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Six methodological steps to build medical data warehouses for research
N B Szirbik1, C Pelletier, T Chaussalet
1Information System Cluster, Faculty of Management and Organization, Rijksuniversiteit Groningen, Landleven 5, Postbus 800, 9700 AV, Groningen, The Netherlands. n.b.szirbik@rug.nl
International Journal of Medical Informatics
|June 10, 2006
Summary
We present a straightforward methodology for collecting diverse healthcare data and designing central databases, saving implementation time. This approach is also beneficial for interdisciplinary research fields.
Area of Science:
- Healthcare Informatics
- Data Management
- Interdisciplinary Research
Background:
- Developed from a healthcare research project focused on integrating heterogeneous, distributed information sources.
- Methodology refined through experience building a data repository for UK long-term care (LTC) patient flow data.
Purpose of the Study:
- Propose a simple methodology for heterogeneous data collection and central repository database design in healthcare.
- Demonstrate potential for significant implementation effort savings.
- Highlight applicability in other research fields, particularly interdisciplinary ones.
Main Methods:
- A six-step methodology adaptable to iterative development frameworks like the Rational Unified Process (RUP).
- Emphasizes critical requirements identification, data modeling, user/stakeholder interaction, ontology building, quality management, and exception handling.
Main Results:
- Ontological engineering proved highly impactful, facilitating improved collaborative negotiations among stakeholders.
- Enhanced understanding led to better system solutions and win-win outcomes.
- Data collection for decision-making ultimately improves global outcomes.
Conclusions:
- The proposed methodology offers a practical approach to healthcare data management.
- Ontological engineering is a key component for successful collaborative decision-making in data-intensive projects.
- The method's flexibility makes it suitable for diverse research settings.
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