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Introduction: Pediatric anxiety is rapidly increasing, and in 2022, the US Preventive Services Task Force recommended universal anxiety screening using a validated tool for children 8-18 years.
Method: This evidence-based practice quality improvement initiative integrated an educational process, a validated anxiety screening tool, and a Caregiver Satisfaction Survey into all primary care wellness visits for patients aged 8-18 years.
Results: Significant increases in screening and referrals for mental healthcare were observed postinitiative implementation, especially in ages 8-11 years.
Injectable Estradiol Use in Transgender and Gender-Diverse Individuals in the U.S.: A Multicenter Retrospective Study.
J Clin Endocrinol Metab
January 2025
Division of Endocrinology, Gerontology and Metabolism, Stanford University School of Medicine, Stanford, CA.
Context: Guidelines for use of injectable estradiol esters (valerate [EV] and cypionate [EC]) among transgender and gender diverse (TGD) individuals designated male at birth vary considerably, with many providers noting supraphysiologic serum estradiol concentrations based on current dosing recommendations.
Objectives: 1. Determine dose of injectable estradiol (subcutaneous [SC] and intramuscular [IM]) needed to reach guideline-recommended estradiol concentrations for TGD adults using EC/EV.
Integrating Model-Informed Drug Development With AI: A Synergistic Approach to Accelerating Pharmaceutical Innovation.
Clin Transl Sci
January 2025
Global Biometrics and Data Management, Pfizer Research and Development, New York, New York, USA.
The pharmaceutical industry constantly strives to improve drug development processes to reduce costs, increase efficiencies, and enhance therapeutic outcomes for patients. Model-Informed Drug Development (MIDD) uses mathematical models to simulate intricate processes involved in drug absorption, distribution, metabolism, and excretion, as well as pharmacokinetics and pharmacodynamics. Artificial intelligence (AI), encompassing techniques such as machine learning, deep learning, and Generative AI, offers powerful tools and algorithms to efficiently identify meaningful patterns, correlations, and drug-target interactions from big data, enabling more accurate predictions and novel hypothesis generation.
View Article and Find Full Text PDFAdvancing Quality and Safety Culture in Healthcare: Insights From the Evaluation of an Improvement Science Program for Nurses and Midwives.
J Adv Nurs
January 2025
Professor of Person Centred Healthcare, South Western Sydney Nursing & Midwifery Research Alliance, The Ingham Institute of Applied Medical Research, Liverpool, New South Wales, Australia.
Aims: This paper presents the outcomes and insights gained from the implementation of an Improvement Science program tailored for nursing and midwifery staff within a large local health district in New South Wales. The programme aimed to enhance frontline clinicians' confidence and capability in quality improvement, ultimately improving patient outcomes and safety culture.
Design: Through an explanatory sequential mixed-methods evaluation study, we assessed the programme's effectiveness in building capacity, sustaining practice changes and fostering a culture of continuous improvement.
From Symptoms to Satisfaction: Optimizing Patient-Centered Care in Dry Eye Disease.
J Clin Med
January 2025
Ocular Surface Unit, ISPRE Ophthalmics, 16129 Genoa, Italy.
Dry eye disease (DED) is a multifactorial, chronic, and often relapsing condition with a significant impact on patient quality of life (QoL). Symptoms such as ocular discomfort and visual disturbances are diverse and frequently misaligned with objective clinical signs, complicating diagnosis and management. DED not only interferes with daily activities like reading, driving, and computer use but also imposes a substantial economic burden due to direct healthcare costs and reduced work productivity.
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