Objectives: To examine the relationship between features of nursing home (NH) medical staff organization and residents' 30-day rehospitalizations.
Design: Cross-sectional study combining primary data collected from a survey of medical directors, NH resident assessment data (minimum data set), Medicare claims, and the Online Survey Certification and Reporting (OSCAR) database.
Setting: A total of 202 freestanding US nursing homes.
Participants: Medicare fee-for-service beneficiaries who were hospitalized and subsequently admitted to a study nursing home.
Measurements: Medical staff organization dimensions derived from the survey, NH residents' characteristics derived from minimum data set data, hospitalizations obtained from Part A Medicare claims, and NH characteristics from the OSCAR database and from www.ltcfocus.org. Study outcome defined within a 30-day window following an index hospitalization: rehospitalized, otherwise died, otherwise survived and not rehospitalized.
Results: Thirty-day rehospitalizations occurred for 3788 (20.3%) of the 18,680 initial hospitalizations. Death was observed for 884 (4.7%) of residents who were not rehospitalized. Adjusted by hospitalization, resident, and NH characteristics, nursing homes having a more formal appointment process for physicians were less likely to have 30-day rehospitalization (b = -0.43, SE = 0.17), whereas NHs in which a higher proportion of residents were cared for by a single physician were more likely to have rehospitalizations (b = 0.18, SE = 0.08).
Conclusion: This is the first study to show a direct relationship between features of NH medical staff organization and resident-level process of care. The relationship of a more strict appointment process and rehospitalizations might be a consequence of more formalized and dedicated medical practice with a sense of ownership and accountability. A higher volume of patients per physician does not appear to improve quality of care.
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http://dx.doi.org/10.1016/j.jamda.2012.04.009 | DOI Listing |
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Medical Biophysics Department, Medical Research Institute, Alexandria University, Alexandria, Egypt.
Lymphadenopathy is associated with lymph node abnormal size or consistency due to many causes. We employed the deep convolutional neural network ResNet-34 to detect and classify CT images from patients with abdominal lymphadenopathy and healthy controls. We created a single database containing 1400 source CT images for patients with abdominal lymphadenopathy (n = 700) and healthy controls (n = 700).
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Medical Oncology Department, UZ Brussel, Brussels, Belgium.
Accurate quantitative assessments are crucial to understanding development of diseases and their effective treatments. Various validated perimetry and volumetry measurement methods for patients with lymphedema exist and each has its own advantages and limitations and choosing the right instrument is essential. PeriKit® (PK) is a new measurement device that requires validation.
View Article and Find Full Text PDFAsian Pac J Cancer Prev
January 2025
Department of Anatomic Pathology, Faculty of Medicine, Universitas Airlangga, Surabaya, Indonesia.
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View Article and Find Full Text PDFMatern Child Health J
January 2025
School of Public Health (Population Health Sciences), Mark Chaffin Ctr. for Healthy Development (Leadership in Disability), School of Public Health, Georgia State University, Atlanta, GA, USA.
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Rheumatology (Oxford)
January 2025
Department of Medicine, Baylor College of Medicine, Houston, TX, USA.
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