Triggers and Monitoring in Intelligent Personal Health Record

Abstract

Although Web-based personal health records (PHRs) have been widely deployed, the existing ones have limited intelligence. Previously, we introduced expert system technology and Web search technology into the PHR domain and proposed the concept of an intelligent PHR (iPHR). iPHR provides personalized healthcare information to facilitate users' daily activities of living. The current iPHR is passive and follows the pull model of information distribution. This paper introduces triggers and monitoring into iPHR to make iPHR become active. Our idea is to let medical professionals pre-compile triggers and store them in iPHR's knowledge base. Each trigger corresponds to an abnormal event that may have potential medical impact. iPHR keeps collecting, processing, and analyzing the user's medical data from various sources such as wearable sensors. Whenever an abnormal event is detected from the user's medical data, the corresponding trigger fires and the related personalized healthcare information is pushed to the user using natural language generation technology, expert system technology, and Web search technology.

Open Issues in Intelligent Personal Health Record – An Updated Status Report for 2012

“…The intelligent personal health record system iPHR is developed following a modular design approach [83,85,91]. Each function of iPHR is implemented as multiple software modules interacting with each other.…”

“…In general, a business or organization in the set R all can be retrieved by more than one search guide phrase in the set C. For each business or organization in R all , we use the methods described in Luo [85] to obtain its snippet, i.e., some words extracted from its profile stored in the local Web search engine.…”

“…These PHR systems enable consumers to actively manage their health records and subsequently their health through a Web interface, but have limited intelligence and can fulfill only a small portion of users' healthcare needs. To improve PHR's capability and usability [105], we have proposed the concept of an intelligent PHR (iPHR) [85,91] by introducing and extending expert system technology, Web search technology, natural language generation technology [117], database trigger technology, and signal processing technology into the PHR domain.…”

“…Since then, three years have passed and more progress has been made with iPHR. At present, our iPHR system provides four functions: (1) guided search for disease information [82], (2) recommending self-care activities (SCAs) [90], (3) recommending home health products [92], and (4) continuous user monitoring [85]. Most of these functions fall into the category of automatically generating personalized healthcare content.…”

“…To overcome this difficulty, an approach similar to the one described in Luo [85] is used. As a rough approximation we assume that this ranking score is inversely proportional to , , , the rank of the business or organization B among all businesses and organizations that the query , retrieves from the local Web search engine.…”