Relations of Time and Effect of Medical Interventions

For the implementation of time-critical decision support algorithms a precise relation between intervention and effect needs to be established. We evaluated for catecholamines and infusions the relation in time between charted dose and effect on hemodynamic variables. The onset of the change of the hemodynamic variables was determined by autoregressive models. The lag of 13 min (0 29) between intervention and effect and the great variance of this lag pose an important problem for time-critical decision support. Even after optimizing data acquisition important factors remain unaccounted for. Therefore, decision support systems may need extensive testing with real-world data.