Background: The aging workforce combined with improvements in medical care means that workers that are diagnosed with a health condition have the opportunity to remain or return to the workforce after a health shock. This paper has two main aims. Firstly, we will investigate if and how the impact of a cancer diagnosis compares with other common health shocks on labour market outcomes. We will perform counterfactual analysis to estimate a causal impact. Secondly, we will explore gender and socioeconomic differences in labour market outcomes. Data: Data from the first four years (2009-2013) of the Understanding Society Survey will be utilised. Understanding Society is a nationally representative longitudinal household panel of approximately 40,000 households. It covers a range of topics from health both physical and mental, employment, opinions and attitudes, and demographic and socioeconomic characteristics. The key health variables used in the analysis relate to self-reported diagnosis of one or more of 16 health conditions in the previous year, self-reported health, and duration of any hospital stays. Participation in the labour market will be measured by employment status and wages will be captured by the log of the hourly wage rate. Socioeconomic status will be measured by occupation and educational attainment. The analysis will also control for gender, age, marital status, number of dependent children. Methods: We will utilise a number of different econometric techniques. The base model will be a simple Heckman selection model to explore the relationship between our health shocks and participation and wages controlling for selection into the labour market. The next step will be to use a propensity matching technique where respondents that suffer a health shock will be matched to respondents with similar observable characteristics to attempt to estimate a causal relationship between our health shocks and labour market outcomes. All analysis will be estimated separately by gender. Latent class models will be used to explore differences in outcomes by socioeconomic status. As robustness checks we will explore different methods for capturing health shocks i.e. a reported condition, change in self assessed health, as well as look at severity of condition by if the respondent had an overnight stay in hospital in the past twelve months. Results: Preliminary results show a heterogeneous effect of health shocks on labour market outcomes. Women are more likely to exit the labour force after a health shock. The impact of a health shock is stronger for those from lower socioeconomic groups. Conclusion: Understanding how the impact of cancer compares to other health shocks will help employers and policy makers develop a strategy to help workers especially women who want to remain in work after a health shock or to return to work make the transition back into employment. Focusing policy and interventions on those in lower socioeconomic groups should help to reduce health inequalities.