RESEARCH/R&D

Natural Language Processing

Consumer Health Question Answering

Research Area: Natural Language Processing

Researchers: Dina Demner-Fushman

Project link: http://chqa.nlm.nih.gov

The consumer health question answering project was launched to support NLM customer services that receive about 90,000 requests a year from a world-wide pool of customers. The requests are categorized by the customer support services staff and are either answered using about 300 stock answers (with or without modifications) or researched and answered by the staff manually. Responding to a customer with a stock reply takes approximately 4 minutes; answering with a personalized stock reply takes about 10 minutes. To reduce the time and cost of customer services, NLM launched the Consumer Health Information and Question Answering (CHIQA) project. The CHIQA project conducts research in both the automatic classification of customers’ requests and the automatic answering of consumer health questions.

The analysis of the requests identified subsets of reference questions that could be answered automatically. LHC researchers have developed a customer service support system that categorizes the incoming requests and prepares answers for review by staff responding to customer requests. The system combines sophisticated statistical methods with knowledge-based natural language processing techniques.The pilot system was integrated in customer services workflow in May 2014. As the system matures, it could immediately provide answers to customers while they are visiting NLM Web pages.

Consumer Health Question Answering workflow.