A novel clinical decision support algorithm for constructing complete medication histories. (July 2017) - Long, Ju; Yuan, Michael Juntao
Highlights: We describe an accurate, computationally efficient, and scalable algorithm to construct the medication history timeline. The algorithm is validated based on 1 million random prescription records. The algorithm is suitable for delivery in a cloud-computing environment. The cloud-based medication history computation service could potentially be integrated into electronic medical records. The algorithm could potentially enable informed clinical decision making at the point of care. Abstract: A patient's complete medication history is a crucial element for physicians to develop a full understanding of the patient's medical conditions and treatment options. However, due to the fragmented nature of medical data, this process can be very time-consuming and often impossible for physicians to construct a complete medication history for complex patients. In this paper, we describe an accurate, computationally efficient and scalable algorithm to construct a medication history timeline. The algorithm is developed and validated based on 1 million random prescription records from a large national prescription data aggregator. Our evaluation shows that the algorithm can be scaled horizontally on-demand, making it suitable for future delivery in a cloud-computing environment. We also propose that this cloud-based medication history computation algorithm could be integrated into Electronic Medical Records, enabling informed clinical decision-making at the point of care.