Accurate prediction of discharge time and identification of patients at risk of extended length of stay (LOS) can facilitate discharge planning and positively impact both the patient and the hospital in a variety of ways. To date, however, most studies only focus on the prediction of the overall LOS, which is generally estimated at admission time to hospital, emergency department or intensive care unit. This paper explores whether individual laboratory results can improve predictions of time of discharge as the tests become available. This study suggests that there is a statistically significant relationship between individual test results and remaining days in hospital and that there is a trend towards better estimates as more consecutive tests are taken into consideration. Their effect on the estimate of discharge time is generally weak. Further work integrating groups of test results into a more sophisticated dynamical model is required.