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Knowledge-based treatment planning for adolescent early intervention of mental healthcare: a hybrid case-based reasoning approach



Abstract: Treatment planning is a crucial and complex task in the social services industry. There is an increasing need for knowledge-based systems for supporting caseworkers in the decision-making of treatment planning. This paper presents a hybrid case-based reasoning approach for building a knowledge-based treatment planning system for adolescent early intervention of mental healthcare. The hybrid case-based reasoning approach combines aspects of case-based reasoning, rule-based reasoning and fuzzy theory. The knowledge base of case-based reasoning is a case base of client records consisting of documented experience while that for rule-based reasoning is a set of IF–THEN rules based on the experience of social service professionals. Fuzzy theory is adopted to deal with the uncertain nature of treatment planning. A prototype system has been implemented in a social services company and its performance is evaluated by a group of caseworkers. The results indicate that hybrid case-based reasoning has an enhanced performance and the knowledge-based treatment planning system enables caseworkers to construct more efficient treatment planning in less cost and less time.