12]

Panel of experts

To create the expert panel, three important groups were identified: Clinicians working in emergency care, researchers publishing studies related to triage, and designers of ED priority triage systems. To the clinical part of the expert group, we recruited Swedish physicians and registered nurses with a specific interest and knowledge of triage. To the research group, we recruited individuals who were listed as either the first, second or last author of a published study during the last five years related to emergency priority triage and outcomes for adult patients. Lastly, in the designer group we recruited designers or editors of emergency care priority triage systems and persons medically responsible or integral in the implementation of such systems. Representatives from all major triage systems in use in Sweden (RETTS, SATS, WEST) were recruited. The experts in all three groups were recruited from geographically diverse locations in Sweden. If an expert missed any of the questionnaire rounds, they were not excluded from joining the following rounds (Table 1).

Table 1 Expert panel demographics

Data collection

The data collection was split into collecting suggested outcomes (round one) during three weeks in the spring of 2021, and testing of these outcomes by a Delphi approach (round two to four) during the last months of 2021. The experts were informed that the term outcome could include any measurable outcome that they felt could be relevant to evaluate triage, including e.g. admission to in-hospital care, diagnosis, interventions or laboratory testing.

Round one: collection of outcome proposals and creation of Delphi questionnaire

The outcomes to be assessed were gathered through qualitative semi-structured interviews using written notes shared with the expert. During the interview, the experts suggested outcomes and assigned them to either of two groups: Outcomes that would motivate red priority at the ED, i.e. with resuscitation team activation, and outcomes with no need for resuscitation team activation but that are still considered time-critical; i.e. that would motivate red or orange priority. After round one the experts could not suggest new outcomes.

For every proposed outcome the experts were asked to also suggest a time-frame within which the outcome should be evaluated. When the suggested time-frames for the outcome varied among the experts, a question of the time-frame was included separately in the Delphi questionnaire, see Fig. 1. If only similar time-frames were suggested, the time-frame was embedded in the outcome description, exemplified in Fig. 2. Two groups of time-frames emerged from the interviews; short-term, often described as”in the ED'' or up to a day from leaving the ED, and long-term, described as a couple of days up to 30 days. Since no clear cutoffs were presented in the interviews, we included this as a question at the beginning of the questionnaire, intentionally leaving the cut offs as overlapping, see Table 2.

Fig. 1
figure 1

Outcome question without a specified time-frame, followed by a question regarding time-frame

Fig. 2
figure 2

Outcome question with the time-frame included in the definition of the outcome

Table 2 Suggested time-frames

At the end of each interview the suggested outcomes were repeated back to the experts to confirm that they were understood correctly. The interviews were conducted during the spring of 2021 and held through video calls due to the COVID-19 pandemic. Two pilot interviews were conducted with emergency care specialist nurses before the first interview, which led to changes in how the questions were presented, to avoid misunderstandings.

The Delphi questionnaire was constructed and answered through REDCap which is a web-based platform that provides secure, web-based access to research data and tools to gather it through questionnaires [13, 14]. Our questionnaire was written in Swedish and piloted on the above mentioned specialist nurses before being sent to the experts.

Rounds two to four

Subsequent rounds followed a modified Delphi process as described by Clayton [10]. Experts were invited to the Delphi questionnaire via individual emails sent through REDCap. The outcomes gathered in round one were presented to the experts together with the experts' arguments for or against the outcomes. Potential for conflict between different outcomes were described next to the affected outcome, such as that positive consensus of one outcome could make another redundant. Admission to ward was added as an outcome in round two based on previous research; the inclusion of this outcome was planned beforehand. The experts were informed that outcomes could be added by the researchers, but not of which specific outcomes.

