Developing call out criteria for South African helicopter services: A delphi study - Laatz, Diane Inge (Division of Emergency Medicine, 2019)
Background Helicopter Emergency Medical Services (HEMS) are an expensive resource that should be utilised efficiently to optimise the cost-benefit ratio. This is especially true in resource-limited settings, such as South Africa. This may be achieved by implementing call-out criteria that are most appropriate to the healthcare system in which HEMS operate. Currently, there are no published evidence-based HEMS callout criteria developed for South Africa. By identifying patients that are most likely to benefit from HEMS, their utilisation can be enhanced and adjusted to ensure optimal patient outcome. Aim To systematically utilise expert opinions to reach consensus on HEMS call-out criteria that are contextual to the South African setting. Methods A modified Delphi technique was used to develop call-out criteria, using current literature as the basis of the study. Purposive, snowball sampling was employed to identify a sample of 118 participants locally and internationally, of which 42 participated for all three rounds. Using an online survey platform, binary agreement/disagreement with each criterion was sought. Acceptable consensus was set at 75%. Statements were sent out in the third round ascertaining whether participants agreed with the analysis of the first two rounds. Results After two rounds, consensus was obtained for 63% (36/57) of criteria, while 64% of generated statements received consensus in the third round. Results emphasised the opinion that HEMS dispatch criteria relating to patient condition and incident locations were preferential to a comprehensive list. We present these criteria in a collated format, favouring further inquiry on a case-by-case basis. Participants suggested the use of a screening tool, which can guide dispatch decision-making. Conclusion The combination of existing literature and participant opinions, established that callout criteria are most efficient when based on clinical parameters and geographic considerations, as opposed to a specified list of criteria. This could improve resource allocation, specifically in a low to middle income country such as South Africa.