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Prevalence of Financial Considerations Documented in Primary Care Encounters as Identified by Natural Language Processing Methods.

JAMA network open
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.

Novel Machine Learning Approach to Identify Preoperative Risk Factors Associated With Super-Utilization of Medicare Expenditure Following Surgery.

JAMA surgery
IMPORTANCE: Typically defined as the top 5% of health care users, super-utilizers are responsible for an estimated 40% to 55% of all health care costs. Little is known about which factors may be associated with increased risk of long-term postoperati...

Assessment of utilization efficiency using machine learning techniques: A study of heterogeneity in preoperative healthcare utilization among super-utilizers.

American journal of surgery
INTRODUCTION: In the United States, 5% of patients represent up to 55% of all health care costs. This study sought to define healthcare utilization patterns among super-utilizers, as well as assess possible variation in patient outcomes.

Does machine learning improve prediction of VA primary care reliance?

The American journal of managed care
OBJECTIVES: The Veterans Affairs (VA) Health Care System is among the largest integrated health systems in the United States. Many VA enrollees are dual users of Medicare, and little research has examined methods to most accurately predict which vete...

A Machine Learning-Based Approach for Predicting Patient Punctuality in Ambulatory Care Centers.

International journal of environmental research and public health
Late-arriving patients have become a prominent concern in several ambulatory care clinics across the globe. Accommodating them could lead to detrimental ramifications such as schedule disruption and increased waiting time for forthcoming patients, wh...