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Impact of the Skilled Nursing Facility 3-Day Rule Waiver on Medicare ACO Expenditures: A Retrospective Analysis of 2023 MSSP Performance Data
No full textThesis (Master's)--University of Washington, 2025ObjectivesTo evaluate whether participation in the Medicare Skilled Nursing Facility (SNF) three-day rule waiver has an effect on total per capita expenditures among Accountable Care Organizations (ACOs) participating in the Medicare Shared Savings Program (MSSP).
Design
A retrospective cross-sectional analysis of 2023 MSSP ACO performance data. The study assessed the relationship between SNF waiver participation and healthcare expenditures using a multivariate linear regression framework. The study included all ACOs participating in the MSSP during the 2023 performance year, encompassing a nationally representative sample of Medicare beneficiaries attributed to those organizations.
Methods
A robust linear regression model was developed to explain variation in per capita expenditures, with adjustment for key covariates including patient risk profiles (CMS Hierarchical Condition Category scores), ACO savings rates, and inpatient and SNF utilization rates. Subgroup analyses were performed based on ACO size, defined by the median beneficiary count (19,457). A post-hoc power analysis confirmed adequate statistical power (>80%) to detect moderate effect sizes.
Results
The model explained 96% of the variance in per capita expenditures (Adjusted R² = 0.96). Key predictors included HCC risk scores (β = 4430.63, p < 0.001), savings rate (β = –52.63, p < 0.001), inpatient utilization (β = 1.80, p < 0.001), and SNF utilization (β = 2.46, p < 0.001). SNF waiver participation was not significantly associated with expenditures overall (β = 12.81, p = 0.828) or in either subgroup analysis.
Conclusions and Implications
While risk profiles, utilization patterns, and financial performance significantly shape ACO expenditures, SNF waiver participation alone does not independently impact spending. As CMS prepares to expand the waiver under the FY 2026 IPPS/LTCH PPS rule, ACOs and policymakers should focus on broader strategies—such as refined risk adjustment, care coordination, and cost-saving interventions—to achieve meaningful value-based care improvements. Keywords: Medicare Shared Savings Program, ACO, Skilled Nursing Facility, 3-Day Rule Waiver, Healthcare Expenditures, Risk Adjustment, Post-Acute Care Transition
Sleep, Cognition, Psychological Symptoms, and Health-Related Quality of Life Among Heart Transplant and Left Ventricular Assist Device Recipients
No full textThesis (Ph.D.)--University of Washington, 2025Heart failure (HF) is a chronic, progressive condition affecting an estimated 6.7 million Americans over age of 20. For individuals with advanced HF, treatment options such as heart transplantation (HTx) and left ventricular assist devices (LVADs) can significantly improve survival and health-related quality of life (HRQOL). Despite these interventions, many individuals continue to face persistent physiological and psychological challenges, including sleep disturbances, cognitive impairments, and psychological symptoms, which may hinder recovery and adversely affect overall well-being and HRQOL. The overarching purpose of this dissertation is to examine changes in sleep, cognition, psychological symptoms, and HRQOL from hospital discharge to 3 months post-discharge, and to explore interrelationships among these health outcomes in individuals who have received a LVAD or HTx. Specifically, the aims of this dissertation are to: 1) Conduct a comprehensive literature review on neurocognitive changes associated with HF, 2) Describe changes in objective and subjective sleep quality, cognition, psychological symptoms, and HRQOL from hospital discharge to 3 months post-discharge following a LVAD implant or HTx, 2) examine relationships between changes in sleep and changes in cognitive function, psychological symptoms, and HRQOL, and 3) Explore patient experiences, challenges, and perspectives on changes in sleep quality and its perceived impact on cognition, psychological wellbeing, and HRQOL during the initial 3 months post-discharge after LVAD or HTx. By characterizing these outcomes and their interconnections, this study provides novel insights into post-operative recovery in both LVAD and HTx recipients. The findings highlight critical gaps in current understanding, underscore the need for further research, and offer preliminary evidence to guide the design of future large-scale, multicenter studies. This work lays a foundation for improving care strategies and supporting multidimensional recovery in these growing patient populations
Functionalized nano-optics for studying optical and mechanical properties of low-dimensional materials
