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- CAP urges caution on AI in quality measures
The CAP has responded to a request for public comments on a proposal for AI in quality measures.
What we're saying: AI-derived measures could place additional burdens on health care entities without clear evidence of enhanced accuracy or reduced workload. The CAP advises that the Centers for Medicare & Medicaid Services (CMS) refrain from mandating these measures until they are tested and proven beneficial.
- Key concerns: We highlighted the need to minimize the administrative burden on entities already managing quality reporting. Responsibility for testing AI measures should lie with program owners, not individual entities.
- Interoperability issues: Our recommendation is that measure developers prioritize making data widely accessible for AI models.
- Feedback loop burden: A proposed centralized reporting system could create significant burdens across the measurement ecosystem, from program owners to entities. The CAP warns that practical implementation of such a system may not be feasible or beneficial at this time.