A Systematic Review of the Barriers to the Implementation of Artificial Intelligence in Healthcare

Ref: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10623210/

Both the use of a new technology and the growth and expansion of its use generate enthusiasm and resistance at the same time. Particularly regarding the barriers, in this paper, the authors systematically analyze existing literature to identify and categorize these barriers that hinder the widespread adoption and implementation of Artificial Intelligence (AI) in the healthcare sector. 

The following key barriers are identified:

1. Technological Barriers:
   • Data Quality and Availability
   • Interoperability
   • Scalability
2. Regulatory and Ethical Barriers:
   • Regulatory Uncertainty
   • Ethical Concerns
3. Economic Barriers:
   • High Costs
   • Return on Investment (ROI)
4. Cultural and Organizational Barriers:
   • Resistance to Change
   • Lack of Skills
   • Organizational Readiness
5. Social Barriers:
   • Patient Acceptance

AI has the potential to revolutionize healthcare, overcoming these barriers is critical for its successful implementation. A multidisciplinary approach involving policymakers, technologists, healthcare providers, and patients to address these challenges. By doing so, the healthcare industry can fully leverage AI's capabilities to improve patient outcomes, enhance efficiency, and reduce costs.