Feedback analytics for indication search and user profiling

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MedCurrent Corporation is a rapidly growing Toronto-based company that develops Health IT Clinical Decision Support Software (CDS). One major problem the company is facing is the performance of the indication search, which is a crucial step for recommending proper medical procedures. In the current system, a physician enters medical indications (e.g. headache) via free-text, and the system prompts with a list of matching indications. If no matching can be found, the entered texts will be saved into the system. Later all the unmatched texts will be analyzed manually to be either added into the pre-defined indication database or discarded. This process is essential to improve the hit ratio of the indication search. However, it is very costly and inefficient. Another problem of the current system is that there is no built-in learning process so that the searching and recommendation can benefit from previous results. In this project, we propose to apply the data analytics and information retrieval techniques to improve the indication search as well as the overall system effectiveness. We would use existing domain corpora and the query logs the system has collected to build a domain-specific thesaurus to increase the chance of finding the matched indications. For the unmatched free-text indications, we would apply proper information retrieval mechanisms to find the best matching existing indications using multiple data sources to alleviate the future manual inspection process. We would also use the collected log data to build user profiles to personalize the indication search and recommendation process for individual users and to generate an analytic report for the client (e.g., hospital), identifying various usage patterns. The proposed project will benefit Canada's health sector by improving the decision support process for ordering medical procedures and giving insights to hospitals on how the rules and guidelines are being followed by the medical practitioners. It would also help MedCurrent optimize their current clinical support software and consequently provide improved experience for their customers.