All outcomes were presented as statements with a similar structure including both outcome and priority level as seen in Figs. 1 and 2. The outcomes were assessed via a five-stepped Likert scale from “Strongly agree” to “Strongly disagree”. The experts also had the possibility, through a free text input, to supplement their opinion with new arguments that they believed were missing. These arguments were analyzed with manifest qualitative content analysis [15] and arguments for or against outcomes were presented verbatim alongside the outcomes in the following rounds. From round three, the aggregated expert opinions of the previous rounds were displayed alongside the outcome, and from round four this included stability. All questionnaires were sent out with three reminders and the experts had one month to answer each questionnaire.

Data analysis

The data from the Delphi questionnaires were extracted from REDCap and analyzed in Microsoft Excel 2013 for Windows. The predetermined cutoff for consensus was that 70% of the responses fell in either of the upper two alternatives of the five-step Likert scale [16], i.e. positive consensus, or in the lower two alternatives, i.e. negative consensus. Stability was similarly deemed reached if 70% of the answers did not change from its dichotomized group in the previous round, i.e. positive or negative. If an outcome reached the predetermined cutoffs for consensus and stability, it was excluded from further rounds. This could happen at earliest after round three since stability required two rounds of questionnaires to be calculated. For the time-frames, consensus/stability was calculated per suggested cutoff in each group (long term/short term).

Since all outcomes that gained consensus also reached stability it was decided to present median and interquartile range [IQR] for all outcomes based on measures of spread [17]. The round where consensus was reached was recorded together with the median and IQR from the round when both consensus and stability were reached.


In total, 18 experts were recruited, 10 in the clinical group and four each in the researcher and design groups. The experts in the research and designer groups all had a clinical background in emergency medicine and care, and most of them were still partly clinically active. The experts had worked an average 14 years with ED triage. All of the groups had an even spread between genders (50%/50%) and profession (61% registered nurses, 39% physicians). The total response rate in all rounds was 83%, and the rounds are described in Table 3.

Table 3 Response rate based on expert group

In round one the experts suggested 67 outcomes, and one (admission to ward) was added from previous research, yielding 68 outcomes to be assessed in the Delphi rounds. In these, there was positive consensus for 49 outcomes, i.e. approval of the outcome, and negative consensus for seven outcomes, i.e. disapproval, as described in Table 4. This was split between red priority where 38 outcomes reached positive consensus and two reached negative consensus, and orange priority where eleven/five reached positive/negative consensus. The outcome admission to ward reached negative consensus. Some outcomes that were suggested for both red and orange priority reached consensus for both priorities, and some outcomes that were similarly formulated also reached consensus. These outcomes are marked with roman numerals in the “Conflict” column in Table 4, and are further clarified below the table.

Table 4 Results from Delphi rounds—outcomes that reached consensus

All outcomes that reached positive consensus and stability also reached consensus and stability regarding that they should be evaluated within the short-term time-frame, which in itself reached consensus for the alternative In the ED, see Table 2. This means that the outcomes should only be counted if they occurred in the ED or in some cases, initiated directly from the ED in the case of hospital admission or immediate surgery.

  1. (I)

    Two variations of how anaphylaxis should be evaluated reached positive consensus for red priority.

  2. (II)

    STEMI reached consensus for both red and orange priority.

  3. (III)

    Admittance to a step-down unit (Intermediate Care Unit) reached positive consensus for both red and orange priority.

  4. (IV)

    Two different outcomes to measure the occurrence of immediate/early surgical intervention reached positive consensus for red priority and one for orange.

  5. (V)

    Two diagnoses that lead to immediate/early surgical intervention reached positive consensus for orange priority, see also conflict IV.

  6. (VI)

    Two variations of how sepsis should be evaluated reached positive consensus for red priority, and one reached positive consensus for orange priority.


The main result of this study is the proposal of 49 outcomes grouped in two priority-specific sets to be used for the validation of ED triage systems for adults, as well as the recommendation against seven outcomes. We have chosen to call the outcome groups Lund Outcome Set for Evaluation of Triage (LOSET).

