Priorities for content for a short‐course on postoperative care relevant for low‐ and middle‐income countries: an e‐Delphi process with training facilitators

Most surgical and anaesthetic mortality and morbidity occurs postoperatively, disproportionately affecting low‐ and middle‐income countries. Various short courses have been developed to improve patient outcomes in low‐ and middle‐income countries, but none specifically to address postoperative care and complications. We aimed to identify key features of a proposed short‐course addressing this topic using a Delphi process with low‐ and middle‐income country anaesthesia providers trained as short‐course facilitators. An initial questionnaire was co‐developed from literature review and exploratory workshops to include 108 potential course features. Features included content; teaching method; appropriate participants; and appropriate faculty. Over three Delphi rounds (panellists numbered 86, 64 and 35 in successive cycles), panellists indicated which features they considered most important. Responses were analysed by geographical regions: Africa, the Americas, south‐east Asia and Western Pacific. Ultimately, panellists identified 60, 40 and 54 core features for the proposed course in each region, respectively. There were high levels of consensus within regions on what constituted core course content, but not between regions. All panellists preferred the small group workshop teaching method irrespective of region. All regions considered anaesthetists to be key facilitators, while all agreed that both anaesthetists and operating theatre nurses were key participants. The African and Americas regional panels recommended more multidisciplinary healthcare professionals for participant roles. Faculty from high‐income countries were not considered high priority. Our study highlights variability between geographical regions as to which course features were perceived as most locally relevant, supporting regional adaptation of short‐course design rather than a one‐size‐fits‐all model.