Mental Health Informatics: Current Approaches
The prevalence of mental disorders among both youths and adults has been growing, e.g., the number of people admitted to mental hospitals and expenditures on mental health related medical expenses have doubled over the past 10 years. Health informatics, t
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Mental Health Informatics: Current Approaches Joachim Diederich and Insu Song
1.1 Introduction According to an AHRQ report [60], mental health disorder is one of the five most costly medical conditions in the U.S., with expenditures almost doubling from 1996 to 2006. The number of people with mental health disorders to a similar degree. This has led to mental illness becoming one of most societies’ largest public health burdens. The major challenges in mental health care can be grouped as follows: (1) availability of health care for remote and underserved population; and (2) making health care more cost-effective and adequate. Developed mental health informatics technologies include traditional information management systems, such as electronic repository of patient information, electronic clinical summaries, and patients’ care plans. These technologies have become critical as network of varying organizations (day hospitals, mental health centres, and small residential units) are involved in the management of mental health patients including chronically disabled patients [30]. One of the main challenges for mental health information management systems is the secure transfer of patient information. Most notable support in the advancement of mental health informatics has come from the Internet, in particular Web 2.0. The massive production of social media enabled by Web 2.0 drives a wealth of clinical knowledge, thereby providing an efficient platform for patients to support each other. According to a 2008 survey, most Americans (up to 80 %) rely on the Internet to find health information in order to make their health care decisions [22]. This trend rivalled physicians as of
J. Diederich (&) School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane Q4072, Australia e-mail: [email protected] I. Song School of Business and IT, James Cook University Australia, Singapore Campus 574421, Singapore e-mail: [email protected]
M. Lech et al. (eds.), Mental Health Informatics, Studies in Computational Intelligence 491, DOI: 10.1007/978-3-642-38550-6_1, Springer-Verlag Berlin Heidelberg 2014
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J. Diederich and I. Song
2008 [56]. An increasing number of patients (and families of patients) are also relying on the Internet for emotional support and to find clinical knowledge for self-care. Slow but steady progress has been made on automated/assisted assessment technologies of mental health ranging from image based automated assessment of stress and anxiety [13], acoustic speech analysis of depressed patients [40, 44], and text analysis for the assessment of autism [59]. We do not expect to see fully automated mental health assessment and treatment systems in the near future, but many clinical trials indicate their potential to be integrated into relatively well established telepsychiatry (e.g., [68]). Except for health social networks (e.g., Health 2.0), which are mainly driven by communities, more extensive and structured clinical trials for quantitative analysis are req
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