published_or_final_version / abstract / toc / Computer Science and Information Systems / Master / Master of Philosophy

published_or_final_version / abstract / toc / Computer Science and Information Systems / Master / Master of Philosophy

published_or_final_version / Computer Science / Master / Master of Philosophy

published_or_final_version / Computer Science and Information Systems / Master / Master of Philosophy

published_or_final_version / Computer Science and Information Systems / Master / Master of Philosophy

Poster paper / The latest developments in Information and Communication Technologies (ICT) have made the concept "Libraries without walls" into a practical reality. This has posed several challenges to the information work force and the information users. At the same time, we have noticed the issues related to the information overload and information quality. At this juncture, efforts are strengthening to develop means to persuade and equip the users and information specialists to achieve maximum efficiency in information services. It was observed that one of the important reasons for the under utilization of electronic information is the lack of requisite level of working knowledge and consumption skills among customers and information intermediaries (Sridhar, 1997). To improve the situation, the conventional user education programmes need be redefined and reengineered, to be it more technology oriented. It should be designed in such a way to provide confidence to the user in locating desired information (Francis, 2005).

Artificial Intelligence Lab, Department of MIS, University of Arizona / As in many other applications, the rapid proliferation and unrestricted Web-based publishing of health-related content have made finding pertinent and useful healthcare information increasingly difficult. Although the development of healthcare information retrieval systems such as medical search engines and peer-reviewed medical Web directories has helped alleviate this information and cognitive overload problem, the effectiveness of these systems has been limited by low search precision, poor presentation of search results, and the required user search effort. To address these challenges, we have developed a domain-specific meta-search tool called Cancer Spider. By leveraging post-retrieval document clustering techniques, this system aids users in querying multiple medical data sources to gain an overview of the retrieved documents and locating answers of high quality to a wide spectrum of health questions. The system presents the retrieved documents to users in two different views: (1) Web pages organized by a list of key phrases, and (2) Web pages clustered into regions discussing different topics on a two-dimensional map (self-organizing map). In this paper, we present the major components of the Cancer Spider system and a user evaluation study designed to evaluate the effectiveness and efficiency of our approach. Initial results comparing Cancer Spider with NLM Gateway, a premium medical search site, have shown that they achieved comparable performances measured by precision, recall, and F-measure. Cancer Spider required less user searching time, fewer documents that need to be browsed, and less user effort.

This colorful tri-fold brochure may be freely reproduced.

Rheumatoid arthritis (RA) is a chronic, destructive, inflammatory arthritis that places significant burden on the individual and society. This thesis represents the most comprehensive effort to date to determine the accuracy of administrative data for detecting RA patients; and describes the development and validation of an administrative data algorithm to establish a province-wide RA database. Beginning with a systematic review to guide the conduct of this research, two independent, multicentre, retrospective chart abstraction studies were performed amongst two random samples of patients from rheumatology and primary care family physician practices, respectively. While a diagnosis by a rheumatologist remains the gold standard for establishing a RA diagnosis, the high prevalence of RA in rheumatology clinics can falsely elevate positive predictive values. It was therefore important we also perform a validation study in a primary care setting where prevalence of RA would more closely approximate that observed in the general population. The algorithm of [1 hospitalization RA code] OR [3 physician RA diagnosis codes (claims) with ≥1 by a specialist in a 2 year period)] demonstrated a high degree of accuracy in terms of minimizing both the number of false positives (moderately good PPV; 78%) and true negatives (high specificity: 100%). Moreover, this algorithm has excellent sensitivity at capturing contemporary RA patients under active rheumatology care (>96%). Application of this algorithm to Ontario health administrative data to establish the Ontario RA administrative Database (ORAD) identified 97,499 Ontarians with RA as of 2010, yielding a cumulative prevalence of (0.9%). Age/sex-standardized RA prevalence has doubled from 473 per 100,000 in 1996 to 784 per 100,000 in 2010, with approximately 50 new cases of RA emerging per 100,000 Ontarians each year. Our findings will inform future population-based research and will serve to improve arthritis surveillance activities across Canada and abroad.

Rheumatoid arthritis (RA) is a chronic, destructive, inflammatory arthritis that places significant burden on the individual and society. This thesis represents the most comprehensive effort to date to determine the accuracy of administrative data for detecting RA patients; and describes the development and validation of an administrative data algorithm to establish a province-wide RA database. Beginning with a systematic review to guide the conduct of this research, two independent, multicentre, retrospective chart abstraction studies were performed amongst two random samples of patients from rheumatology and primary care family physician practices, respectively. While a diagnosis by a rheumatologist remains the gold standard for establishing a RA diagnosis, the high prevalence of RA in rheumatology clinics can falsely elevate positive predictive values. It was therefore important we also perform a validation study in a primary care setting where prevalence of RA would more closely approximate that observed in the general population. The algorithm of [1 hospitalization RA code] OR [3 physician RA diagnosis codes (claims) with ≥1 by a specialist in a 2 year period)] demonstrated a high degree of accuracy in terms of minimizing both the number of false positives (moderately good PPV; 78%) and true negatives (high specificity: 100%). Moreover, this algorithm has excellent sensitivity at capturing contemporary RA patients under active rheumatology care (>96%). Application of this algorithm to Ontario health administrative data to establish the Ontario RA administrative Database (ORAD) identified 97,499 Ontarians with RA as of 2010, yielding a cumulative prevalence of (0.9%). Age/sex-standardized RA prevalence has doubled from 473 per 100,000 in 1996 to 784 per 100,000 in 2010, with approximately 50 new cases of RA emerging per 100,000 Ontarians each year. Our findings will inform future population-based research and will serve to improve arthritis surveillance activities across Canada and abroad.