Abstract
Accurately predicting patient expenditure in healthcare is an important task with many applications such as provider profiling, accountable care management, and capitated medical payment adjustment. Existing approaches mainly rely on manually designed features and linear regression-based models, which require massive medical domain knowledge and show limited predictive performance. This paper proposes a multi-view deep learning framework to predict future healthcare expenditure at the individual level based on historical claims data. Our multi-view approach can effectively model the heterogeneous information, including patient demographic features, medical codes, drug usages, and facility utilization. We conducted expenditure forecasting tasks on a real-world pediatric dataset that contains more than 450,000 patients. The empirical results show that our proposed method outperforms all baselines for predicting medical expenditure. These findings help toward better preventive care and accountable care in the healthcare domain.
Highlights
The increasing healthcare expenditures represent a significant challenge to healthcare providers and care organizations
This paper proposes a multi-view deep learning framework to capture the heterogeneous information within claims data
We demonstrate that the proposed multi-view deep learning framework achieves promising model performance for expenditure prediction compared to various baselines on a large pediatric claims data
Summary
The increasing healthcare expenditures represent a significant challenge to healthcare providers and care organizations. As reported by the Centers for Medicare & Medicaid Services (CMS), the national health expenditure (NHE) for the United States grew 4.6% to $3.6 trillion in 2018 (i.e., $11,172 per person) and accounted for 17.7% of Gross Domestic Product (GDP). Medicare spending grew 6.4% to $750.2 billion, and Medicaid grew by 3.0% to $597.4 billion.. The healthcare system is likely to become unsustainable unless medical cost growth is kept in check [1]. It is imperative to control the healthcare expenditure increase and reduce the medical cost for each individual. A special kind of Electronic Health Records (EHR) mainly for billing purposes, contains longitudinal patient health records including demographics, diagnoses, procedures, medications, facility usages, and expenditures.
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