Published in:
Open Access 01-12-2010 | Correspondence
The deployment of a tissue request tracking system for the CHTN: a case study in managing change in informatics for biobanking operations
Published in: BMC Medical Informatics and Decision Making | Issue 1/2010
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Background
Managing change has not only been recognized as an important topic in medical informatics, but it has become increasingly important in translational informatics. The move to share data, together with the increasing complexity and volume of the data, has precipitated a transition from locally stored worksheet and flat files to relational data bases with object oriented interfaces for data storage and retrieval. While the transition from simple to complex data structures, mirroring the transition from simple to complex experimental technologies, seems natural, the human factor often fails to be adequately addressed leading to failures in managing change.
Methods
We describe here a case study in change management applied to an application in translational informatics that touches upon changes in hardware, software, data models, procedures, and terminology standards. We use the classic paper by Riley and Lorenzi to dissect the problems that arose, the solutions that were implemented, and the lessons learned.
Results
The entire project from requirements gathering through completion of migration of the system took three years. Double data entry into the old and new systems persisted for six months. Contributing factors hindering progress and solutions to facilitate managing the change were identified in seven of the areas identified by Riley and Lorenzi: communications, cultural changes in work practice, scope creep, leadership and organizational issues, and training.
Conclusions
Detailed documentation of the agreed upon requirements for the new system along with ongoing review of the sources of resistance to change as defined by Riley and Lorenzi were the most important steps taken that contributed to the success of the project. Cultural changes in tissue collection mandated by standards requirements introduced by the Cancer Bioinformatics Grid (CaBIG®) and excessive reliance on the outgoing system during a lengthy period of dual data entry were the primary sources of resistance to change.