Improving Project Management of Healthcare Projects through Knowledge Elicitation

This chapter describes a case study where Bayesian Networks (BNs) were used to construct an expertbased software effort and risk prediction model for use by a large healthcare organisation in Auckland (New Zealand) to manage healthcare software projects delivered on the Web. This model was solely elicited from expert knowledge, with the participation of seven project managers, and was validated using data from 22 past finished projects. The model led to numerous changes in process and also in business. The company adapted their existing effort and risk management process to be in line with the model that was created, and the use of a mathematically based model also led to an increase in the number of projects being outsourced to this company by other company branches worldwide. Their predictions improved significantly too. The results suggest that the use of a model that allows the representation of uncertainty, inherent in effort estimation, can outperform expert-based estimates. INTRODUCTION AND BACKGROUND Healthcare projects, similarly to software projects in other domains, need to be managed effectively so to enable the corresponding applications to be delivered on time and within budget. However, for a project to be managed effectively, it is important that a realistic estimate of the amount of effort (in person hours) needed to develop a software application be obtained and used as basis to predict project costs and to allocate resources (e.g. developers). This estimate is generally derived Emilia Mendes The University of Auckland, New Zealand DOI: 10.4018/978-1-4666-3990-4.ch039