  The presence of methicillin-resistant \textit{Staphylococus Aureus} (MRSA) in
complicated skin and soft structure infections (cSSSI) is associated with
greater health risks and economic costs to patients. There is concern that MRSA
is becoming resistant to other "gold standard" treatments such as vancomycin,
and there is disagreement about the relative efficacy of vancocymin compared to
linezolid. There are several review papers employing Bayesian Network
Meta-Analyses (BNMAs) to investigate which treatments are best for MRSA related
cSSSIs, but none address time-based design inconsistencies. This paper proposes
a time-varying BNMA (tBNMA), which models time-varying treatment effects across
studies using a Gaussian Process kernel. A dataset is compiled from nine
existing MRSA cSSSI NMA review papers containing 58 studies comparing 19
treatments over 19 years. tBNMA finds evidence of a non-linear trend in the
treatment effect of vancomycin - it became less effective than linezolid
between 2002 and 2007, but has since recovered statistical equivalence.
