OBJECTIVES: Current technology does not adequately predict the prognosis of patients with acute myeloid leukaemia (AML). Many patients therefore undergo unneeded but costly and toxic treatment. However, innovative approaches using genomics, epigenomics and proteomics technology are being developed to ameliorate this problem. The aim of this study was to estimate the potential economic and health impact of these technologies for AML. METHODS: This study was based on a literature review and expert opinion regarding the epidemiology, clinical practice and costs relating to AML and its treatment. Data were subsequently analysed using decision modelling. RESULTS: Conventional methods help to divide patients into three categories: favourable prognosis (20% of patients, >60% chance of survival); intermediate prognosis (60%, 30-40%); and poor prognosis (20%, <20%). Improved diagnostics would reduce the frequency and costs of unneeded treatment (chemotherapy, stem cell transplantation). Specifically, it could reassign some intermediate prognosis patients to the favourable prognosis category (approx. 10%) and others to the poor prognosis category (approx. 20%). Cost-savings could be €10,000-15,000 per patient assuming average costs of €100,000. Avoidance of unnecessary therapy would also reduce frequencies of side-effects. While better diagnostics would also result in some extra costs because of treating patients more intensively, these treatments would also lead to health gain. Given current diagnostic costs of €1500–5000 per patient and the high volume of tests, the cost reduction achievable by improving AML diagnostics would save millions of euros per year.CONCLUSIONS: Improved AML diagnostics would reduce some diagnosis, prognosis, and treatment costs. Any increased treatment costs would be coupled with health gain. In addition, rapid testing would reduce the time needed to develop a treatment plan and may thereby improve prognosis.