We propose a simulation approach to examine which patient characteristics a protocol “captures” and integrates. Several patient characteristics (see ) influence warfarin outcomes. When a protocol captures important characteristics and accurately integrates them, patients displaying these characteristics will receive effective individualized treatment. Consequently, TTR variation between patients with these characteristics will be low.
We note that a protocol integrating important characteristics does not guarantee the protocol to have a high overall TTR. More complex issues such as the number of integrated characteristics, the weights of these characteristics, and interaction among characteristics should be considered. Rather it indicates people with these characteristics can equally benefit from the protocol, showing similar TTR measurements.
The simulation framework can identify patient sub-populations (when treated based on a certain protocol) that tend to have poor outcomes. Precautions can then be taken to reduce the chance of having a poor outcome in these sub-populations.
This proposed method merges three distinctive knowledge sources; dosing protocols, an INR model, and EMRs, and integrates them into the simulation framework for knowledge discovery. The three knowledge sources, which exist in various forms, provide different aspects of information: protocols, which exist in the forms of tables and algorithms, guide warfarin dosing; the INR model, which exists in the form of a complex two-compartment model, predicts dynamic INR measurements; finally, PharmGKB, EMR data provides patient characteristics and their interactions needed for the INR model and protocol predictions which generate TTR and facilitate the discovering process. This project demonstrates that a sophisticated simulation algorithm can discover valuable clinical knowledge from mixed types of data sources.
Each element in the proposed approach is highly modularized. One can easily replace the PharmGKB data, INR model, or protocol for other research purposes. In addition, we can use this simulation platform to examine which characteristics a newly designed warfarin protocol is able to capture and compare advantages and disadvantages among other existing protocols.
Future work will expand the current work to a large number of protocols and allow for protocol comparison. We also plan to use different INR models, compare them, and further improve the simulation platform. More importantly, we will refine the platform to support comparative effectiveness research that allows comparison of not only TTR but also other outcome metrics, such as bleeding and thrombosis risks, and treatment costs.