Artificial intelligence is about to change the face of healthcare; state-of-the-art solutions are being offered for diagnostics, treatment planning, and operational efficiency.
However, its adoption is not straightforward. AI implementation in healthcare institutions will be influenced by various factors that can make it a success or failure.
A recent systematic review introduces The Adoption of AI in the Healthcare Industry Model. The model encapsulates five dimensions that influence the adoption of AI in the healthcare industry and places them in context.
Specifically, the study proposes that “macro-economic, regulatory, and technological readiness serve as external antecedents whereas organizational and individual readiness constitutes internal antecedents influencing adoption of AI in healthcare institutions.”
A closer look at the external factors
Macro-economic readiness
Health facilities are bound by economic systems that either promote or are a barrier to adopting AI. Most AI technologies require huge investments in research and development, implementation, and ongoing costs.
Richer countries and better-funded healthcare systems can easily embrace this technology while poor ones struggle with financial impediments to its adoption. Therefore, these economic disparities in AI readiness can increase global healthcare inequalities.
Regulatory readiness
AI in healthcare functions within a very complex legal and ethical framework. Governments and regulatory agencies must make policies that would guide AI deployment to ensure compliance with medical ethics, data privacy laws, and accountability standards.
In the absence of well-defined regulations, there is a possibility of AI application mismanagement, potential bias, and ethical issues.
So, healthcare organizations must establish regulatory frameworks for AI transparency, patients' rights, and the responsibilities of developers and healthcare providers.
Technological readiness
AI cannot function effectively without sound digital infrastructure in healthcare facilities, like secure electronic health records, cloud storage, and cybersecurity.
Most healthcare facilities, especially in developing regions, lack the required IT frameworks, making AI adoption difficult.
Additionally, AI interoperability must be resolved for AI integration. So, without a good technological foundation, AI applications can bring more risks than benefits.
Investigating the internal factors
Organizational readiness
Healthcare organizations must be prepared to introduce AI into their workflow processes with infrastructure, redesign of operational processes, and staff training.
Resistance to change and fear of job loss from automation, along with financial issues at the organizational level, could postpone AI adoption. Hospitals and clinics must plan proper implementation strategies for AI systems to enhance rather than rupture the existing workflow.
Individual readiness
AI should help augment provider expertise rather than replace it. So, healthcare professionals must be willing and able to work with AI-driven technologies.
More specifically, physicians, nurses, and administrative staff require training to interpret AI-generated insights correctly while maintaining patient-centered care.
Incorporating security and compliance
When using AI, healthcare providers must adhere to existing laws regarding healthcare privacy, such as the U.S. Health Insurance Portability and Accountability Act (HIPAA).
For example, AI healthcare solutions must have strict data security with features, like encryption, access controls, and audit trails to safeguard individuals’ protected health information (PHI).
Ultimately, healthcare professionals must address the external and internal factors influencing AI adoption while upholding ethical, legal, and professional standards.
Learn more: Using AI for HIPAA compliance
FAQs
What is HIPAA compliance?
HIPAA compliance refers to adhering to regulations outlined in the Health Insurance Portability and Accountability Act to safeguard patients’ protected health information (PHI).
Can AI be integrated into HIPAA compliant emails?
Yes, AI-powered features can be integrated with HIPAA compliant emailing platforms, like Paubox, to automate processes like patient consent management and sending personalized emails while maintaining HIPAA compliance.
Are there any limitations when using AI in HIPAA compliant emails?
Yes, healthcare providers must ensure that AI-powered features comply with HIPAA regulations and industry best practices for data security and privacy. Additionally, providers should evaluate the reliability of AI algorithms to avoid potential risks or compliance issues.
Read also: HIPAA compliant email API
