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Real-World Applications of Artificial Intelligence to Improve Medication Management Across the Care Continuum

Abstract

Ken Perez

The United States spends more in aggregate and on a per-capita basis on healthcare than any other country. Spending on medications accounts for over 10% of U.S. healthcare expenditures and has been identified as a key driver of the nation’s higher spending on healthcare. In addition, there are several issues with and shortcomings of the medication management system, including non-adherence and adverse drug events, which often result in emergency department visits and hospitalizations, and increasing administrative burdens placed on clinicians, which cause pharmacists to spend the majority of their time on non-clinical activities. A private sector initiative, the Autonomous Pharmacy Advisory Board, which involves several leading hospitals and health systems from across the U.S., is applying automation, analytics, machine learning and AI to improve operational and clinical outcomes, ensure regulatory compliance, and advance population health. The aforementioned technologies are being used by various companies and healthcare provider organizations to address four significant medication management issues: 1) drug shortages; 2) the opioid crisis; 3) drug diversion; and 4) medication adherence. Practical real-world use cases will be highlighted, along with suggested vectors for future development.

अस्वीकृति: इस सारांश का अनुवाद कृत्रिम बुद्धिमत्ता उपकरणों का उपयोग करके किया गया है और इसे अभी तक समीक्षा या सत्यापित नहीं किया गया है।

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