IMPORTANCE: Quantifying patient-physician cost conversations is challenging but important as out-of-pocket spending by US patients increases and patients are increasingly interested in discussing costs with their physicians.
The Journal of foot and ankle surgery : official publication of the American College of Foot and Ankle Surgeons
Feb 23, 2019
Ankle fractures are common orthopedic injuries with favorable outcomes when managed with open reduction and internal fixation (ORIF). Several patient-related risk factors may contribute to poor short-term outcomes, and machine learning may be a valua...
BACKGROUND: This paper studies the temporal consistency of health care expenditures in a large state Medicaid program. Predictive machine learning models were used to forecast the expenditures, especially for the high-cost, high-need (HCHN) patients.
Studies in health technology and informatics
Aug 7, 2025
Chronic non-cancer pain (CNCP) is a major health concern in the United States, incurring substantial healthcare costs and frequently requiring opioid therapy in primary care. This retrospective cross-sectional study used Medicaid claims data from six...
OBJECTIVE: The objective of this study was to leverage machine learning techniques to analyze administrative claims and socioeconomic data, with the aim of identifying and interpreting the risk factors associated with high-dose opioid prescribing.
In 2008, Oregon expanded its Medicaid program using a lottery, creating a rare opportunity to study the effects of Medicaid coverage using a randomized controlled design (Oregon Health Insurance Experiment). Analysis showed that Medicaid coverage low...
The Journal of bone and joint surgery. American volume
Jan 6, 2021
BACKGROUND: Understanding the interactions between variables that predict prolonged hospital length of stay (LOS) following spine surgery can help uncover drivers of this risk in patients. This study utilized a novel game-theory-based approach to dev...
BACKGROUND: Quality improvement efforts are frequently tied to patients achieving ≥80% medication adherence. However, there is little empirical evidence that this threshold optimally predicts important health outcomes.
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