AITB No. 36 "Accounting for AI-Enhanced Healthcare Diagnostic Systems"

AITB No. 36: Accounting for AI-Enhanced Healthcare Diagnostic Systems - Pioneering Precision Medicine with Cutting-Edge Technology

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AITB No. 36 Accounting for AI-Enhanced Healthcare Diagnostic Systems

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Issue: How should entities account for costs and benefits associated with the deployment of AI-enhanced healthcare diagnostic systems, including imaging and predictive health assessments?

Background: AI is transforming healthcare diagnostics by analyzing medical images, predicting health risks, and offering timely interventions. Such systems are enhancing accuracy, reducing diagnostic time, and improving patient outcomes.

Guidance:

  1. Capitalization of Diagnostic System Costs: Expenses related to the development or acquisition of AI-enhanced healthcare diagnostic systems intended for long-term medical use should be capitalized as an intangible asset.
  2. Expensing of Data Collection and Model Training: Costs related to collecting medical data, patient histories, or training the AI model for enhanced diagnostic precision should be expensed as incurred.
  3. Amortization of Capitalized System Costs: The capitalized costs should be amortized over the system's expected useful life, considering technological advancements, medical practices, and regulatory changes.
  4. Benefit Recognition: Financial benefits resulting from reduced diagnostic errors, enhanced patient care, increased hospital efficiency, and reduced treatment costs due to the AI system's diagnostic capabilities should be recognized in the income statement in the relevant period.

Examples:

  • Hospital J1 invests $7M in an AI-enhanced medical imaging system expected to be beneficial for 10 years. They would capitalize the $7M and amortize it over the 10-year timeframe.

Note: This is a fictional representation and does not represent any real-world standard for AI. The development of such standards would involve extensive consultations with experts, stakeholders, and the public. Fictional representations simplify complex AI concepts, stimulate discussion, envision future scenarios, highlight ethical considerations, encourage creativity, bridge knowledge gaps, and set benchmarks for debate in fields like accounting.