OBJECTIVES: Decision analytic models used in cost-effectiveness analysis often rely upon long-term survival data from observational studies for which patient-level data are not available. Analysts may therefore be required to digitally extract survival data from published Kaplan-Meier plots and fit parametric survival curves, in order to provide estimates of time until an event or a per-cycle probability of an event occurring. Methods used in practice include minimising a sum of squared residuals statistic (using Microsoft Excel Solver) in order to estimate desired parameters for a given distribution. A technique recently published by Guyot et al provides a methodology for reconstructing a patient-level dataset from published Kaplan-Meier plots, using the tabulated numbers at risk to incorporate censoring. An alternative reconstructing methodology which does not account for censoring is also explored. We sought to establish the accuracy of these methods. METHODS: The techniques described were tested on a published dataset (Gehan). Patient-level datasets were reconstructed based on the digitised curves. Results of survival models fitted using these techniques are presented for comparison against models fitted using the original data. RESULTS: Median survival times using a Weibull regression on the original dataset was 7.2 and 25.7 months for the placebo and treatment arms, respectively. Using the minimisation of squared residuals approach resulted in median times of 6.1 and 25.0 months. The reconstructed patient-level approach incorporating censoring yielded median times of 7.1 and 28.9 months, whilst the alternative technique (without censoring) resulted in median times of 7.1 and 27.6 months. CONCLUSIONS: The reconstructed patient-level datasets can be interrogated as per patient-level survival data, allowing diagnostic statistics such as the Akaike Information Criterion to be estimated and plots of log-cumulative hazard to be generated, which aid the analyst in selecting appropriate distributions and assumptions. It is therefore suggested that these techniques become the preferred methods.