In this study, we updated the HEMS Benefit Score by using the Delphi method to meet the current needs of prehospital emergency care. The structure of nine-level numerical scoring categories, inherited from the original HBS, remained intact, but the exemplar interventions in each category were totally renovated. With this renewal, the scoring system was expanded from HEMS usage to cover all prehospital emergency care, including non-HEMS units, and to better face present-day needs. The renamed score, EBS, better represents the fundamental features of this scoring system and encourages non-HEMS units to utilise it in their practice.
The EBS focuses on interventions that are performed prehospitally and considers the impact of these manoeuvres for treated patients. By this, the EBS aims to evaluate the true benefit of EMS for single patients. In contrast, other scores and classifications used in prehospital settings, such as the American Society of Anesthesiologists Physical Status Classification System (ASA-PS) or NACA [5, 6, 9], describe patient background characteristics and acute clinical status. However, these scores do not evaluate the influence of prehospital care and were not originally built or implemented for prehospital use, so their reliability in prehospital settings is questionable .
The revised scoring examples are expected to improve correct benefit category selection. After each EMS mission, EMS personnel responsible for mission documenting, choose a suitable benefit category depending on the individual mission circumstances. Even though the revised examples introduce the consensus opinion of the experts and give guidelines to the benefit category selection, the scoring is ultimately based on the subjective judgement of the person doing documentation. This is because the revised examples are obviously not comprehensive, even if they are versatile. Additionally, it is justifiable to deviate from the score suggested by the exemplar interventions, if the patient has, for example, benefited from several interventions or fast air transport or, on the other hand, the interventions performed have been unnecessary or ineffectual. Despite the subjective nature of the EBS, it can serve as a valuable tool for gathering information from one aspect of prehospital missions, as the effectiveness of prehospital emergency care is a highly complex ensemble and a totally inclusive scoring system for this purpose does not exist.
During the Delphi process, the benefit category examples were renovated, but the numerical scoring categories remained intact, as it was judged unreasonable to evaluate the number of the categories during the same process. These numerical categories were originally developed based on practical experience, so there is no science behind them, and they or the number of them might be inappropriate. This issue must be taken into account in the future studies, and one must estimate the need of possible revision of the categories.
To evaluate the effectiveness of prehospital care, various quality indicators and measurement protocols have been launched [1, 11,12,13], but few studies have focused on their implementation or outcomes. A single scoring system does not solve the absence of process control in EMS systems, but combined with other manoeuvres, the EBS can support intrinsic quality improvement. For example, data on EMS unit-dispatch codes and criteria can be compared on EBSs and the benefit produced by EMS to prehospitally treated patients, based on interpretation of a treating clinician. Beyond accurately dispatching the proper level and number of EMS units, however, EMS system coverage and the geographic locating of units remain challenges [14, 15]. The type and number of missions historically presented in the areas under observation are important aspects in locating EMS units and bases. With the EBS, additional information on regional missions can be gathered. However, far-reaching conclusions based on the EBS are not justified until its reliability and validity have been studied in various settings.
Strengths and limitations
The international expert panel improved the EBS’s generalisability. Despite variations in EMS systems between countries, the EBS evaluates the potential advantages for prehospital patients regardless of the level of the treating EMS unit, the only exception being the highest EBS category, which is reserved for treatments usually offered by only advanced-level units.
The Delphi technique in this study enabled a panel of 18 experienced panellists to express their opinions freely and impersonally guided by the opinions of 11 in-hospital experts from seven specialties. This method limits dominance by eminent, eloquent or highly opinionated individuals in their respective fields of expertise [7, 8], and the panel moderator is less likely to bias the work of the panel. The Delphi method gives panellists substantial time to express their ideas, reflect on their answers and make changes, P and it avoids geographical constraints. On the other hand, the Delphi method itself is vulnerable to a loose definition of an expert, and biases might influence participant selection. The method is also dependent on questionnaire design [7, 8].
A major limitation of this study is, that there is limited data on the impact of several prehospital interventions such as prehospital airway management [16, 17]. An intervention may or may not be life-saving, depending on context. However, in the absence of a thorough research-based data on the impact of different interventions, a consensus opinion of experts is meaningful. In addition, currently no evidence exists of paramedics` ability to predict mortality.
The EBS is based on the subjective opinion of an attending prehospital clinician. To make the scoring system less dependent on individual variation, the renewed exemplar interventions in each EBS category support the selection of the appropriate category. The revised EBS can be used to benchmark different types of units, enabling quality control, which also allows the development of EMS efficiency. The given EBS scores can be compared to in-hospital interventions and patient outcome, to evaluate the adequacy of prehospital care. For example, a person unconscious due to alleged alcohol intoxication has been given EBS 2 on paramedic evaluation but needs rapid sequence intubation upon arrival in the emergency department. In this case EBS could be used to detect and study why this has happened, and this way for system quality control. Moreover, if the patients with low EBS receive intensive care or emergency procedures in hospital, this should raise the question of the quality of prehospital evaluation of the patients’ condition. Finally, this scoring system can be used to categorize prehospital interventions in clinical studies on EMS performance and to get more data where and in which type of missions, the patients are likely to benefit most. In the future EBS could optimally be linked to the care patient receive in hospital and their later level of performance. However, further reliability and validity studies are needed, before a wide-scale implementation.