Uncertainty and unpredictability are features of general practice despite all efforts to decrease them by guidelines and decision support tools. A great many medical problems are simple or complicated, and guidelines support GPs to find the best solutions. In cases with multimorbidity, however, medical problems are complex and not easy to deal with.
In simple problems, GPs recognise linear causal relationships, e.g. the relation between hypertension and damage of the vascular system, and management focusses on lowering of the blood pressure. Also, in complicated situations, there are linear causal relationships, i.e. when (input) A, then (effect) B. In complex problems, a network model of interacting determinants represents the non-linear causal relationships, i.e. when A, then B if C keeps stable and D and E increase and F decreases a little. A child with a fracture of the upper arm needs a cast of tight bandages, a simple medical problem, but in case of child maltreatment the problem becomes complex.
Regarding multimorbidity, instead of simply stacking all relevant guidelines, a complexity informed approach is important for dealing with it. In a Dutch article, we explain how complexity reasoning might support GPs in managing multimorbidity.
