Background And Objectives: Despite concerns about the adequacy of nursing home (NH) staffing, the federal agency responsible for NH certification and regulation has never adopted an explicit quantitative nursing staff standard. A prior study has proposed a benchmark for this purpose based on the 1995/97 Staff Time Measurement (STM) studies. This article aims to assess the extent to which NHs staff to this proposed STM benchmark, the extent to which regulators already implicitly apply the STM benchmark, and compute the additional operating expenses NHs would incur to adhere to the STM benchmark.
Research Design And Methods: Using NH Compare Archive data, the STM benchmark was compared to staffing levels reported by the facility and whether NHs received a nursing staff deficiency. Using financial information from Medicare Cost Reports, the additional annual operating expenses required to staff to the STM benchmark were calculated for each state and nationwide.
Results: The vast majority of NHs did not staff to the STM benchmark; 80.2% for registered nurses and 60.0% for total nursing staff. Deficiency patterns showed that NH regulators were not using the STM benchmark to determine sufficiency of nursing staff. Implementing the STM benchmark as a regulatory standard would increase operating expenses for 59.1% of NHs, at an average annual cost of half-million dollars per facility. The nationwide increase in operating expense is estimated to be at least $4.9 billion per year.
Discussion And Implications: Without clear guidance on the staffing level needed to be sufficiently staffed, most NHs are subject to a community standard of care, which some have argued could be associated with suboptimal staffing levels. Implementing an acuity-based benchmark could result in improved staffing levels but also comes with significant economic costs. The STM benchmark is not economically feasible at current Medicare and Medicaid reimbursement levels.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9196696 | PMC |
http://dx.doi.org/10.1093/geroni/igac017 | DOI Listing |
Rev Sci Instrum
December 2024
2nd Institute of Physics B and JARA-FIT, RWTH Aachen University, 52074 Aachen, Germany.
Low-temperature scanning tunneling spectroscopy is a key method to probe electronic and magnetic properties down to the atomic scale, but suffers from extreme vibrational sensitivity. This makes it challenging to employ closed-cycle cooling with its required pulse-type vibrational excitations, albeit this is mandatory to avoid helium losses for counteracting the continuously raising helium prices. Here, we describe a compact ultra-high vacuum scanning tunneling microscope (STM) system with an integrated primary pulse tube cooler (PTC) for closed-cycle operation.
View Article and Find Full Text PDFSci Rep
October 2024
Department of Structural Engineering, Mansoura University, PO BOX 35516, Mansoura, Egypt.
This study uses symbolic regression with a strut-and-tie model to predict the shear strength of reinforced concrete deep beams (RCDBs) and corbels (RCCs). Previous studies have proposed two distinct types of models for estimating shear capacity: explainable models based on theoretical derivations and black-box models derived from machine learning (ML) methods. This study proposes a hybrid model derived from the strut-and-tie model (STM), where the performance of STM is enhanced through the ML approach using genetic programming.
View Article and Find Full Text PDFJ Biomed Inform
September 2024
Department of Biostatistics, Harvard T.H. Chan School of Public Health, United States of America; Department of Biomedical Informatics, Harvard Medical School, United States of America.
Background: Risk prediction plays a crucial role in planning for prevention, monitoring, and treatment. Electronic Health Records (EHRs) offer an expansive repository of temporal medical data encompassing both risk factors and outcome indicators essential for effective risk prediction. However, challenges emerge due to the lack of readily available gold-standard outcomes and the complex effects of various risk factors.
View Article and Find Full Text PDFNanoscale
June 2024
Kavli Institute of Nanoscience, Delft University of Technology, Lorentzweg 1, 2628 CJ Delft, The Netherlands.
ACS Nano
May 2024
School of Chemistry, University of Birmingham, Birmingham B15 2TT, U.K.
Conjugated polymers have become materials of choice for applications ranging from flexible optoelectronics to neuromorphic computing, but their polydispersity and tendency to aggregate pose severe challenges to their precise characterization. Here, the combination of vacuum electrospray deposition (ESD) with scanning tunneling microscopy (STM) is used to acquire, within the same experiment, assembly patterns, full mass distributions, exact sequencing, and quantification of polymerization defects. In a first step, the ESD-STM results are successfully benchmarked against NMR for low molecular mass polymers, where this technique is still applicable.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!