Abstract
There has been an emerging interest in managing healthcare cost in the time of value-based care. However, many challenges arise in analyzing high-dimensional healthcare operational data and identifying actionable opportunities for cost saving in an effective way. In this paper, we proposed a comprehensive analytic pipeline for healthcare operational data and designed the Cost and Care Insight, an interactive and scalable hierarchical learning system for identifying cost saving opportunities, which provides attributable and actionable insights in improving healthcare management. This interactive system was built and tested on operational data from more than 750 facilities in ActionOI, a service assisting operational and performance evaluation in a realistic context. Here we introduce the design and framework of the system and demonstrate its use through a case study in the nursing department.
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Acknowledgement
The author wise to thank D.K for his expertise on dealing with healthcare operational data and his advice on study design as well as data analyses. The author also thanks M.J for her guidance in this project.
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Zhang, Y. et al. (2022). Cost and Care Insight: An Interactive and Scalable Hierarchical Learning System for Identifying Cost Saving Opportunities. In: Huang, DS., Jo, KH., Jing, J., Premaratne, P., Bevilacqua, V., Hussain, A. (eds) Intelligent Computing Theories and Application. ICIC 2022. Lecture Notes in Computer Science, vol 13393. Springer, Cham. https://doi.org/10.1007/978-3-031-13870-6_60
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DOI: https://doi.org/10.1007/978-3-031-13870-6_60
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