AIMC Topic: Health Care Costs

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Breaking down costs: rehabilitation robotics vs. usual care therapy in diverse healthcare models.

Scientific reports
One of the significant barriers to the adoption of rehabilitation robotics into clinical care over the last 30 years has been the high investment costs of the technology. There have been limited efforts to understand the healthcare economics of imple...

Causal effect of conventional anti-dementia drugs on economic burden: an orthogonal double/debiased machine learning approach.

BMC geriatrics
BACKGROUND: The Inflation Reduction Act (IRA) did not introduce a cap on out-of-pocket (OOP) for newly approved Alzheimer's Disease (AD) drugs, such as lecanemab which is covered under Medicare Part B. Therefore, expanding the use of conventional ant...

Using Machine Learning to Match Clients and Therapy Providers: Evaluating Clinical Quality and Cost of Care.

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
OBJECTIVES: Matching clients in need of mental healthcare with providers who will deliver high quality treatment presents a substantial challenge. Machine learning models hold potential for predicting the best pairings from a multitude of data points...

The Cost Outcome Pathway framework: Integrating socio-economic impacts to Adverse Outcome Pathways for supporting policy makers.

Toxicology
The Adverse Outcome Pathway (AOP) concept leverages existing data to formalize and disseminate knowledge and is a well-accepted concept in chemical risk assessment. However, it does not handle the socio-economic impact that environmentally-induced di...

Improved radiological diagnosis of osteoporotic vertebral fragility fractures following UK-wide interventions and re-audit-can this be maintained and translated into clinical practice?

Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA
UNLABELLED: To determine the potential economic, morbidity and mortality impact of improvements in reporting of vertebral fragility fractures (VFFs) following a complete audit cycle. Six percent interval increase in reporting of moderate/severe VFFs ...

Predictors of High Healthcare Cost Among Patients with Generalized Myasthenia Gravis: A Combined Machine Learning and Regression Approach from a US Payer Perspective.

Applied health economics and health policy
BACKGROUND: High healthcare costs could arise from unmet needs. This study used random forest (RF) and regression methods to identify predictors of high costs from a US payer perspective in patients newly diagnosed with generalized myasthenia gravis ...

Machine learning models for assessing risk factors affecting health care costs: 12-month exercise-based cardiac rehabilitation.

Frontiers in public health
INTRODUCTION: Exercise-based cardiac rehabilitation (ECR) has proven to be effective and cost-effective dominant treatment option in health care. However, the contribution of well-known risk factors for prognosis of coronary artery disease (CAD) to p...

A systematic review of economic evaluation of artificial intelligence-based screening for eye diseases: From possibility to reality.

Survey of ophthalmology
Artificial Intelligence (AI) has become a focus of research in the rapidly evolving field of ophthalmology. Nevertheless, there is a lack of systematic studies on the health economics of AI in this field. We examine studies from the PubMed, Google Sc...

Enhancing Stress Detection: A Comprehensive Approach through rPPG Analysis and Deep Learning Techniques.

Sensors (Basel, Switzerland)
Stress has emerged as a major concern in modern society, significantly impacting human health and well-being. Statistical evidence underscores the extensive social influence of stress, especially in terms of work-related stress and associated healthc...

Risk adjustment for regional healthcare funding allocations with ensemble methods: an empirical study and interpretation.

The European journal of health economics : HEPAC : health economics in prevention and care
We experiment with recent ensemble machine learning methods in estimating healthcare costs, utilizing Finnish data containing rich individual-level information on healthcare costs, socioeconomic status and diagnostic data from multiple registries. Ou...