Data-Driven Decision Making for Effective Resource Management in Healthcare

  • Authors

    • Dr. R. Kartikeyan Associate Professor, Anna University, Chennai, India. Author

    DOI:

    https://doi.org/10.67228/30713498/IJADSMC-2018PII9L7W

    Published 07-04-2018

  • Data-Driven Decision Making (DDDM), Healthcare Resource Management, Predictive Analytics, Healthcare Operations, Patient Flow Management, Inventory Management, Healthcare Workforce Optimization, Cost Reduction in Healthcare, Artificial Intelligence in Healthcare, Data Analytics in Healthcare

    Issue

    Vol. 1 No. 2 (2018)

    Section

    Articles

    How to Cite

    [1]
    K. R, “Data-Driven Decision Making for Effective Resource Management in Healthcare”, IJADSMC, vol. 1, no. 2, pp. 01–14, Jul. 2018, doi: 10.67228/30713498/IJADSMC-2018PII9L7W.

  • Abstract

    In healthcare, efficient resource management is critical to ensuring the sustainability of services and the quality of care provided to patients. Data-driven decision making (DDDM) has emerged as a powerful tool to address the challenges posed by limited resources, rising patient demand, and operational inefficiencies. This paper explores the role of data analytics in enhancing healthcare resource management by focusing on key areas such as human resources, inventory management, patient flow, and financial planning. Through case studies and real-world applications, the paper highlights how data-driven approaches can optimize the allocation of resources, improve operational efficiencies, and lead to significant cost savings. The paper concludes with insights into the future of healthcare resource management, emphasizing the potential of emerging technologies like artificial intelligence, machine learning, and real-time data integration to transform healthcare operations and improve patient care outcomes.

  • References

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