People with disabilities are less likely than the general population to receive clinical preventive services.

Gout is characterized by deposition of monosodium urate (MSU) crystals in or around joints, tendons, bursae, and other tissues, resulting in painful recurrent flares and tissue damage. Gout is the most common form of inflammatory arthritis, with a prevalence of 5.1% in the United States, affecting 12.1 million adults. When urate levels exceed the limit of solubility (6.8 mg/dL [400 μmol/L]), MSU crystals may form or grow. Gout flares are the result of inflammatory responses to MSU crystals. The primary method to prevent and reduce gout flares, tophi, chronic inflammatory arthritis, and joint damage is to reduce urate levels below the saturation threshold. The pathophysiology of gout is well understood, and inexpensive and effective therapies are available. However, outcomes for patients with gout remain poorly optimized.

The Kidney Disease: Improving Global Outcomes (KDIGO) organization updated its existing clinical practice guideline in 2024 to provide guidance on the evaluation, management, and treatment of chronic kidney disease (CKD) in adults and children who are not receiving kidney replacement therapy.

Although glucagon-like peptide-1 receptor agonists (GLP-1RAs) have shown potential antidepressant effects, population studies yield inconsistent results.

The federal government spends billions of dollars per year on payments to Medicare Advantage (MA) plans based, in part, on beneficiaries' risk scores. Despite this, little is known about the true burden of chronic medical conditions among MA beneficiaries compared with those in fee-for-service (FFS) Medicare.

When randomized trials are not available to answer a causal question about the comparative effectiveness or safety of interventions, causal inferences are drawn using observational data. A helpful 2-step framework for causal inference from observational data is 1) specifying the protocol of the hypothetical randomized pragmatic trial that would answer the causal question of interest (the target trial), and 2) using the observational data to attempt to emulate that trial. The target trial framework can improve the quality of observational analyses by preventing some common biases. In this article, we discuss the utility and scope of applications of the framework. We clarify that target trial emulation resolves problems related to incorrect design but not those related to data limitations. We also describe some settings in which adopting this approach is advantageous to generate effect estimates that can close the gaps that randomized trials have not filled. In these settings, the target trial framework helps reduce the ambiguity of causal questions.

The Centers for Medicare & Medicaid Services (CMS) Severe Sepsis and Septic Shock Management Bundle (SEP-1) is now included in the Hospital Value-Based Purchasing (VBP) Program.

Future U.S. congressional funding for the President's Emergency Plan for AIDS Relief (PEPFAR) program is uncertain.