Consumers face barriers when seeking health information on the Internet. A Personalized Health Information Retrieval System (PHIRS) is proposed to recommend health information for consumers. The system consists of four modules: (1) User modeling module captures user inverted exclamation mark s preference and health interests; (2) Automatic quality filtering module identifies high quality health information; (3) Automatic text difficulty rating module classifies health information into professional or patient educational materials; and (4) User profile matching module tailors health information for individuals. The initial results show that PHIRS could assist consumers with simple search strategies.