No full textThesis (Ph.D.)--University of Washington, 2025A central challenge in nanoscience is the development of new tools to non-invasively probe the rich physics of low-dimensional materials whose properties are dominated by quantum confinement and surface effects. Conventional characterization techniques often lack the required sensitivity or can perturb the fragile systems they aim to measure. To address this metrological gap, we introduce and develop "functionalized nano-optics" where we transform static photonic crystal cavities into dynamic, reconfigurable instruments by endowing them with active degrees of freedom. Two principal functionalities are explored: in-situ strain tuning for precise spectral control, and spatial mobility, which recasts the nanocavity as a scanning probe tool. The first functionality is demonstrated through the development of a cryo-compatible, in-situ strain-tuning platform for hybrid photonic systems. By integrating a Gallium Phosphide (GaP) photonic crystal cavity with a monolayer of the 2D semiconductor WSe2 on a strain cell, we overcome the common problem of spectral mismatch between emitters and cavities. This system achieves a continuous and reversible tuning of the cavity resonance by 5.5 nm at 5 K, an order of magnitude larger than the cavity linewidth, without degrading the Q-factor. This spectral control is used to modulate the cavity-enhanced exciton photoluminescence, establishing a robust method for systematically studying light-matter interactions in 2D materials. As a complementary approach and followup to hybrid integration, we also explore the use of the van der Waals material itself as the core photonic component. By fabricating waveguides and integrated devices directly from bulk MoS2, we demonstrate deeply subwavelength light confinement, with guided modes in structures as thin as /16. These devices are characterized using a combination of far-field spectroscopy and scattering-type near-field optical microscopy (SNOM) to reveal the properties of highly confined exciton-polaritons. The second core functionality of spatial mobility is realized through the development of a novel scanning optomechanical probe. A high-Q Silicon Nitride nanobeam cavity is integrated onto the tip of a tapered optical fiber, creating a versatile instrument for studying nanomechanical motion. This platform is applied to perform the first direct, high-bandwidth measurements of the thermally-driven mechanical vibrations of suspended DNA bundles, which are prepared via self-assembly on super-hydrophobic micropillar arrays. Additionally, we observe significant optomechanical back-action, first of its kind in a DNA resonator, which manifests as a symmetric frequency softening characteristic of a dissipative-like coupling mechanism. Together, these results establish functionalized nano-optics as a powerful and versatile platform for exploring the complex optical and mechanical properties of diverse low-dimensional material systems
Exploration of stall dynamics on a high-speed CRM wing
No full textThesis (Master's)--University of Washington, 2025The sensitivity of the flowfield and the resulting loads/moments are examined on a 4% scale, half-span, high-speed version of the Common Research Model (CRM-HS). A range of Reynolds numbers and angles of attack were examined using a combination of tuft flow-visualization and Particle Image Velocimetry (PIV) in the 8 ft by 12 ft Kirsten Wind Tunnel (KWT) at the University of Washington. The tufts showed a leading edge–tip stall at every tested condition, with separation delayed to higher angles of attack at higher Reynolds numbers (Re). Approximate Reynolds number independence was observed for Rec > 10^6, based on the mean aerodynamic chord. The separation point drifts towards the root for larger angles of attack at the same Rec condition. PIV data reveal a thickening of the separated shear layer and the formation of reversed flow with consequent vortical structures in the downstream region at a higher angle of attack. We evaluate and compare background subtraction and denoising methods to mitigate low signal-to-noise ratio (SNR) typical of large scale wind tunnels. A POD-based background removal approach proved more robust than average subtraction or high-pass filters, especially in removing model-induced reflections. Conversely, an entropy-based criterion designed to isolate higher order POD modes representing noise, was found to also attenuate turbulent flow features and so it was unsuitable for this dataset. Proper Orthogonal Decomposition (POD) of the top-down PIV data identified a dominant mode pair (modes 1 and 2) exhibiting large-scale spanwise periodicity. These modes strongly resemble the spanwise alternation seen in stall cells and are phase-shifted to represent a traveling structure in the spanwise direction. The coherent footprint of these modes across the field of view suggests that a low-dimensional mechanism may underlie the separation dynamics. In summary, a highly dynamic reversed flow region and spanwise periodicity are observed which are poorly represented by the mean flow
