Mental Health Clinical Decision Support Exploiting Big Data

Mental Health Clinical Decision Support Exploiting Big Data

Jan Kalina
DOI: 10.4018/978-1-7998-9023-2.ch048
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The complexity of clinical decision-making is immensely increasing with the advent of big data with a clinical relevance. Clinical decision systems represent useful e-health tools applicable to various tasks within the clinical decision-making process. This chapter is devoted to basic principles of clinical decision support systems and their benefits for healthcare and patient safety. Big data is crucial input for clinical decision support systems and is helpful in the task to find the diagnosis, prognosis, and therapy. Statistical challenges of analyzing big data in psychiatry are overviewed, with a particular interest for psychiatry. Various barriers preventing telemedicine tools from expanding to the field of mental health are discussed. The development of decision support systems is claimed here to play a key role in the development of information-based medicine, particularly in psychiatry. Information technology will be ultimately able to combine various information sources including big data to present and enforce a holistic information-based approach to psychiatric care.
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Developing Clinical Decision Support Systems

Designing and implementing a decision support system is a very complex and demanding process. The usage of decision support systems is strongly dependent on factors of legal, social, technical, economical and ethical environment. If the systems should offer a truly unobtrusive and easy-to-use interface, they must meet the needs of the particular healthcare providers and therefore their introduction requires changing organizational and workflow issues of hospitals as well as their healthcare specialists. Also, it is important to realize that adopting a foreign decision support system typically requires translating the system to the local language together with accommodating all details to the local environment.

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