Factors predicting burn surgery operative time in a middle income country regional burn service.
Marlé MaraisShelley WallMichelle SmithNikki AllortoPublished in: Journal of burn care & research : official publication of the American Burn Association (2024)
Access to theatre is essential for surgical management of deep burns. This is a scarce resource in low-middle income countries. It underpins the importance of optimizing theatre time. We sought to look at specific factors and their influence on operative time in minor to moderate burn surgery. This knowledge can assist teams where theatre planning and optimization may be beneficial in resource limited settings . Operative records between January and December 2018 at the Regional Hospital , were analysed. Data fields included age, gender, total body surface area of burn, surface area burn operated on, intra-operative position change, seniority of surgeon, presence of an assistant, inclusion of special areas, predicted operative time and actual operative time. Operative records for 265 patients were analysed, with a median operative time of 40 minutes (IQR 25 - 64). Overall factors that predict longer operating time are larger total body surface area burn, larger surface area burn operated on, an operation involving at least one special area, number of special areas operated on, position change, presence of an assistant and longer predicted operative time. Total percentage burn, operated percentage, special areas to be operated and position change are overall factors to be considered when planning a burns list for the non-specialist burn surgeon. This knowledge may be useful for an inexperienced surgeon to understand, and aid in the effective utilisation of limited operative time available for the surgical management of deep burns in resource limited settings.
Keyphrases
- wound healing
- healthcare
- minimally invasive
- mental health
- end stage renal disease
- physical activity
- palliative care
- chronic kidney disease
- robot assisted
- ejection fraction
- prognostic factors
- newly diagnosed
- machine learning
- atrial fibrillation
- coronary artery disease
- percutaneous coronary intervention
- high intensity
- electronic health record