Abstract
Organizations across industry sectors continue to develop data resources and utilize analytic techniques to enhance efficiencies in their operations. One example of this is evident as Managed Care Organizations (MCOs) enhance their care and disease management initiatives through the utilization of population segmentation techniques. This article proposes a classification system for population segmentation techniques for care and disease management and provides an evaluation process for each. The three proposed operational areas for Managed Care Organizations are: 1) Risk Status: early identification of high-risk patients, 2) Treatment Status: compliance with treatment protocols, and 3) Health Status: severity of illness or episodes of care groupings, all of which require particular analytic methodologies to leverage data resources. By applying this classification system an MCO can improve its ability to clarify internal goals for population segmentation, more accurately apply existing analytic methodologies, and produce more appropriate solutions.
Original language | English (US) |
---|---|
Pages (from-to) | 21-31 |
Number of pages | 11 |
Journal | International Journal of Healthcare Information Systems and Informatics (IJHISI) |
Volume | 3 |
Issue number | 2 |
DOIs | |
State | Published - Apr 2008 |
All Science Journal Classification (ASJC) codes
- Medicine (miscellaneous)
- Information Systems
- Information Systems and Management
Keywords
- data mining
- healthcare produtivity
- informatic
- quantitative analytics