From Data to Knowledge: Discovery of Medical Laboratory Demand Patterns Using Social Network Analysis [STUDY]

This new study is part of the Social Media Lab’s Organizational Networks Research Initiatives. Projects under this initiative use data visualization techniques and social network analysis to advance our understanding of complicated issue facing our community such as rising demand for  health care services. The abstract to the paper and the companion poster* is below.

 Abstract:

This research uses data visualization techniques and social network analysis to determine the status and efficiency of laboratory ordering for the outpatient system in Nova Scotia, Canada. Currently, the Capital District Health Authority (CDHA) model demonstrates that approximately 60% of laboratory ordering originates in the outpatient setting and is costing the province approximately $3.3 million per month. The goal of this pilot project is to turn the vast amount of data in the CDHA’s laboratory information system into usable information and allow the CDHA to identify usage trends to better understand the future demands on lab testing and allow policymakers more insight into the Nova Scotia primary care landscape.

(* This poster recently won the Best Poster Award at the iConference ’12 in Toronto. A copy of the short conference paper is available in the Conference Proceedings)

View more presentations from Anatoliy Gruzd.
This research has been presented at both the 2012 ALISE Annual Conference and the iConference ’12 and was funded by Mitacs and the Capital District Health Authority (CDHA). We also thank the CDHA Pathology Informatics Group for assisting in the data extraction and verification process.

Citation:
Conrad Ng, Anatoliy Gruzd, Calvino Cheng, Bryan Crocker, Don Doiron, and Kent Stevens (2012). From data to knowledge: discovery of medical laboratory demand patterns through visualisation techniques Proceedings of the 2012 iConference (iConference ’12). ACM, New York, NY, USA, 585-586 : 10.1145/2132176.2132298

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