Critically Appraising the Wellness Movement: Cost Without Value, A Narrative Review

Area of Science:

• Health informatics
• Genomics
• Medical diagnostics

Background:

• The direct-to-consumer wellness testing market has expanded rapidly, encompassing genomics, lab panels, wearables, and imaging.
• This market growth outpaces scientific evidence, leading to significant downstream costs and potential patient harm, including false positives and anxiety.

Purpose of the Study:

• To propose a three-tier precision health framework to optimize diagnostic testing.
• To integrate data from omics, sensors, imaging, and lifestyle medicine.
• To leverage AI for population assessment and guide high-value testing based on pre-test probability.

Main Methods:

• Synthesizing data across multiple health-related fields (omics, sensors, imaging, lifestyle medicine).
• Developing a three-tier framework: Tier 1 (high-sensitivity screens), Tier 2 (targeted confirmation), and Tier 3 (precision interventions).
• Utilizing Artificial Intelligence (AI) for population assessment to determine pre-test probability.

Main Results:

• The proposed framework aims to reduce low-value diagnostics and associated downstream costs (estimated over $100 billion annually in the US).
• It seeks to mitigate patient exposure to false-positive results, anxiety, and bias.
• The model prioritizes high-value testing guided by pre-test probability.

Conclusions:

• Adopting this precision health model can significantly decrease unnecessary medical examinations.
• Resources can be redirected towards evidence-based preventive measures.
• This approach promises to enhance healthcare efficiency and patient outcomes.