A fusion of machine learning algorithms and traditional statistical forecasting models for analyzing American healthcare expenditure

TY - JOUR

T1 - A fusion of machine learning algorithms and traditional statistical forecasting models for analyzing American healthcare expenditure

AU - Wang, John

AU - Qin, Zhaoqiong

AU - Hsu, Jeffrey

AU - Zhou, Bin

N1 - Publisher Copyright: © 2024 The Author(s)

PY - 2024/6

Y1 - 2024/6

N2 - The American healthcare system allocates considerable resources compared to peer-developed nations. However, outcomes significantly trail behind, particularly in life expectancy. This study addresses questions about the enduring trends in healthcare spending as a percentage of Gross Domestic Product (GDP), notable factors contributing to this concerning trend, and the timing to apply an emergency brake to curb this accelerating trajectory. Advanced machine learning algorithms, such as Random Forest and Support Vector Regression (SVR), in conjunction with traditional statistical forecasting methods, are used to forecast future patterns. The research underscores the importance of healthcare analytics in unraveling the intricacies of the healthcare system. The findings highlight the pressing need for effective policies to confront this mounting challenge.

AB - The American healthcare system allocates considerable resources compared to peer-developed nations. However, outcomes significantly trail behind, particularly in life expectancy. This study addresses questions about the enduring trends in healthcare spending as a percentage of Gross Domestic Product (GDP), notable factors contributing to this concerning trend, and the timing to apply an emergency brake to curb this accelerating trajectory. Advanced machine learning algorithms, such as Random Forest and Support Vector Regression (SVR), in conjunction with traditional statistical forecasting methods, are used to forecast future patterns. The research underscores the importance of healthcare analytics in unraveling the intricacies of the healthcare system. The findings highlight the pressing need for effective policies to confront this mounting challenge.

KW - AutoRegressive integrated moving average

KW - Healthcare analytics

KW - Healthcare expenditure

KW - Random forest

KW - Support vector machine

KW - Support vector regression

UR - https://www.scopus.com/pages/publications/85186634936

U2 - 10.1016/j.health.2024.100312

DO - 10.1016/j.health.2024.100312

M3 - Article

SN - 2772-4425

VL - 5

JO - Healthcare Analytics

JF - Healthcare Analytics

M1 - 100312

ER -