Research Objective The Home Health Value‐Based Purchasing (HHVBP) Model provides financial incentives for quality improvement to home health agencies in nine states with the goal of improving quality and efficiency of care for Medicare beneficiaries. The maximum Medicare payment adjustment increases during each of the five years of the model, ranging from ±3% in 2018 to ±8% in 2022. Our goal is to understand the early impact of the HHVBP Model on quality, utilization, and Medicare spending during its first three years (2016–2018), which includes the first year in which payment adjustments to agencies took effect. Study Design CMS randomly selected nine states to participate in the HHVBP Model starting January 2016, with mandatory participation from all agencies. Agencies in these states received performance scores for 20 measures of quality of care used to determine their payment adjustment relative to other agencies within their state. To evaluate the effects of HHVBP, we used a difference‐in‐differences design and multivariate linear regression to compare differences in the changes in outcomes of the nine HHVBP states with those in the 41 comparison states for three years pre‐intervention (2013–2015) through the first three years of the model (2016–2018). We evaluated agency performance using Outcome and Assessment Information Set (OASIS)‐based quality measures and measures of claims‐based Medicare fee‐for‐service (FFS) health care utilization and spending. Population Studied Medicare and Medicaid patients receiving home health care in the nine HHVBP states and forty‐one comparison states. Principal Findings We found evidence of slightly greater improvements in most measures of improved functional status used to determine payment adjustments in HHVBP states relative to non‐HHVBP states. Compared to non‐HHVBP states, Medicare FFS beneficiaries who received home health care in the nine HHVBP states had a relative decrease in unplanned hospitalization rate (−1.8%) and in skilled nursing facility (SNF) stays (−4.9%) from pre‐HHVBP implementation average levels. Conversely, we observed a 2.4% increase in emergency department (ED) visits relative to the average pre‐implementation rates for HHVBP states. Overall, we found evidence of a 1.2% reduction in Medicare spending due to HHVBP, corresponding to an average $141 million reduction in annual Medicare spending in HHVBP states over the first three years of the model. The reduction in spending among home health Medicare FFS patients was driven primarily by reductions in inpatient hospital spending (−2%) and SNF spending (−4%). We did not find an appreciable difference in savings between the third year—in which payment adjustments were applied—and the first two years of the model prior to HHVBP agencies receiving payment adjustments. Conclusions Through the HHVBP Model's first three years—which includes the first year of payment adjustments to agencies—we found modest impacts of HHVBP: lower growth in Medicare spending, declines in unplanned hospitalizations and use of...

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ImportanceThe original Home Health Value-Based Purchasing (HHVBP) model provided financial incentives to home health agencies for quality improvement in 9 randomly selected US states.ObjectiveTo evaluate quality, utilization, and Medicare payments for home health patients in HHVBP states compared with those in comparison states.Design, Setting, and ParticipantsThis cohort study was conducted in 2021 with secondary data from January 2013 to December 2020. A difference-in-differences design and multivariate linear regression were used to compare outcomes for Medicare and Medicaid beneficiaries who received home health care in HHVBP states with those in 41 comparison states during 3 years of preintervention (2013-2015) and the subsequent 5 years (2016-2020).ExposuresHome health care provided by a home health agency in HHVBP states and comparison states.Main Outcomes and MeasuresUtilization (unplanned hospitalizations, emergency department visits, skilled nursing facility [SNF] visits) for Medicare beneficiaries within 60 days of beginning home health, Medicare payments during and 37 days after home health episodes, and quality of care (functional status, patient experience) during home health episodes.ResultsAmong 34 058 796 home health episodes (16 584 870 beneficiaries; mean [SD] age of 76.6 [11.7] years; 60.5% female; 11.2% Black non-Hispanic; 79.5% White non-Hispanic) from January 2016 to December 2020, 22.6% were in HHVBP states and 77.4% were in non-HHVBP states. For the HHVBP and non-HHVBP groups, 60.4% and 61.0% of episodes were provided to female patients; 10.0% and 13.6% were provided to Black non-Hispanic patients, and 82.4% and 75.2% were provided to White non-Hispanic patients, respectively. Unplanned hospitalizations decreased by 0.15 percentage points (95% CI, –0.30 to –0.01) more in HHVBP states, a 1.0% decline compared with 15.7% at baseline. The use of SNFs decreased by 0.34 percentage points (95% CI, –0.40 to –0.27) more in HHVBP states, a 6.9% decline compared with the 4.9% baseline average. There was an association between HHVBP and a reduction in average Medicare payments per day of $2.17 (95% CI, –$3.67 to –$0.68) in HHVBP states, primarily associated with reduced inpatient and SNF services, which corresponded to an average annual Medicare savings of $190 million. There was greater functional improvement in HHVBP states than comparison states and no statistically significant change in emergency department use or most measures of patient experience.Conclusions and RelevanceIn this cohort study, the HHVBP model was associated with lower Medicare payments that were associated with lower utilization of inpatient and SNF services, with better or similar quality of care.

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Loss factor is one of the most significant parameters of Statistical Energy Analysis (SEA) which represents the damping loss characteristics of a system and indicates the ability of its vibration energy consumption. In order to estimate it, the power input method (PIM) and the impulse response decay method (IRDM) have become widely used especially when the object of study is made of Fiber Reinforced Plastics (FRP) of which dynamic interaction is really complicated. Numerical simulation is also applied to analyze the loss factor of the spring-damping-system with single degree of freedom (SDOF) using MATLAB to introduce the identification procedure of PIM and IRDM. With the comparison of the methods, the analytical study indicates these techniques are effective for the estimation of loss factor. This paper focuses on an experimental approach to get the SEA loss factor of FRP plate and the test investigations are performed in detail. The requirements and limitations of each method applied are discussed and PIM is a better solution dealing with this kind of the composite material. The loss factor of test specimen is obtained to provide a valuable reference for the prediction and control of vibration and noise of yachts with SEA.