Artificial Intelligence (AI)
American Hospital Association resources on artificial intelligence (AI) and machine learning, their impact on the health care field, and AI and machine learning innovation in hospitals and health systems.
Two-thirds of consumers think generative AI could reduce extended wait times for physician appointments, notes a recent Deloitte report. Yet despite that optimism, consumer adoption of generative AI for health reasons has remained essentially flat over the past year, with only 37% of respondents…
Amid recent investigations and heightened scrutiny of AI, PAA emphasizes the importance of transparent and accountable AI systems in healthcare.
How should organizations harness AI’s transformative potential without creating unintended, adverse consequences? We offer steps to help establish guardrails, collaborations, and strategies for use.
Getting type 2 diabetes patients to go the last mile in changing behaviors has the potential to improve their blood glucose numbers significantly over time. Personalized artificial intelligence(AI)-powered health nudges could be part of the solution, according to a recent report from telehealth…
Health care executives continue to place a high priority on digital, artificial intelligence (AI) and analytics transformation, but 75% lack sufficient resources or planning in this area according to recent McKinsey & Company survey report.
Integrating artificial intelligence (AI) and automated workflows have significant potential to improve health care operations, particularly in revenue-cycle management (RCM). And with third-party payer denials and the rising cost of collections, providers increasingly are exploring solutions.
The most obvious entry point for xAI in health care will be similar to what other tech giants are doing, notes Forbes contributor Sai Balasubramanian, M.D., J.D.: Increase task automation, improve clinical workflows and optimize clinician productivity.
A new AHA Center for Health Innovation Leadership Scan episode, “Revolutionizing Revenue Cycle Management (RCM) Efficiency with AI,” will share insights on how AI solutions can help hospitals and health systems overcome staffing challenges in critical RCM areas to respond more efficiently to payer…
In this webinar, AHA Policy staff Shannon Wu, Tammy Love, Stephen Hughes, and Akin Demehin delved into the key provisions outlined in the FY 2025 Inpatient Prospective Payment System Proposed Rule. They explored topics, such as proposals concerning Medicare disproportionate share…
Join this panel discussion to learn how AI technology solutions can help provider organizations overcome staffing challenges in critical revenue cycle management (RCM) areas to respond more efficiently and effectively to payer denials.