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Smart health and wellbeing [Trends & Controversies]
September/October 2011 (vol. 26 no. 5)
pp. 78-90
Hsinchun Chen, Artificial Intelligence Lab, University of Arizona, AZ, USA
In light of such overwhelming interest from governments and academia in adopting and advancing IT for effective healthcare, there are great opportunities for researchers and practitioners alike to invest efforts in conducting innovative and high-impact healthcare IT research. This IEEE Intelligent Systems Trends and Controversies (T&C) Department hopes to raise awareness and highlight selected recent research that helps move us toward such goals. This department includes three articles on Smart Health and Wellbeing from distinguished experts in computer science, information systems, and medicine. Each article presents unique perspectives, advanced computational methods, and selected results and examples.

1. Nat'l Research Council, Computational Technology for Effective Health Care: Immediate Steps and Strategic Directions, Nat'l Academy Press, 2009.
2. Inst. of Medicine, To Err Is Human: Building a Safer Health System, Nat'l Academy Press, 2000.
3. G. Anderson and P. Markovich, Multinational Comparisons of Health Systems Data, The Commonwealth Fund, 2009.
4. G. Fairclough, "In China, Rx for Ailing Health System," Wall Street J.,15 Oct. 2009, p. A1; http://online.wsj.com/articleSB125556557369186287.html .
5. Nat'l Academy of Eng., Grand Challenges for Engineering, 2008; www.engineeringchallenges.org/cmschallenges.aspx .
1. G. Anderson and P. Markovich, Multinational Comparisons of Health Systems Data, The Commonwealth Fund, 2009.
2. T.K. Landauer, The Trouble With Computers: Usefulness, Usability, and Productivity, MIT Press, 1995.
3. President's Council of Advisors on Science and Technology (PCAST), Realizing the Full Potential of Health Information Technology To Improve Healthcare for Americans: The Path Forward, Executive Office of the President, 2010.
4. Inst. of Medicine, Digital Infrastructure for the Learning Health System: The Foundation for Continuous Improvement in Health and Health Care: Workshop Series Summary, Nat'l Academies Press, 2011.
5. L. Northrop et al., Ultra-Large-Scale Systems: The Software Challenge of the Future, Software Eng. Inst., Carnegie Mellon Univ., 2006.
6. A. Bandura, "Self-Efficacy in Health Functioning," Cambridge Handbook of Psychology, Health and Medicine, 2nd ed., S. Ayers et al., eds., Cambridge Univ. Press, 2007.
7. C. Chen et al., , "The Kaiser Permanente Electronic Health Record: Transforming and Streamlining Modalities of Care," Health Affairs, vol. 28, no. 2, 2009, pp. 323–333.
1. S.T. Rosenbloom et al., "Data from Clinical Notes: A Perspective on the Tension Between Structure and Flexible Documentation," J. Am. Medical Informatics Assoc., vol. 18, no. 2, 2011, pp. 181–186.
2. D.A. Hanauer, D.R. Rhodes, and A.M. Chinnaiyan, "Exploring Clinical Associations Using '-omics' Based Enrichment Analyses," PLoS One, 2009;4(4):e5203.
3. D. Patnaik et al., "Experiences with Mining Temporal Event Sequences from Electronic Medical Records: Initial Successes and Some Challenges," Proc. 17th ACM SIGKDD Int'l Conf. Knowledge Discovery and Data Mining (KDD 11), 2011.
4. US Food and Drug Administration, "FDA Review Indicates Possible Association between Breast Implants and a Rare Cancer,"26 Jan. 2011; www.fda.gov/NewsEvents/Newsroom/PressAnnouncements ucm241090.htm.
5. US Food and Drug Administration, "FDA Significantly Restricts Access to the Diabetes Drug Avandia," 23 Sept. 2010; www.fda.gov/NewsEvents/Newsroom/PressAnnouncements ucm226975.htm.
1. E.J. Thomas et al., "Incidence and Types of Adverse Events and Negligent Care in Utah and Colorado," Medical Care, vol. 38, no. 3, 2000, pp. 261–271.
2. R. Agrawal, T. Imieliński, and A. Swami, "Mining Association Rules Between Sets of Items in Large Databases," ACM SIGMOD Record, vol. 22, no. 2, 1993, pp. 207–216.
3. A. Wright, E.S. Chen, and F.L. Maloney, "An Automated Technique for Identifying Associations Between Medications, Laboratory Results and Problems," J. Biomedical Informatics, vol. 43, no. 6, 2010, pp. 891–901.
4. G.D. Schiff and D.W. Bates, "Can Electronic Clinical Documentation Help Prevent Diagnostic Errors?" New England J. Medicine, vol. 362, no. 12, 2010, p. 1066.

Index Terms:
Biomedical monitoring,Medical services,Diseases,Visualization,Medical information systems,Data mining,visualization,Intelligent systems,NSF,Smart Health and Wellbeing,healthcare,health IT,digital infrastructure,data mining,electronic health records
Citation:
Hsinchun Chen, "Smart health and wellbeing [Trends & Controversies]," IEEE Intelligent Systems, vol. 26, no. 5, pp. 78-90, Sept.-Oct. 2011, doi:10.1109/MIS.2011.91
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