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AI identified as a top risk to the healthcare industry

by Shreeya
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AI and new technologies have emerged as prominent risks for healthcare providers in 2024, according to an annual report by Kodiak Solutions. The report identifies these risks in the context of financial performance, competition, workforce, and cybersecurity. The integration of AI impacts multiple facets of healthcare management, with considerations for efficiencies, costs, workforce challenges, and potential legal and reputational risks.

Key Management Risks

Financial Performance:

The efficiencies gained from AI tools must be balanced against the costs of implementation and training. Organizations need to assess the overall impact on financial performance.

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Competition:

AI plays a role in enhancing competitive advantages, but the adoption and effective use of AI tools are critical in staying ahead. Failure to integrate AI may result in a competitive disadvantage.

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Workforce Challenges:

Realizing the benefits of AI requires addressing workforce challenges. Recruiting employees with the right skills to manage AI tools and providing adequate training are crucial for successful implementation.

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Cybersecurity:

The increased reliance on AI introduces new cybersecurity challenges, including the protection of vast amounts of health data and securing AI models’ training data from malicious actors.

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Workforce Turnover:

Automation through AI may lead to workforce turnover as employees lacking the necessary skills exit the organization. This poses legal, reputational, and cultural risks that need to be managed.

Methodology:

The top management risks were identified through interviews with executive leaders and board members at health systems in the United States. Risk assessments were conducted at hundreds of hospitals, health systems, medical practices, and other provider organizations.

Associated Risks of AI in Healthcare

Storing and securing protected health information (PHI) data.
Protecting AI models’ training data from malicious actors.
Addressing biases in AI algorithms related to gender, sexual orientation, race, and ethnicity.

Conclusion

Healthcare organizations face complex and interconnected risks, and AI’s integration brings both opportunities and challenges. The report emphasizes the need for careful evaluation, internal audit, and compliance plans tailored to each organization’s capabilities and market characteristics. Successfully managing these risks is essential for achieving goals in critical areas such as patient care, regulatory compliance, operations, strategic growth, and financial performance.

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