Effect of Financial Analytics on Emergency Care Performance and Health Policy Decision-Making in Healthcare Organizations in Nigeria
1 Rush University Medical Center, Chicago, Illinois, USA.
2 Abia State University, Department of Medicine, Abia, Nigeria.
3 Ajayi Crowther University, School of Business, Oyo, Nigeria.
Research Article
World Journal of Advanced Research and Reviews, 2021, 12(03), 801-819
Publication history:
Received on 17 November 2021; revised on 21 December 2021; accepted on 28 December 2021
Abstract:
Background: This study investigates the effect of financial analytics on emergency care performance and health policy decision-making in public healthcare organizations in Nigeria. Despite advances in medical technology, operational inefficiencies persist, with Nigerian hospitals often experiencing long wait times, inadequate resource allocation, and poor financial management. The study focuses on four key financial analytics capabilities cost analysis, budget forecasting, expenditure tracking, and financial performance dashboards and examines their influence on emergency care outcomes and the quality of health policy decisions. Guided by the Resource-Based View (RBV) and Decision Support Systems (DSS) theory, financial analytics is conceptualized as a strategic resource that enables evidence-based operational and policy decisions.
Methodology: A cross-sectional survey design was employed to target 400 healthcare professionals, financial managers, emergency care managers, and policymakers across six major Nigerian cities representing diverse geopolitical zones. Data was collected using structured questionnaires and analyzed through Structural Equation Modelling (SEM), including Confirmatory Factor Analysis (CFA) to validate measurement models.
Results: Tracking had the highest mean score (M = 3.98; SD = 0.65), indicating relatively strong perceptions or agreement among respondents. This was followed by Cost Analysis (M = 3.85; SD = 0.72) and Budget Forecasting (M = 3.72; SD = 0.78). Constructs such as Financial Dashboards (M = 3.59; SD = 0.83), Emergency Care Performance (M = 3.67; SD = 0.71). Results revealed that cost analysis and budget forecasting significantly improved emergency care performance, whereas expenditure tracking and dashboards strongly influenced the quality of policy decision-making. Emergency care performance mediated the relationship between financial analytics and policy decisions, indicating that operational improvements enhance policy effectiveness. Model fit indices and reliability tests confirmed the robustness of the proposed framework.
Conclusion: The findings underscore the critical role of integrating financial analytics into routine hospital management to optimize resource utilization, improve operational efficiency, and support evidence-based policymaking. Challenges such as inadequate digital infrastructure, poor data quality, and limited skilled personnel were identified as barriers to effective implementation.
Recommendation: The study recommends investment in analytics technology, staff training, governance frameworks, and a strategic financial analytics roadmap to enhance operational efficiency and policy outcomes. These insights provide actionable guidance for administrators and policymakers aiming to strengthen emergency care delivery and decision-making in Nigerian public healthcare systems.
Keywords:
Financial Analytics; Cost- Effectiveness; Resource Allocation; Operational Efficiency; Decision Support Systems
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Copyright © 2021 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0