Quantifying Financial Impact of Hospital Readmissions Using Clinical Severity and Resource Utilization Analytics

Author

Akpos Janet

Abstract

 Hospital readmissions impose substantial clinical and economic burdens on healthcare systems by increasing bed occupancy, diagnostic activity, treatment intensity, staffing demands, and overall expenditure. Conventional readmission metrics frequently emphasize rates and frequencies without adequately accounting for differences in patient complexity, clinical severity, and resource consumption. This study develops an integrated analytical framework for quantifying the financial impact of hospital readmissions by combining clinical severity indicators, healthcare resource utilization, and patient-level cost information. Clinical characteristics, comorbidity burden, complications, length of stay, intensive-care utilization, procedures, diagnostic services, medications, and repeated admissions are transformed into severity and resource-intensity features. These measures are integrated with observed expenditure to estimate severity-adjusted readmission costs and identify financially consequential patient profiles. Statistical and predictive models evaluate relationships among clinical complexity, resource consumption, and financial outcomes, while benchmarking determines whether integrated models improve cost estimation compared with conventional approaches. The framework enables differentiation between frequent low-resource readmissions and clinically complex, resource-intensive episodes generating disproportionate expenditure. This approach supports targeted readmission management, financial-risk stratification, resource allocation, and evidence-based hospital decision-making while preserving the distinction between economic burden and clinical care requirements.

Keywords

Hospital Readmissions; Clinical Severity; Healthcare Costs; Resource Utilization; Financial Impact Analytics; Predictive Modeling

DOI : https://doi.org/10.5281/zenodo.22767422

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References

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