The health care sector in New Zealand has undergone substantial structural reform since 1983, and stands out relative to other OECD countries, in that it has a relatively low per capita health expenditure, and a high share of public funding. Efficient allocation of resources to accommodate local needs in this community-oriented and public dominant model of the health care system is paramount. This paper employs the National Minimum Dataset from 2007 to 2011 to construct an empirical model aimed at predicting hospital demand. We formulate an easy to implement approach that can be used at the national level, as well as for individual District Health Boards (DHBs) that are regionally defined, and can also be disaggregated by category of patient, e.g. acute care versus elective admissions. We find the use of lagged information in this model to be vital, and by contrasting expected and actual demand, we then evaluate variations in excess demand. We find evidence that suggests in low risk elective cases, unexpected demand significantly reduces an individual’s hospital stay, and increases the likelihood of acute readmission in 30 days. Additionally, the cumulative evidence presented points to excess demand at both the hospital level and within-disease chapter, resulting in more attention paid to high risk patients, to the detriment of low risk cases. The negatively and significant association between hospital stay and readmission in 30 days for low risk cases may prompt policy makers to consider a ‘reduction in readmission program’ for New Zealand.