Comparison to other comprehensive sets of outcomes

To our knowledge the only other comprehensive work on outcomes in the evaluation of triage systems has been done by van Veen et al. [9] in pediatric patients. In this study, the authors evaluated a specific triage system (SATS) for a specific study, with the methodology focused on the evaluation at hand and not the development of the outcomes. In contrast, LOSET was developed independently of any specific study with a methodology focused on the selection of outcomes, and is by design triage system agnostic. Further, van Veen et al. evaluated the highest priority based only on vital parameters, and we argue that this creates the possibility of circular logic that LOSET does not have: A triage system where the cutoffs for vital signs are based on the reference values for red priority will in principle never be wrong. Moreover, diagnoses such as sepsis or meningitis were found In the second highest priority in van Veens work, but in the highest priority in the present study. In a subsequent sudy, Hansen et al. [18] combined the highest two priorities in van Veen’s study to validate the highest priority in a pediatric population, making the third highest priority comparable to the second highest priority (orange) in our study. This would increase the disparity even further, with no common outcomes except one that was disapproved in this study; A head CT scan was ordered on the patient in the ED.

Singular outcomes used in other studies

Previous studies evaluating triage for adults have used some of LOSET’s proposed outcomes: mortality, admittance to the ICU, acute surgical intervention and lactate over 5 mmol/L [3, 6]. Admittance to a ward, which was the outcome with the clearest negative consensus in this study (median 1,00, IQR 0,00), has also been used. Spangler [19] used hospital admission as an outcome because of “face validity”, perhaps also because of its previous use in multiple studies [20,21,22]. Its inversion, discharged from the ED, has been used to indicate low acuity [3]. The negative consensus for admission to a ward in the present study could probably be explained by the fact that not all admissions are time-critical, and that the experts valued triage specificity.

Conflicts in LOSET

There were six identified conflicts in the results. These could be viewed from a methodological perspective; can a Delphi approach efficiently reach a dichotomous consensus if an outcome is proposed in many forms, or is it more methodologically sound to first reach a consensus on which version of the outcome to use? An alternative is that the complexity of the research question might make it difficult to reach a dichotomized consensus. One conflict (VI) arose from a proposal to supplement a sepsis diagnosis with vital signs assessed at ward admission (which avoids circular logic, as the vital signs at triage are not used, see above). Including vital signs in the sepsis outcome could also lessen the effect on triage specificity that liberally made sepsis diagnoses could create. The apparent risk, however, is that early treatment in the ED will reverse or stop a septic patient from developing shock, and that effective treatment could thereby make a red priority “wrong”. Testicular or ovarian torsion (conflict V) were assigned to orange priority by our experts to save resources, i.e. to not activate a resuscitation team that red priority generally leads to. However, by including acute surgical intervention in the red priority, both these conditions could be correctly evaluated as red. All of the conflicts above could be viewed as stemming from the will to limit overtriage, which seems like a recurring theme in the results.

Application of LOSET

We suggest assessing both red and orange priority as correct in conflicts II-VI. For conflict I, we would suggest disregarding adrenaline use in anaphylaxis since this outcome should be easier to use. Although developed for ED triage, LOSET should also be possible to use in the evaluation of pre-hospital priority triage, including ambulance dispatch telephone triage, since the goal in these situations are generally the same as in the ED, i.e. identifying time critical conditions. The outcome set could also form a basis for the evaluation of care level triage which is often applied in the form of telephone triage, where the goal is to direct the patient to the optimal level of care, such as the ED, urgent care, primary care etc. However, it should be noted that LOSET is focused on time-critical conditions, which is likely only a subset of all conditions that that should be referred to the ED.

Strengths and limitations

Even if the research question fits the Delphi methodology, i.e. generation of consensus on complex questions [23], the conflicts in the results indicate a methodological problem. However, most outcomes proposed do not include conflicts, and it seems reasonable to assume that multiple studies are needed to optimize the LOSET outcomes. Followup studies with other methodologies may answer some of the questions raised by the present results.

