A life sciences company sought to gain a granular understanding of coronary artery disease patients in order to inform its value argument around a diagnostic imaging modality.
Decision Resources Group assembled a team of experts to:
- Define initial patient segments according to relevant clinical practices
- Identify additional potential criteria for patient segmentation using machine learning
- Refine patient segments to include all factors impacting downstream utilization
- Execute patient journey analysis, following patients pre- to post-diagnostic test
- Perform comparative analysis on post-test utilization for matched
The results enabled the client to evaluate downstream effects of each test, and confirmed their hypothesis: that some patients respond better to certain tests, and demonstrate lower downstream utilization as a result