Health technology assessment requires the synthesis of evidence from multiple sources to assess the cost-effectiveness of competing interventions. However, the format of the available reported evidence is often complex. We present a case-study of electronic aids to smoking cessation, which raises various methodological challenges. The evidence base evaluated highly complex and diverse interventions, reporting one or both of two different, but related, outcome measures. Furthermore, there were differences between studies in the number and timing of follow-up times reported, whereas 12-month continuous abstinence is required in the cost-effectiveness analysis. We develop a categorization system to evaluate the interventions, and we use network meta-analysis of time-to-relapse model parameters to estimate coherent intervention effects for any pair of categories. We compare the fit of alternative time-to-relapse models and explore the effect of joint models for both outcome measures, which can be used to estimate treatment effects when a given outcome is not reported, so that all the available evidence can be combined.