Objective: To compare cost estimates for hospital stays calculated using diagnosis-related group (DRG) weights to actual Medicare payments.
Data Sources/study Setting: Medicare MedPAR files and DRG tables linked to participant data from the Study of Osteoporotic Fractures (SOF) from 1992 through 2010. Participants were women age 65 and older recruited in three metropolitan and one rural area of the United States.
Study Design: Costs were estimated using DRG payment weights for 1,397 hospital stays for 795 SOF participants for 1 year following a hip fracture. Medicare cost estimates included Medicare and secondary insurer payments, and copay and deductible amounts.
Principal Findings: The mean (SD) of inpatient DRG-based cost estimates per person-year were $16,268 ($10,058) compared with $19,937 ($15,531) for MedPAR payments. The correlation between DRG-based estimates and MedPAR payments was 0.71, and 51 percent of hospital stays were in different quintiles when costs were calculated based on DRG weights compared with MedPAR payments.
Conclusions: DRG-based cost estimates of hospital stays differ significantly from Medicare payments, which are adjusted by Medicare for facility and local geographic characteristics. DRG-based cost estimates may be preferable for analyses when facility and local geographic variation could bias assessment of associations between patient characteristics and costs.
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http://dx.doi.org/10.1111/1475-6773.12151 | DOI Listing |
Drugs
December 2024
The Aurum Institute, Parktown, South Africa.
Tuberculosis (TB) is the leading cause of death from a single infectious agent. The burden is highest in some low- and middle-income countries. One-quarter of the world's population is estimated to have been infected with TB, which is the seedbed for progressing from TB infection to the deadly and contagious disease itself.
View Article and Find Full Text PDFAppl Health Econ Health Policy
December 2024
Health Systems and Health Economics, School of Public Health, Curtin University, Bentley, Perth, Australia.
Background: Women's preferences for time allocation reveal how they would like to prioritise market work, family life, and other competing activities. Whilst preferences may not always directly translate to behaviour, they are an important determinant of intention to act.
Objective: We present the first study to apply a discrete choice experiment (DCE) to investigate time allocation preferences among women diagnosed with breast cancer and women without a cancer diagnosis.
Sci Rep
December 2024
Clean Energy Technologies Research Institute (CETRI), Process Systems Engineering, Faculty of Engineering & Applied Science, University of Regina, 3737 Wascana Parkway, Regina, SK, S4S 0A2, Canada.
Real-world emissions of particulate matter (PM) and smoke opacity were studied for an older-model diesel pickup truck during four types of driving tests, namely fixed-point test, snap-acceleration test, road test, and hill road test (uphill/downhill). A portable emissions measurement system (PEMS) and an opacimeter were used to measure real-time concentrations of PM and smoke opacity, respectively, and simultaneously. Correlation analysis showed a significant positive association between PM and opacity, suggesting the feasibility of using an opacimeter to estimate PM mass emissions from diesel vehicles.
View Article and Find Full Text PDFSci Rep
December 2024
State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
The gut microbiome, recognized as a critical component in the development of chronic diseases and aging processes, constitutes a promising approach for predicting host health status. Previous research has underscored the potential of microbiome-based predictions, and the rapid advancements of machine learning techniques have introduced new opportunities for exploiting microbiome data. To predict various host nonhealthy conditions, this study proposed an integrated machine learning-based estimation pipeline of Gut Age Index (GAI) by establishing a health aging baseline with the gut microbiome data from healthy individuals.
View Article and Find Full Text PDFBMC Geriatr
December 2024
ZHAW Zurich University of Applied Sciences, Winterthur Institute of Health Economics, Winterthur, Switzerland.
Background: Fall prevention programmes are essential interventions in societies with aging populations. This study assessed the fall rate and other health outcomes, as well as the cost-effectiveness of a home-based fall prevention programme for community-dwelling older people. In a single home visit, trained physical or occupational therapists performed fall risk assessments, eliminated environmental risk factors, and provided tailored exercises.
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