AI Risk Management in Healthcare and Managed Care

Artificial intelligence (AI) is transforming industries across the board, and healthcare is no exception. In the managed care space, the adoption of AI promises significant operational gains while also introducing new challenges around data privacy, compliance and cyber risk.

Alliant Cyber and Alliant Healthcare have worked together to explore how organizations can harness the power of AI while managing the associated risks.

How is AI Impacting Managed Care?

The healthcare sector (including providers, payors, PBMs, life science firms and ancillary service providers) is rapidly investing in AI to streamline operations, improve care delivery and enhance financial performance.

IHS Markit predicts, spending on AI is projected to exceed $300 billion globally by 2030, and managed care organizations are positioned to benefit, if the risks are properly managed. Healthcare remains one of the fastest moving sectors in adopting AI technologies across its many verticals.

Opportunities and Barriers to AI Adoption in Healthcare

The potential use cases for AI in healthcare are varied and will continue to grow as the technology becomes more accessible, affordable and advances in its ability to gather and standardize relevant data in sufficient quantities.

However, despite all the advances in the medical industry, it is beset by regulations, privacy considerations, proprietary information, antiquated technology and limited interoperability. This limits some advancements in the use of AI in healthcare. Additionally, risks associated with implementation create further impediments to adoption.

How AI Is Being Used in Managed Care

The use cases for AI in healthcare fall into several categories, including:

• Administrative process streamlining
• Compliance
• Purchasing and inventory
• Revenue cycle management
• Research
• Production
• Benefit claims processing
• Medical diagnostics
• Treatment pathways

Many of these applications offer efficiency gains and improved accuracy of administrative functions, enhancements to core operational or business processes, labor-saving or labor-replacing benefits, and clinical care improvements.

Key Risk Considerations for AI Use

AI solutions have limitations and risk, particularly in the context of operations, compliance, cyber risk management and security. Key considerations for any AI use case include:

• Safety and Care: Does the new AI solution support the managed care, safety and health objectives that the organization holds critically important?
• Data Privacy: Will the implementation and adoption of AI solutions cause unintentional exposure of sensitive Personally Identifiable Information (PII) or Personal Healthcare Information (PHI)?
• Security Vulnerabilities: Does the new AI-enabled technology expand the organization’s technology exposure by introducing potentially vulnerable applications, systems, interfaces or end-user functions?
• Regulatory Compliance: Has the organization taken measures to ensure that critical compliance and regulatory requirements will be met during and after the implementation?
• Enterprise Risk Management: Does the implementation of new AI solutions change the organization’s exposure to key risks, such as cyber attacks or errors and omissions, and does this impact insurance coverage?
• Fraud and Kickbacks: Has the organization addressed the risk of intentional, unintentional or unforeseen outcomes, transactions or trends from AI use cases in medical billing, referrals or diagnoses that could result in potential fraud or kickback regulatory violations?
• Completeness and Accuracy: Has the organization taken measures to ensure that the AI solution will meet completeness and accuracy requirements of the respective underlying process?
• Auditability and Accountability: Will the new AI solution provide the transparency, auditability and accountability that is required by the organization and its regulators?
• Return on Investment: Has the organization completed a realistic return on investment (ROI) analysis for any planned AI investment, and how will it measure its success?

Taking into account these questions will help healthcare organizations develop an AI governance framework that addresses their unique risks.

How Alliant Can Support AI Risk Governance in Healthcare

Alliant takes an integrated approach to guiding our clients through the secure and ethical adoption of artificial intelligence, with particular focus on enterprise and cyber risk management. 

The Alliant Cyber team, Managed Care Industry group and Healthcare practice work together to identify, quantify, mitigate, finance and, where possible, efficiently and effectively transfer critical AI risks that threaten security, privacy and operability. As a true partner in achieving your risk management objectives, our team of specialists bring extensive industry expertise and strong capabilities in consulting, brokerage, risk management and compliance to ensure end-to-end coverage. 

Contact Alliant today for more information on how we can help you achieve optimized risk management outcomes for your AI initiatives.