Avoidable hospitalizations are the subject of considerable interest to decision makers, because such admissions are deemed to be expensive, unhelpful to patients, and reflect underperformance of health systems’ organization [2–7]. Hospitalizations that might have been averted by health service interventions for older people are of particular concern. This chapter examines the nature of the problem and limitations of current approaches. It identifies the need for a comprehensive conceptual framework that addresses the complex human systems of aging, being ill, and dying in contemporary society. Avoidable hospitalizations conceptualized as reflecting biological, psychosocial, organizational, and social phenomena opens up a complex adaptive systems approach to the problematical issue of hospitalizations for older people. It focuses on the current and potential contributions of informatics and computational science to this field. A real-time informatics system based on patients’ narratives of their wellness and illness: the Patient Journey Record system provides an example of an adaptive system that addresses avoidable hospitalizations using a complex systems framework.
- Machine Learn
- Natural Language Processing
- Complex Adaptive System
- Personal Narrative
- Patient Journey
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One unintended outcome of the modern transformation of the medical care system is that it does just about everything to divert the practitioner’s attention away from the experience of illness.
Arthur Kleinman 
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The “one” right answer principle reflects the classical Newtonian cause-and-effect model.
Natural language processing, as a discipline, is also known as natural language engineering and human language technology. NLP in this sense is not to be confused with neuro-linguistic programming.
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Martin, C.M. et al. (2013). Avoidable Hospitalizations in Older Adults. In: Sturmberg, J., Martin, C. (eds) Handbook of Systems and Complexity in Health. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-4998-0_27
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