OPERATIONALIZING BUSINESS ANALYTICS IN HOSPITAL MANAGEMENT

Abstract

While the theoretical benefits of business analytics (BA) in healthcare are well-
documented, hospitals continue to struggle with a persistent implementation gap: fragmented IT
infrastructure, unresolved data interoperability, mounting regulatory compliance demands, and
systemic workforce resistance prevent the full operationalization of predictive, real-time, and AI-
driven analytics. This study presents an integrated, actionable framework — the Hospital Analytics
Operationalization Model (HAOM) — designed to guide healthcare institutions through a structured,
phased transition from data-aware to analytics-driven management. Drawing on a multi-site mixed-
methods investigation across twelve hospitals of varying resource levels in Nigeria and the United
States, the research identifies five critical failure modes that obstruct BA adoption and proposes
evidence-based interventions for each. The findings demonstrate that hospitals deploying the HAOM
framework achieved statistically significant improvements in resource utilization efficiency (mean:
23.4%), readmission rate reductions (mean: 17.8%), and administrative cost savings (mean: 19.2%)
within 18 months of structured implementation. The study further introduces a tiered analytics
readiness index (ARI) that enables hospitals — including those in low-resource settings — to self-
assess their implementation stage and identify prioritized investment pathways. This paper
contributes a practical, reproducible implementation blueprint to the healthcare analytics literature,
addressing the critical gap between BA's documented potential and its real-world deployment across
diverse hospital environments.