Super-resolved Optical Imaging, Reconstruction, and Spatial Analysis of Whole Mouse Renal Glomeruli via GloMAP
No full textThesis (Ph.D.)--University of Washington, 2025The glomerulus plays a crucial role in blood filtration and is made up of several key components that function collaboratively. Traditionally, optical microscopy has provided insights into general physiology and molecular distributions, and electron microscopy has been used to reveal ultrastructural details of the glomerular structures. While past studies have extensively examined local changes in glomerular diseases and aging, the global relationships and coordination among glomerular structures remain poorly understood due to the limitations of two-dimensional and partial analyses. To address these limitations, I present a novel pipeline that employs super-resolution fluorescence microscopy to achieve holistic three-dimensional imaging, reconstruction, and analysis of whole mouse glomeruli at 100 nm resolution. This workflow integrates advanced tissue labeling techniques and super-resolution imaging to capture entire mouse glomeruli, and combines manual segmentation with machine learning methods to reconstruct all glomerular compartments in 3D. I further demonstrate the versatility of this approach by applying it to various glomerular types, including cortical and juxtamedullary, as well as different conditions such as aging and focal segmental glomerulosclerosis. I also show that the detailed spatial analyses of the resulting models reveal new insights into the spatial correlations among glomerular components in both aged and diseased mice. Once published, the unique datasets generated by this approach will serve as a valuable resource for the nephrology community
Schrödinger Operators with Lattice Invariant Potentials
No full textThesis (Ph.D.)--University of Washington, 2025We develop a systematic framework to study the dispersion surfaces of Schrödinger operators H = −∆+V, where the potential V is both periodic with respect to a lattice Λ and respects its symmetries. Our analysis relies on an abstract result, previously proven by Franz Rellich [Rel40] and which we prove using an alternative approach inspired by methods developed by Tosio Kato [Kat95]: if a self-adjoint operator depends analytically on a parameter, then so do its eigenvalues and eigenprojectors in a neighborhood of the real line. Using this and techniques from Floquet-Bloch theory and representation theory, we prove a series of results that can be used to analyze the operator H where the lattice Λ is arbitrary. As an application of this framework, we describe the generic structure of some singularities in the band spectrum of Schrödinger operators invariant under various two- and three-dimensional lattices. Specifically, we study the square, hexagonal, rectangular, simple cubic, body-centered cubic, face-centered cubic, and stacked hexagonal lattices, in the process reproducing results due to [Kel+18] and [FW12], and also proving a conjecture of [GZZ22]
Estimation of carbon stock in tea plants (Camellia sinensis) based on age variation at Tambi plantation unit
Full text linkBackground: As an effort to reduce current climate change, conservation measures such as carbon stock measurements are needed. Tea plants are a suitable commodity for transforming towards low carbon production because perennial plants such as can absorb and store more carbon than seasonal agricultural crops. Methods: Sampling was carried out using a random sampling method that was taken randomly to represent a population for each block number. Data collection for the study was carried out by taking 3 soil and plant samples at each age of the tea plant with an age of 10 years, 30 years, 40 years, and 100 years. The plant samples taken were leaves, stems, roots, and litter. The soil samples taken were soil with a depth of 0-10 cm, 10-20 cm, and 20-30 cm with disturbed and undisturbed soil sampling. Findings: The total carbon stock value of tea plants stored in the Pemandangan Block UP Tambi is 63.17 tons/ha in 10-year-old tea plants; 67.26 tons/ha in 30-year-old tea plants; 67.87 tons/ha in 40-year-old tea plants; and 69.40 tons/ha in 100-year-old tea plants. After analyzing the relationship between physical and chemical properties of soil with biomass carbon reserves, C-Organic, soil texture, and soil volume weight are the parameters that most influence carbon reserve content. Conclusion: Plant age due to replanting and pruning, making them unsuitable for soil carbon stock estimation. Novelty/Originality of this article: This study offers novelty by integrating field-based carbon stock measurements of tea plants with variations in plant age and Sentinel-2A remote sensing analysis, providing a unique contribution to understanding the relationship between soil properties, biomass, and carbon storage capacity in tea plantations, which has not been extensively explored in previous research
