Injury
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Artificial intelligence (AI) is a broad term referring to the application of computational algorithms that can analyze large data sets to classify, predict, or gain useful conclusions. Under the umbrella of AI is machine learning (ML). ML is the process of building or learning statistical models using previously observed real world data to predict outcomes, or categorize observations based on 'training' provided by humans. ⋯ AI and ML are becoming cornerstones in the medical and healthcare-research domains and are integral in our continued processing and capitalization of robust patient EMR data. Considerations for the use and application of ML in healthcare settings include assessing the quality of data inputs and decision-making that serve as the foundations of the ML model, ensuring the end-product is interpretable, transparent, and ethical concerns are considered throughout the development process. The current and future applications of ML include improving the quality and quantity of data collected from EMRs to improve registry data, utilizing these robust datasets to improve and standardized research protocols and outcomes, clinical decision-making applications, natural language processing and improving the fundamentals of value-based care, to name only a few.
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Fragility fractures of the pelvis (FFP) are a clinical entity with a rapidly growing incidence among elderly women. The characteristics of these fractures are different from those appearing after high-energy trauma. In 2013, the comprehensive FFP-classification provided a new framework for analysis of these fractures. ⋯ Mobility, independency and quality of life are worse than before the fracture, independent of the FFP-classification and the type of treatment. The classification triggered a rapid increase of expertise. This publication gives a detailed overview on the evolution from eminence to evidence.
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Patient-reported outcomes (PROs) capture data related to patients' perception of their health status and aspects of health care delivery. In parallel, digital innovations have advanced the administration, storage, processing, and accessibility of PROs, allowing these data to become actively incorporated in day-to-day clinical practice along the entire patient care pathway. ⋯ This technology-enabled, data-driven approach provides insights which, when actioned, can enhance musculoskeletal care of patients and populations, while enriching the clinician-patient experience of decision making. In this review, we provide an overview of the opportunities enabled by PROs and technology for the cycle of orthopedic care.
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Clinical practices guidelines (CPGs) play a fundamental role in improving healthcare and patients' outcomes by helping clinicians make the best evidence-based decisions for their patients in a time-efficient manner. By following the available methods and criteria to create trustworthy CPGs, panel members can develop high-quality guidelines. However, despite the improvements over the years, CPGs are still subjected to biases and limitations, with conflicts of interest being the ugliest problem GCPs must face. In this review, we discuss the main characteristics of clinical practice guidelines, their pros and cons, and the future challenges they need to overcome.
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Review
E-scooter and E-bike injury pattern profile in an inner-city trauma center in upper Manhattan.
Electric bikes and scooters are becoming popular means of short-distance transportation in major cities. Regulations for safe riding established by ride-sharing companies and local governments have not been effectively implemented. Inner-city hospitals are at the frontline of receiving traumas related to e-bikes and e-scooters and are receiving an increasing number of injuries. The works of literature reporting these injuries are limited. ⋯ The use of e-bikes and e-scooters is increasing as a means of affordable short-distance transportation but with evidence of significant injuries with varying severity. These findings suggest a need to review public policy regarding e-bike and electric scooter use regulations for the safety of riders and pedestrians; Driving While Intoxicated (DWI) law enforcement, mandatory helmet, education, speed control, creation of special lanes, and no car zones.