Inter-case similarity metrics can potentially help find similar cases from a case base for evidence-based practice. While several methods to measure similarity between cases have been proposed, developing an effective means for measuring patient case similarity remains a challenging problem. We were interested in examining how abstracting could potentially assist computing case similarity. In this study, abstracted patient-specific features from medical records were used to improve an existing information-theoretic measurement. The developed metric, using a combination of abstracted disease, finding, procedure and medication features, achieved a correlation between 0.6012 and 0.6940 to experts.
Bibliographical noteFunding Information:
This research was funded by National Library of Medicine R01 LM06910 “Discovering and applying knowledge in clinical databases”. Dr. Markatou was supported by Grant NSF-DMS-0504957 from the National Science Foundation. We acknowledge Dr. Pamela Tarrazona-Yu at Western Queens Health Associates for her help in the reliability study for the evaluation of metrics.
- Case similarity
- Case-based reasoning
- Patient feature