The American journal of managed care
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The treatment of metastatic colorectal cancer (mCRC) remains challenging. There has been substantial progress in understanding the molecular pathology of the disease that has led to meaningful advancements in treatment options with varying mechanisms of action, although treatment remains costly. Cytotoxic therapies, which are typically combined with targeted therapies, remain the mainstay of first- and second-line treatment for mCRC. ⋯ A paucity of data exists in establishing clinical criteria for optimizing the sequencing of therapies in the third line and beyond. A customized approach should consider the efficacy of the therapy balanced with the patient's goals. Sequencing criteria should include a consideration for exposing patients to as many different modes of therapy as possible while preserving quality of life, avoiding serious toxicities, and accounting for the potential impact of cumulative toxicities from prior therapies.
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Emergency department risk model: timely identification of patients for outpatient care coordination.
Major depressive disorder (MDD) is linked to a 61% increased risk of emergency department (ED) visits and frequent ED usage. Collaborative care management (CoCM) models target MDD treatment in primary care, but how best to prioritize patients for CoCM to prevent frequent ED utilization remains unclear. This study aimed to develop and validate a risk identification model to proactively detect patients with MDD in CoCM at high risk of frequent (≥ 3) ED visits. ⋯ The risk identification model has potential for clinical application in triaging primary care patients with MDD in CoCM, aiming to reduce future ED utilization.
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To understand whether and how equity is considered in artificial intelligence/machine learning governance processes at academic medical centers. ⋯ We found a lack of consistent equity consideration among academic medical centers as they develop their governance processes for predictive technologies despite considerable national attention to the ways these technologies can cause or reproduce inequities. Health systems and policy makers will need to specifically prioritize equity literacy among health system leadership, design oversight policies, and promote critical engagement with these tools and their implications to prevent the further entrenchment of inequities in digital health care.
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Observational Study
Bleeds and resource use in hemophilia B: retrospective observational study.
To describe people with hemophilia B (PWHB) in the US who experience bleeds despite factor replacement therapy and to quantify the associated burden from the third-party payer perspective. ⋯ This study reports significant resource use and clinical burden among PWHB who seek medical care. PWHB with MRBs had considerable all-cause resource use compared with PWHB without MRBs. The prevalence of mental illness was consistently high across all age groups.
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In 2018, CMS established reimbursement for the first Medicare-covered artificial intelligence (AI)-enabled clinical software: CT fractional flow reserve (FFRCT) to assist in the diagnosis of coronary artery disease. This study quantified Medicare utilization of and spending on FFRCT from 2018 through 2022 and characterized adopting hospitals, clinicians, and patients. ⋯ In the initial 5 years of Medicare reimbursement for FFRCT, growth was concentrated among well-resourced hospitals and clinicians. As Medicare begins to reimburse clinicians for the use of AI-enabled clinical software such as FFRCT, it is crucial to monitor the diffusion of these services to ensure equal access.