This study included a panel with expertise evident through their experience with triage, their diverse and relevant backgrounds, and the richness of suggestions for outcomes. There is no clear consensus on the panel size in Delphi studies, but our size of 18 is in accordance with Clayton [10] who recommends groups of 15–30 panelists if the group is heterogeneous such as ours. The fact that all experts were from Sweden could limit the results’ transferability to other countries. Transferability could also be a problem towards triage systems without five levels, and in pediatric systems. However we find it likely that any system that considers the top two priorities as time-critical and uses the highest priority to call on a resuscitation team can apply most, if not all, of the outcomes suggested in the present study.


This study proposes a standard of 49 outcomes divided into two sets tied to red and orange priority respectively, to be used when evaluating 5-level priority triage systems; Lund Outcome Set for Evaluation of Triage (LOSET). The proposed outcomes include diagnoses, interventions and laboratory results. Before widespread implementation of LOSET, prospective testing is needed, preferably at multiple sites.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.



Bilevel positive airway pressure


Computed tomography


Continuous positive airway pressure


Emergency department


Intensive care unit


Interquartile range


Lund Outcome Set for Evaluation of Triage


National Early Warning Score


Non-invasive ventilation


Percutaneous coronary intervention


Rapid Emergency Triage and Treatment System


South African Triage Scale


Statens beredning för medicinsk och social utvärdering


ST Elevation Myocardial Infarction


WEst coast System for Triage


  1. Farrokhnia N, Göransson KE. Swedish emergency department triage and interventions for improved patient flows: a national update. Scand J Trauma Resusc Emerg Med. 2011;19:72.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Wireklint SC, Elmqvist C, Parenti N, Göransson KE. A descriptive study of registered nurses’ application of the triage scale RETTS©; a Swedish reliability study. Int Emerg Nurs. 2018;38:21–8.

    Article  PubMed  Google Scholar 

  3. Zachariasse JM, van der Hagen V, Seiger N, Mackway-Jones K, van Veen M, Moll HA. Performance of triage systems in emergency care: a systematic review and meta-analysis. BMJ Open. 2019;2019(9): e026471.

    Article  Google Scholar 

  4. Widgren, B. (2012). RETTS: Akutsjukvård direkt. Studentlitteratur.

  5. Statens beredning för medicinsk och social utvärdering. (2010). Triage och flödesprocesser på akutmottagningen: En systematisk litteraturöversikt (SBU-rapport, 197). Stockholm: SBU

  6. Levin S, Toerper M, Hamrock E, Hinson JS, Barnes S, Gardner H, Douglas A, Linton B, Kirsch T, Kelen G. Machine-learning-based electronic triage more accurately differentiates patients with respect to clinical outcomes compared with the Emergency Severity Index. Ann Emerg Med. 2018;71(5):565–74.

    Article  PubMed  Google Scholar 

  7. Gilboy, N., Tanabe, P., Travers, D., & Rosenau, A. M. (2020) Implementation handbook 2020 edition: ESI Emergency Severity Index. (Version 4). Emergency Nurses Association

  8. Predicare. (2022). RETTS-online (Version 2022) [Web-app]. Predicare.

  9. van Veen M, Steyerberg EW, Ruige M, van Meurs AHJ, Roukema J, van der Lei J, Moll HA. Manchester triage system in pediatric emergency care: prospective observational study. BMJ. 2008;337:a1501.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Clayton MJ. Delphi: a technique to harness expert opinion for critical decision-making tasks in education. Educ Psychol. 2006;4(17):373–86.

    Article  Google Scholar 

  11. Wihlborg J, Edgren G, Johansson A, Sivberg B. The desired competence of the Swedish ambulance nurse according to the professionals—a Delphi study. Int Emerg Nurs. 2014;22(3):127–33.

    Article  PubMed  Google Scholar 

  12. Khorram-Manesh A, Burkle FM, Nordling J, Goniewicz K, Faccincani R, Magnusson C, Merzaai B, Ratnayake A, Carlström E. Developing a translational triage research tool: part two—evaluating the tool through a Delphi study among experts. Scand J Trauma Resusc Emerg Med. 2022;30(1):48.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)—a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42(2):377–81.

