AIMC Topic: Medicare

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Low-value care and excess out-of-pocket expenditure among older adults with incident cancer - A machine learning approach.

Journal of cancer policy
OBJECTIVE: To evaluate the association of low-value care with excess out-of-pocket expenditure among older adults diagnosed with incident breast, prostate, colorectal cancers, and Non-Hodgkin's Lymphoma.

Improving Stroke Risk Prediction in the General Population: A Comparative Assessment of Common Clinical Rules, a New Multimorbid Index, and Machine-Learning-Based Algorithms.

Thrombosis and haemostasis
BACKGROUND: There are few large studies examining and predicting the diversified cardiovascular/noncardiovascular comorbidity relationships with stroke. We investigated stroke risks in a very large prospective cohort of patients with multimorbidity, ...

A Machine Learning Approach to Identify Predictors of Potentially Inappropriate Non-Steroidal Anti-Inflammatory Drugs (NSAIDs) Use in Older Adults with Osteoarthritis.

International journal of environmental research and public health
Evidence from some studies suggest that osteoarthritis (OA) patients are often prescribed non-steroidal anti-inflammatory drugs (NSAIDs) that are not in accordance with their cardiovascular (CV) or gastrointestinal (GI) risk profiles. However, no suc...

Machine learning to predict mortality after rehabilitation among patients with severe stroke.

Scientific reports
Stroke is among the leading causes of death and disability worldwide. Approximately 20-25% of stroke survivors present severe disability, which is associated with increased mortality risk. Prognostication is inherent in the process of clinical decisi...

Closing the Digital Health Evidence Gap: Development of a Predictive Score to Maximize Patient Outcomes.

Telemedicine journal and e-health : the official journal of the American Telemedicine Association
Clinical studies of telemedicine (TM) programs for chronic illness have demonstrated mixed results across settings and populations. With recent uptake in use of digital health modalities, more precise patient classification may improve outcomes, eff...

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...