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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM40624
Volume:
9 |
1 |
Jan 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Government hospitals are the primary healthcare providers to a large population and healthcare accessibility is an important aspect of the public welfare. Serious issues that need solutions are the adequate supply of essential medicines and the distribution of doctors in government hospitals and the framework is a predictive analysis based on this study. The framework analyzes historical data, applies machine learning algorithms, and employs statistical models to uncover patterns and trends that impact availability and resource allocation Future demand and potential shortages are predicted through analyses of critical factors such as patient inflow, disease seasonality, inventory logistics, and staff scheduling The research illustrates how predictive analytics in conjunction with hospital management systems offer actionable insights for administrators. And by forecasting potential shortages in medicines and shortages in health workers, this framework allows for pre-emptive measures to enable consistently delivering services. Accordingly the prediction analytics can provide a significant impact in terms of minimizing the wastage of time and effort which leads to improve the decision making process and keeping up the patient satisfaction which leads the government hospitals to be increased in their workflow. This recent research highlights the invaluable role of data-driven approaches in improving the efficiency and quality of public healthcare systems.
KEYWORDS
Publication Date
8/31/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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The authors declare no conflict of interest related to this research work.
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