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Abstract
The healthcare revenue cycle in the United States refers to the financial process that healthcare providers follow to manage patient payments, from the moment a patient makes an appointment to the resolution of any outstanding balances. The complex billing systems, reimbursement variability, regulatory changes, and patient demographics make the revenue predictions for a hospital way more complex than any other industry. This study uses 28 variables related to patient demographics, visit characteristics, and payor attributes to develop a predictive model for understanding and forecasting Payment-to-ratio PCR trends. A descriptive analysis of the first and the last quarters of the data was conducted for 6 variables and their effect was studied. Multiple machine-learning methods were used, and the decision tree regression had the best performance resulting in a testing R-squared equal to 72%.
Keywords
The healthcare revenue cycle, Machine Learning, Revenue Prediction.
1. Introduction
The healthcare revenue cycle in the United States refers to the financial process that healthcare providers follow to manage patient payments, from the moment a patient makes an appointment to the resolution of any outstanding balances. Each phase plays a crucial role in ensuring the smooth flow of revenue while addressing the complexities of the healthcare billing system.
The revenue cycle initiates with the crucial step of patient registration. This stage involves gathering comprehensive demographic and insurance information and creating a foundation for accurate billing and reimbursement. As patients receive care, Accurate documentation of services rendered, including procedures, tests, and treatments, is essential for generating precise bills. Following the provision of healthcare services, the hospital must submit claims to insurance providers for reimbursement. This phase involves translating the documented services into billing codes and adhering to standardized coding systems.
Denials from insurance providers can pose challenges to the revenue cycle. Effective denial management involves identifying and rectifying claim discrepancies promptly. By addressing denials systematically, healthcare facilities can mitigate financial losses, optimize revenue recovery, and enhance overall revenue cycle performance. Patient statements communicate financial obligations to individuals. And finally reporting mechanisms within the revenue cycle offer insights into key performance indicators, financial trends, and areas for improvement. Comprehensive reporting allows healthcare institutions to analyze their revenue cycle efficiency, identify bottlenecks, and implement strategic enhancements to optimize financial outcomes.
2. Problem Description