OBJECTIVES: To model the financial impact for the healthcare institution of specimen rejection due to preanalytical errors in the laboratory testing phase, using institution specific data. METHODS: Critical data such as number of beds; overall budget; number of patients of different types seen each year; and number of sample rejections, as well as qualitative data, eg. probable impact of sample rejection were collected by interviewing institution staff from multiple country institutions (N=10).  The data were then entered into a model to calculate the possible financial impact of laboratory sample rejections.  The model separates patients into different groups according to the likely effects of having a sample rejected, the probability that the rejection would have a low, medium or high impact and the consequences on institution time and resources.  The overall consequence, or opportunity cost, was expressed as patient treatment time and financial cost. RESULTS:  The size of the institutions ranged from 326 to 1,200 beds, with total operating costs varying between €41 million and €1.1 billion.  The number of blood tests per month was between 37,000 and 458,000 and of these between 0.09% and 2% were rejected (mean 0.93%).  The total cost of specimen rejection ranged from €22k to €5.9 million per annum (mean €1.9 million), equating to a percentage of total operating costs from 0.1% to 1.2% (mean 0.4%).  The estimated cost per patient for a sample rejection was from €29 to €349 (mean €171). CONCLUSIONS:  A customisable model allows institutions to estimate, using local data and assumptions, the effect of sample rejection on patient treatment and cost.  Results can be compared to those from other institutions to benchmark performance and assumptions.  The results demonstrated that a reduction in the number of rejected samples due to preanalytical errors could lead to significant cost savings for most institutions.