Dr Tamlyn Rautenberg
- Post-doc research dellow
Dr Tamlyn Rautenberg joined HEARD as a Post-Doctoral Research Fellow. She holds a degree in Diagnostic Medical Ultrasound from the Durban University of Technology, South Africa, a Masters in International Healthcare Management, Economics and Policy from Bocconi University, Milan (Italy), and a PhD in Health Economics from the University of Leeds (UK).
As part of her PhD, Dr Rautenberg developed a step by step guide to cost effectiveness modelling under the supervision of Chris McCabe, Claire Hulme and Richard Edlin. She has completed various training in health economic modelling including the Advanced Modelling Methods Course for Health Economic Evaluation: A Computer-Based Course at the University of York in 2008 and has 8 years’ experience as senior research consultant for a European contract research organisation specialising in the reimbursement of pharmaceutical and medical devices in the European and UK markets.
In this capacity, Dr Rautenberg has undertaken systematic reviews of clinical and economic evidence and developed health economic models and has been involved in evidence for reimbursement in countries including UK, Germany, Switzerland and South Africa. Her main research area is cost effectiveness modelling and the methods used to develop models. She also enjoys training and teaching of health economics, modelling and related topics.
Siedner, MJ., Bwana, MB., Moosa, MYS., Paul, M., Pillay,, McCluskey, SS Aturinda, I., Ard, K., Muyindike, W., Moodley, P., Brijkumar, J., Rautenberg, T., George, G., Johnson,B., Gandhi, RT., Sunpath, H & Marconi, VC (2017) The REVAMP trial to evaluate HIV resistance testing in sub-Saharan Africa: a case study in clinical trial design in resource limited settings to optimize effectiveness and cost effectiveness estimates HIV Clinical Trials, http://dx.doi.org/10.1080/15284336.2017.1349028
Rautenberg, T., Hulme, C and Edlin, R (2016) Methods to construct a step-by-step beginner's guide to decision analytic cost-effectiveness modeling Dove Press, 11(8), pp 573-581, DOI https://doi.org/10.2147/CEOR.S113569