Six methodological steps to build medical data warehouses for research

Abstract: Purpose: We propose a simple methodology for heterogeneous data collection and central repository-style database design in healthcare. Our method can be used with or without other software development frameworks, and we argue that its application can save a relevant amount of implementation effort. Also, we believe that the method can be used in other fields of research, especially those that have a strong interdisciplinary nature. Background: The idea emerged during a healthcare research project, which consisted among others in grouping information from heterogeneous and distributed information sources. We developed this methodology by the lessons learned when we had to build a data repository, containing information about elderly patients flows in the UK''s long-term care system (LTC). Design: We explain thoroughly those aspects that influenced the methodology building. The methodology is defined by six steps, which can be aligned with various iterative development frameworks. We describe here the alignment of our methodology with the RUP (rational unified process) framework. The methodology emphasizes current trends, as early identification of critical requirements, data modelling, close and timely interaction with users and stakeholders, ontology building, quality management, and exception handling. Results: Of a special interest is the ontological engineering aspect, which had the effects with the highest impact after the project. That is, it helped stakeholders to perform better collaborative negotiations that brought better solutions for the overall system investigated. An insight into the problems faced by others helps to lead the negotiators to win-win situations. We consider that this should be the social result of any project that collects data for better decision making that leads finally to enhanced global outcomes. [Copyright &y& Elsevier]