Algorithmic prediction of anaesthesia manpower quantity needs: A multicentre study

Abstract

Background: A shortage of anaesthetists affects health system globally. This is a study on task-force to develop a predictive model for the appropriate number of anaesthetic providers (Y). Methods: A cross-sectional study was performed with randomisation from every health service region across Thailand. The decision-making criteria for manpower needed were written and provided guidance. The number of personnel was calculated from the sum of total time spent by all anaesthetic providers divided by duration of the service. Linear regression analysis was applied. Results: In total 3774 patients were included from 18 hospitals. The factors that affect the anaesthetic providers’ allocation needs were included in the predictive model, calculated as Y = 3.53 + [0.56 (standard centre) + 0.36 (advanced centre) + 1.03 (specialty centre)] + 0.07 (American Society of Anesthesiologists physical status IV and V) + 0.61 (advanced anaesthetic medication) + [0.61 (monitored anaesthesia care) + 0.17 (general anaesthesia)] − [0.27 (pre-anaesthetic duration within 31–60 minutes) + (0.61 (over 60 minutes)] − [0.85 (anaesthetic duration within 31–60 minutes) + 1.04 (within 61–120 minutes) + 1.32 (over 120 minutes)] – [0.16 (post-anaesthetic duration within 31–60 minutes) + 0.45 (within 61–90 minutes) + 0.74 (over 90 minutes)]. Conclusion: The anaesthesia manpower algorithm developed during this study can be used to calculate the number of anaesthetists per population to maintain health services.