Advancing Healthcare Through Data Analytics Transitioning from Descriptive Insights to Predictive and Prescriptive Solutions

Fahim Rahman^1*, Ariful Islam², Sonia Nashid³, Al Akhir², Sonia Khan Papia⁴

This study integrated data analytics transforms healthcare decision-making, improving accuracy, efficiency, and patient-centered outcomes through descriptive, predictive, and prescriptive solutions.

Abstract

Background: The healthcare field stores large digital datasets through its clinical information systems and patient observation systems and diagnostic examination systems and administrative workflows. Healthcare service delivery needs data transformation to create operational knowledge which improves service delivery processes. The transition from traditional reporting systems to predictive and prescriptive reporting systems enables advanced analytics to deliver proactive patient-centered care.

Methods: Researchers studied hospital records from 115 healthcare facilities throughout the 24-month duration that began in January 2024 and ended in December 2025. A three-phase analytical framework was applied. Researchers used descriptive analytics during the initial phase to investigate patterns inpatient admissions and readmissions together with treatment outcomes. Predictive analytics developed readmission prediction models through logistic regression and decision trees while producing patient outcome probability estimations.

Results: The analysis of admission data shows chronic diseases make up 36% of hospital admissions and 42% of these patients return to the hospital within thirty days. The analysis found that 28% of hospital admissions were due to acute infections while surgical complications made up 22% of admissions with 19% of patients returning to the hospital within thirty days. The predictive modeling system showed high predictive ability since logistic regression delivered 83% accuracy but decision trees achieved 87% accuracy together with 82% sensitivity and 84% specificity levels.

Conclusion: The study demonstrates that descriptive analytics explains previous performance while predictive analytics forecasts risks and prescriptive analytics delivers practical solutions.

Keywords: Healthcare analytics, Descriptive insights, Predictive modeling, Prescriptive solutions, Patient outcomes

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