Static Response and Failure Analysis of Anisotropic Parts Printed using Fused Filament Fabrication
No full textThesis (Master's)--University of Washington, 2025Additively manufactured polymer parts produced via Fused Filament Fabrication (FFF) exhibit direction-dependent behavior as a result of the deposition process. This anisotropy presents a challenge for aerospace applications, where material properties and failure mechanisms vary depending on the orientation of the material. To accurately model and anticipate the behavior of Poly-Ether-Ether-Ketone (PEEK), a high-strength and high-temperature thermoplastic, this study explored strain limit failure mechanics. Uniaxial tension tests were performed on custom-dimensioned PEEK dogbone coupons across multiple material orientations and print rasters. Digital Image Correlation enabled full-field strain measurement across coupon surfaces and a "Strain Tornado" method was developed to interpret locally oriented strains. This analysis revealed the orientation-dependent strain limits and failure trends both between different material orientations and between FFF print rasters. A MATLAB Finite Element program was developed, incorporating transverse isotropy to predict anisotropic material behavior. Beam case studies explored this strain-based approach for flexural loading. These results establish the foundation for reliable strain-based design methods, building design confidence of 3D-printed PEEK in aerospace applications
Validation of an ultrasound-embedded shoe for calculating stiffness of the plantar soft tissue
No full textThesis (Master's)--University of Washington, 2025In the United States, diabetes affects approximately 38.4 million people, or 11.6% of the population, including nearly 29% of adults aged 65, and older and can lead to foot complications such as peripheral neuropathy and ulceration. Quantifying tissue-level structural changes due to diabetes may improve our understanding of ulcer formation. This work focused on the Ultrashoe, a device that integrates an ultrasound sensor and load cells to assess plantar soft tissue mechanics. To calculate stiffness, the Ultrashoe must accurately measure both force and displacement. The most accurate speeds of sound for the plantar tissue were identified as 1600 m/s for the heel and 1660 m/s for the second metatarsal head. Load cell error was found to be acceptable. In cadaver testing, stiffness increased with loading frequency and decreased with higher assumed sound speed. This work represents an important validation step toward using the Ultrashoe to study diabetes-related structural changes in the foot and to explore its potential integration with plantar pressure measurements to investigate the effect of diabetes in the foot
Adapting and Customizing Machine Learning Models for Renal Pathology Tissue Segmentation
No full textThesis (Master's)--University of Washington, 2025Adaptation and customization of machine learning models in renal pathology remain an obstacle to researchers' rapid development of computational renal pathology and clinician’s implementation of the
published machine learning models. The challenge of adapting and customizing renal pathological models
is due to a lack of documentation, data disclosure, and open-source code. To bridge the gap between
published models and researchers trying to make use of them, we present a general framework for
adapting and customizing machine learning models and a working pipeline in the context of renal
pathology image analysis. We leveraged the post-transplant renal data from our collaborators and the
Omni-Seg model trained with minimum change disease to create the Auto-OSeg pipeline. Auto-OSeg
pipeline can automatically predict pathology image data in .ndpi format, retrain models, and produce test
accuracies for the retrained models. Auto-OSeg pipeline is repeatable with automation, accessible through
detailed documentation, and expandable with functionally separate scripts. We also provided a framework
for the general process of adaptation and customization to help organize the process of adapting image
segmentation models in general: data relevance assessment, model assessment, customization
implementation, and adaptation and retraining assessment. Auto-OSeg pipeline’s retraining and
predictions have shown initial signs of accuracy improvements and will provide a strong foundation for
future optimizations