The quality of care for sickle cell disease patients hospitalized with a vaso-occlusive crisis (VOC) is poor, resulting in staggeringly high healthcare resource utilization. To evaluate in-patient care for VOC, we conducted a mixed-methods study of all adult sickle cell disease patients admitted with a VOC from 2010-2012. We quantitatively assessed the quality of care for all patients, and qualitatively studied a subset of frequently admitted patients. In total, there were 182 admissions from 57 unique patients. The median length of stay was 6 days and the 30-day readmission rate was 34.0%. We identified red blood cell transfusion and patient controlled analgesia use as predictors of increased length of stay. Interestingly, unlike prior findings, younger patients (18-30 years old) did not have increased healthcare resource utilization. Moreover, older age appeared to increase readmission rate and enhance the effect of patient controlled analgesia use on length of stay. Interviews of high healthcare resource utilizers revealed significant deficiencies in pain management and a strong desire for individualized care. This is the first study to examine in-patient predictors of acute healthcare resource utilization in sickle cell disease patients and to correlate them with qualitative perspectives of high healthcare resource utilizers.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7138462 | PMC |
http://dx.doi.org/10.3109/03630269.2015.1055576 | DOI Listing |
Transl Vis Sci Technol
January 2025
School of Optometry and Vision Science, University of New South Wales, Sydney, Australia.
Purpose: The purpose of this study was to develop and validate a deep-learning model for noninvasive anemia detection, hemoglobin (Hb) level estimation, and identification of anemia-related retinal features using fundus images.
Methods: The dataset included 2265 participants aged 40 years and above from a population-based study in South India. The dataset included ocular and systemic clinical parameters, dilated retinal fundus images, and hematological data such as complete blood counts and Hb concentration levels.
JAMA Netw Open
January 2025
America's Physician Groups, Washington, DC.
Importance: Many physician groups are in 2-sided risk payment arrangements with Medicare Advantage plans (at-risk MA). Analysis of quality and health resource use under such arrangements may inform ongoing Medicare policy concerning payment and service delivery.
Objective: To compare quality and efficiency measures under 2 payment models: at-risk MA and fee-for-service (FFS) MA.
JMIR Dermatol
January 2025
Department of Dermatology, College of Medicine, Imam Mohammad Ibn Saud Islamic University, Riyadh, Saudi Arabia.
Background: Dermoscopy is a noninvasive technology used to examine the skin's invisible microstructures in dermatological practice and is gaining prominence as a crucial tool. Dermoscopy is an evidence-based practice used to enhance the early detection of skin malignancies and to help distinguish between various skin conditions, including pigmented and nonpigmented skin malignancies. Currently, the vast majority of global guidelines for skin cancer recommend dermoscopy as a critical component.
View Article and Find Full Text PDFJ Funct Morphol Kinesiol
January 2025
Department of Physical Medicine and Rehabilitation, Tri-Service General Hospital, National Defense Medical Center, Taipei 114, Taiwan.
Pars fractures are a common cause of lower back pain, especially among young individuals. Although computed tomography (CT) and magnetic resonance imaging (MRI) scanning are commonly used in developed regions, traditional radiography remains the main diagnostic method in many developing countries. This study assessed whether the standard radiographic angles suggested in textbooks are optimal for an Asian population since Asian groups have lower lumbar lordosis.
View Article and Find Full Text PDFGeriatrics (Basel)
January 2025
School of Telematics, University of Colima, Colima 28040, Mexico.
: Hospitalization among older adults is a growing challenge in Mexico due to the high prevalence of chronic diseases and limited public healthcare resources. This study aims to develop a predictive model for hospitalization using longitudinal data from the Mexican Health and Aging Study (MHAS) using the random forest (RF) algorithm. : An RF-based machine learning model was designed and evaluated under different data partition strategies (ST) with and without variable interaction.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!