[AISWorld] CFP for AMCIS MINI-TRACK: Exploring Unstructured Data Analytics in Healthcare

[Abraham, Chon]

CFP for Mini-Track at AMCIS 2013 (see http://amcis2013.aisnet.org/index.php?option=com_content&view=article&id=61&Itemid=58 )

TRACK: Data Quality and Information Quality, Special Interest Group Information Quality (SIGIQ)
MINI-TRACK: Exploring Unstructured Data Analytics in Healthcare
IMPORTANT DATES
Jan 4, 2013 Paper submissions open via http://aisel.aisnet.org/amcis2013/
Feb 22, 2013 Paper submissions deadline 11:59 p.m. Eastern Time
April 17-19, 2013 Notification of paper acceptance
May 9, 2013 Camera-ready copy of accepted papers due

Instructions for authors and more information about the conference is available on the conference website at http://amcis2013.aisnet.org/.
DESCRIPTION
Organizations are facing an increasing challenge managing and understanding unstructured data. In the healthcare arena, unstructured data is an essential factor in understanding the quality of information presented in electronic health records, how clinicians translate unstructured textual data and act upon it, or how patients understand, interpret and form opinions about healthcare providers. Social media, or the tools and platforms with which "individuals and communities create and share user-generated content" (Wikipedia), are thriving and generate a wealth of information in the form of blogs, Twitter feeds, or review sites. Together, the seemingly endless array of consumer-generated data provides a detailed picture of an organization’s standing in the marketplace. The growing prevalence of social networks, and the role social media plays today, make it necessary for healthcare organizations to "listen" to user-generated information, to make sense of it, and consequently to act upon it.
Analyzing this data is a major challenge due to its unstructured nature, and also because the tools available are in their infancy and have not yet been commonly deployed in organizations. While there is a wide portfolio of data mining and analysis tools available for structured data, a much smaller variety of options are available for data that are unstructured. Unstructured data require a different analytical approach than those traditionally employed, and the exploration of standards and quality issues are necessary to consider when studying the healthcare field. Only lately have the semantic algorithms improved to such an extent that making sense of textual data is becoming a reality. This mini-track will seek to provide an outlet for research and contributions on the effective use of unstructured data analytics in healthcare.
Suggested Topics
Topics for this mini track could include, but are not limited to, the following:

·        Aspects of information quality in healthcare environments, particularly in the context of electronic medical records

·        The various meanings of unstructured data put forth by healthcare providers and/or consumers of services

·        Sentiment analysis of specific services and products as described by organizational members and patients on social media

·        Relationship between firm performance and unstructured data analytics tools

·        Behavioral and cognitive factors that influence the usage of unstructured data analytics

·        Demonstrations of unstructured data analytics tools in form of reviews and tutorials

·        Teaching cases: The usage of unstructured data analytics tools in educational environments
MINI-TRACK CHAIRS
Iris Junglas, Florida State University, ijunglas at cob.fsu.edu<mailto:ijunglas at cob.fsu.edu>
Chon Abraham, College of William and Mary, chon.abraham at mason.wm.edu<mailto:chon.abraham at mason.wm.edu>
TRACK CHAIR
Yang Lee, MIT and Northeastern University, y.lee at neu.edu<mailto:y.lee at neu.edu> or ylee at mit.edu<mailto:ylee at mit.edu>


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