    Article  PubMed  Google Scholar 

  14. Harris PA, Taylor R, Minor BL, Elliott V, Fernandez M, O’Neal L, McLeod L, Delacqua G, Delacqua F, Kirby J, Duda SN. The REDCap consortium: Building an international community of software platform partners. J Biomed Inform. 2019;95: 103208.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Lundman, B., & Hällgren Graneheim, U. (2017). Kvalitativ innehållsanalys. B. Höglund-Nielsen & M. Graneskär (Red). Tillämpad kvalitativ forskning inom hälso- och sjukvård. (Tredje upplagan. s. 219–233). Studentlitteratur.

  16. Hsu C-C, Sandford BA. The Delphi technique: making sense of consensus. Pract Assess Res Eval. 2007;12:10.

    Article  Google Scholar 

  17. Varndell W, Fry M, Lutze M, Elliott D. Use of the Delphi method to generate guidance in emergency nursing practice: a systematic review. Int Emerg Nurs. 2020;56: 100867.

    Article  PubMed  Google Scholar 

  18. Hansen LH, Mogensen CB, Wittenhoff L, Skjöt-Arkil H. The danish regions pediatric triage model has a limited ability to detect both critically ill children as well as children to be sent home without treatment—a study of diagnostic accuracy. Scand J Trauma Resusc Emerg Med. 2017;25:55.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Spangler D, Hermansson T, Smekal D, Blomberg H. A validation of machine learning-based risk scores in the prehospital setting. PLoS ONE. 2019;14(12): e0226518.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Aeimchanbanjong K. Validation of different pediatric triage systems in the emergency department. World J Emerg Med. 2017;8(3):223.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Gravel J, Fitzpatrick E, Gouin S, Millar K, Curtis S, Joubert G, Boutis K, Guimont C, Goldman RD, Dubrovsky AS, Porter R, Beer D, Doan Q, Osmond MH. Performance of the Canadian triage and acuity scale for children: a multicenter database study. Ann Emerg Med. 2013;61(1):27–32.

    Article  PubMed  Google Scholar 

  22. Gräff I, Goldschmidt B, Glien P, Bogdanow M, Fimmers R, Hoeft A, Kim S-C, Grigutsch D. The German Version of the Manchester Triage System and its quality criteria—first assessment of validity and reliability. PLoS ONE. 2014;9(2):e88995.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Powell C. The Delphi technique: myths and realities. J Adv Nursing. 2013;41(4):376–82.

Download references


We wish to acknowledge the triage experts crucial to the construction of LOSET.


Open access funding provided by Lund University. This work was supported by Region Skåne and an ALF grant at Skane University Hospital, and the Swedish Heart-Lung Foundation. This study was also part of the AIR Lund (Artificially Intelligent use of Registers at Lund University) research environment, and received funding from the Swedish Research Council (VR; grant no. 2019-00198).

Author information

Authors and Affiliations



AJ conceptualized the idea, designed the methodology together with AE, recruited experts in the academic and designer group, constructed the questionnaire, analyzed the results and wrote the first draft of the article. AE designed the methodology together with AJ and provided revisions of the manuscript. JLF critically revised the manuscript. UE provided funding, recruited the experts in the clinician group and critically revised the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to André Johansson.

Ethics declarations

Ethics approval and consent to participate

All experts were informed about the study in writing before the first interview and again verbally at the first interview. Oral consent was collected from every expert before the start of interviews. In accordance with Swedish law, this study was not subject to review by an ethics review board. Confidentiality was kept through multiple layers. Only the researcher doing the analysis was able to access the data, and the data was kept at a cloud service which required two-part authentication to access. Confidentiality was also kept between experts.

Consent for publications

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Johansson, A., Ekwall, A., Forberg, J.L. et al. Development of outcomes for evaluating emergency care triage: a Delphi approach. Scand J Trauma Resusc Emerg Med 31, 10 (2023).

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI:


  • Triage
  • Outcome measures
  • Outcome set
  • Emergency care
  • Risk assessment
  • Reference standard