Responsible Use of AI in Healthcare Accountability, Transparency, and Ethical Oversight Artificial intelligence (AI) has emerged as a powerful tool in healthcare, revolutionizing diagnostics, treatment
The threat of government shutdown over financial disagreements is not new. Have we forgotten that the history of government shutdowns and the threat of defunding the government stretches back decades?
Let’s take a look at the history of government shutdowns before we predict an outcome on this one.
Strategies for balancing cost containment and quality care in healthcare. Explore methods executives can employ to optimize resources, enhance efficiency, and sustain financial stability while delivering exceptional patient outcomes.
On December 10, 2024, the Centers for Medicare & Medicaid Services (CMS) published a proposed rule introducing significant policy and technical changes to the Medicare Advantage (MA) Program, Medicare Prescription Drug Benefit Program (Part D), Medicare Cost Plan Program, and Programs of All-Inclusive Care for the Elderly (PACE) for Contract Year 2026.
Recent AI legislation suggests an increase in regulations on the horizon, particularly concerning high-risk applications like healthcare. Is your organization prepared to comply?
Part 1 of 2 Analyze recent data on AI hallucination in healthcare, exploring its occurrence, implications, and strategies to mitigate associated risks.
An analysis of recent data on AI hallucination in healthcare, exploring its occurrence, implications, and strategies to mitigate associated risks.
Explore why hospital admissions spike during the holidays and what healthcare providers can do to manage the surge. From delayed care to seasonal illnesses and mental health challenges, this article dives into the data and offers actionable tips to improve outcomes and ease the strain on healthcare systems during the busiest time of year.
With the election of a new president who is signaling significant interest in overhauling healthcare policies, the stakes are high for providers, payers, and policymakers.
What lessons can be drawn from the past, and what predictions can we make about the road ahead?
The landscape of data-driven management in healthcare has transformed in ways that were both anticipated and unforeseen. Revisiting the predictions from that article provides a unique opportunity to evaluate what has changed, where expectations aligned with reality, and what new challenges have emerged.
