Abstract
Patient satisfaction is a critical criterion for healthcare Customer Relationship Management (CRM). By retrieving and adapting previous similar patient cases, our previous research proposed a case-based prediction model to predict patient satisfaction [3]. The prediction model is useful to forecast the possible patient satisfaction level for a target patient segment. Based on the prediction model, this research further proposes a constraint-based optimization mechanism to determine the optimum values of case features that best approximate the goal of patient satisfaction. The optimization model can help healthcare providers develop appropriate CRM plans to upgrade the satisfaction level for a target patient segment. Two hundred eighty-four real patient cases are collected in the case base for the experiment. The integrated system with both prediction and optimization models can support the decision making of healthcare providers to establish a proactive CRM as well as provide better healthcare services.
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© 2004 Springer-Verlag Berlin Heidelberg
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Hsu, CI., Chiu, C., Hsu, PL. (2004). A Constraint-Based Optimization Mechanism for Patient Satisfaction. In: Negoita, M.G., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2004. Lecture Notes in Computer Science(), vol 3213. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30132-5_124
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DOI: https://doi.org/10.1007/978-3-540-30132-5_124
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23318-3
Online ISBN: 978-3-540-30132-5
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