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With patients responsible for an increasing amount of their healthcare costs, self-pay accounts are now the top contributor to bad debt for hospitals and health systems—accounting for more than $55 billion annually. A predictive model that could successfully support a propensity to pay strategy. The propensity to pay machine learning model uses artificial intelligence to predict the probability that the patient will pay their bill during the month


The propensity to pay machine learning predictive model, in conjunction with propensity to pay strategy, allows the finance team to focus its collection efforts on patients who are more likely to pay. Resources are not allocated to collecting from patients that will either pay their balances without intervention or not pay their bills regardless of interventions

Business Value

This solution allows clients to make the best use of its limited resources, increasing payments for the services provided and improves remittance process efficiency. It also enhances customer service and improve accuracy levels. Remits AI solution

H2O's AI and Data Approaches

This solution is powered by the H2O AI Cloud Driverless AI AutoML, H2O-3, and Wave. The data science approaches include genetic algorithm, advanced feature engineering, classification algorithms, GLM, GBM, XGBoost, ensemble stacking, and various machine learning interpretability algorithms



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