Delivering the Power of Data-Driven Decisions: An AI-Enabled Data Strategy Framework for Healthcare Financial Systems

Abstract

A universal AI-based data approach framework has been proposed that will enable achieving a data-rich decision in healthcare financial systems. The growing needs of cost optimization, correctness of reimbursements, adherence to the rules, and efficiency of the operations in the healthcare organizations put traditional data management methods in a poor position. The proposed architecture brings together artificial intelligence, metadata-driven architecture, and a convergent data integration pipeline and cloud-native analytics to transform fragmented financial data into operational intelligence. Architecturally, the framework applies a hybrid architectural platform such as knowledge graphs, machine-learned data quality engines, automatic lineage tracking, and semantic enrichment of data processes to make it reliable and consistent. Exception management, including the Internal Controls Exception Dashboard, is one of the fundamental functions that allow the users of Medicare Administrative Contractor (MAC) to see unapplied receipt exceptions, implement corrective actions, and eliminate the use of manual spreadsheets. Predictive analytics and generative AI models assist in real-time predictions, the optimization of the revenue cycle, the detection of fraud, and the mitigation of financial risks. Testing on synthetic healthcare finance data demonstrated that data consistency was improved by 38 percent, data processing latency was reduced by 42 percent, forecasting and cost variance accuracy was enhanced by 55 percent, compliance monitoring has gone up by 60 percent, and manual data preparation has been reduced by 45 percent. Overall, the results indicate that AI-enhanced data strategy, exception management, and automated dashboards can possibly enhance operational agility, financial visibility, and strategic decision intelligence multiple times, as well as provide a future-proof, scalable architecture of advanced analytics in healthcare finance.