Abstract
This study examines data mining as an extension of system design to support continuous process improvement. This paper identifies how dynamic technological activities of synthesis, analysis, and evaluation can highlight complex relationships within integrated information systems through existing patterns of associated organizational data. The identification of data patterns and subsequent human contextual understanding are contributing factors that yield business process redesign opportunity and re-enforce continuous process improvement within the perioperative services of a hospital. Based on a 72- month longitudinal study of a large 909 registered-bed teaching hospital, this case study investigates the operationalization of data mining in business process redesign as a method to identify, qualify, understand, and capture benefits from continuous process improvement. The theoretical and practical implications and/or limitations of this study’s results are also discussed with respect to practitioners and researchers alike.
Recommended Citation
Ryan, Jim; Doster, Barbara; Daily, Sandra; and Lewis, Carmen, "Mining Perioperative Data for Business Process Analysis and Redesign: A Case Study Perspective" (2010). AMCIS 2010 Proceedings. 561.
https://aisel.aisnet.org/amcis2010/561