Technology Title
Artificial Intelligence (AI) in Healthcare
Artificial Intelligence (AI) in Healthcare
Project Title
Overtreatment vs Undertreatment
Overtreatment vs Undertreatment
Category
Bioscience Medical
Bioscience Medical
Authors
amkpong4901@lcu.edu
amkpong4901@lcu.edu
Short Description
This paper explores how overtreatment and undertreatment affect healthcare quality and efficiency, using economic theory to examine the role of costs, incentives, and market failures.
This paper explores how overtreatment and undertreatment affect healthcare quality and efficiency, using economic theory to examine the role of costs, incentives, and market failures.
Long Description
This paper looks at overtreatment and undertreatment in healthcare using basic economic ideas, especially the balance between marginal cost and marginal benefit. In a perfect system, care would be given up to the point where the benefit matches the cost, but that is rarely what happens in real life. Instead, healthcare often provides too much low-value care while also failing to deliver high-value services to patients who need them. I explain how factors like information asymmetry, insurance design, externalities, and behavioral biases all push the system away from efficiency. Real-world examples like unnecessary antibiotic use, excessive imaging, and gaps in preventive care help show how these problems play out. Overall, both overtreatment and undertreatment lead to wasted resources and worse outcomes, showing that improving healthcare is not just about spending more or less, but about making better, more efficient decisions.
This paper looks at overtreatment and undertreatment in healthcare using basic economic ideas, especially the balance between marginal cost and marginal benefit. In a perfect system, care would be given up to the point where the benefit matches the cost, but that is rarely what happens in real life. Instead, healthcare often provides too much low-value care while also failing to deliver high-value services to patients who need them. I explain how factors like information asymmetry, insurance design, externalities, and behavioral biases all push the system away from efficiency. Real-world examples like unnecessary antibiotic use, excessive imaging, and gaps in preventive care help show how these problems play out. Overall, both overtreatment and undertreatment lead to wasted resources and worse outcomes, showing that improving healthcare is not just about spending more or less, but about making better, more efficient decisions.
Potential Applications
This research could help inform healthcare policies, improve how resources are allocated, and encourage better incentives for providers. The goal is to reduce unnecessary spending without limiting access to care that patients actually need.
This research could help inform healthcare policies, improve how resources are allocated, and encourage better incentives for providers. The goal is to reduce unnecessary spending without limiting access to care that patients actually need.
Open Questions
- How can we reduce overtreatment without making undertreatment worse?
- Can healthcare systems realistically achieve the MB = MC equilibrium?
- How do we balance healthcare efficiency with equal access to care?
- Are performance indicators enough to change how providers make decisions?
- How can we reduce overtreatment without making undertreatment worse?
- Can healthcare systems realistically achieve the MB = MC equilibrium?
- How do we balance healthcare efficiency with equal access to care?
- Are performance indicators enough to change how providers make decisions?
AI Assistant
How do i use econometrics to make this paper better?
How do i use econometrics to make this paper better?
Keywords
Data, Analysis, Healthcare Economics, #IdeaInnovationBusiness
Data, Analysis, Healthcare Economics, #IdeaInnovationBusiness
Email
amkpong4901@lcu.edu
amkpong4901@lcu.edu