Hospital Readmissions Reduction Program: An Economic and Operational Analysis

The Hospital Readmissions Reduction Program (HRRP), a part of the U.S. Patient Protection and Affordable Care Act, requires the Centers for Medicare and Medicaid Services to penalize hospitals with excess readmissions. We take an economic and operational (patient flow) perspective to analyze the effectiveness of this policy in encouraging hospitals to reduce readmissions. We develop a game-theoretic model that captures the competition among hospitals inherent in HRRP’s benchmarking mechanism. We show that this competition can be counterproductive: it increases the number of nonincentivized hospitals, which prefer paying penalties over reducing readmissions in any equilibrium. We calibrate our model with a data set of more than 3,000 hospitals in the United States and show that under the current policy, and for a large set of parameters, 4%–13% of the hospitals remain nonincentivized to reduce readmissions. We also validate our model against the actual performance of hospitals in the three years since the introduction of the policy. We draw several policy recommendations to improve this policy’s outcome. For example, localizing the benchmarking process—comparing hospitals against similar peers—improves the performance of the policy

Why Chromatic Imaging Matters

During the last two decades, the first generation of beam combiners at the Very Large Telescope Interferometer has proved the importance of optical interferometry for high-angular resolution astrophysical studies in the near- and mid-infrared. With the advent of 4-beam combiners at the VLTI, the u-v coverage per pointing increases significantly, providing an opportunity to use reconstructed images as powerful scientific tools. Therefore, interferometric imaging is already a key feature of the new generation of VLTI instruments, as well as for other interferometric facilities like CHARA and JWST. It is thus imperative to account for the current image reconstruction capabilities and their expected evolutions in the coming years. Here, we present a general overview of the current situation of optical interferometric image reconstruction with a focus on new wavelength-dependent information, highlighting its main advantages and limitations. As an Appendix we include several cookbooks describing the usage and installation of several state-of-the art image reconstruction packages. To illustrate the current capabilities of the software available to the community, we recovered chromatic images, from simulated MATISSE data, using the MCMC software SQUEEZE. With these images, we aim at showing the importance of selecting good regularization functions and their impact on the reconstruction.Comment: Accepted for publication in Experimental Astronomy as part of the topical collection: Future of Optical-infrared Interferometry in Europ

Longitudinal T1 relaxation rate (R1) captures changes in short-term Mn exposure in welders

We demonstrated recently that the T1 relaxation rate (R1) captured short-term Mn exposure in welders with chronic, relatively low exposure levels in a cross-sectional study. In the current study, we used a longitudinal design to examine whether R1 values reflect the short-term dynamics of Mn exposure

Increased R2* in the Caudate Nucleus of Asymptomatic Welders

Welding has been associated with neurobehavioral disorders. Welding fumes contain several metals including copper (Cu), manganese (Mn), and iron (Fe) that may interact to influence welding-related neurotoxicity. Although welding-related airborne Fe levels are about 10-fold higher than Mn, previous studies have focused on Mn and its accumulation in the basal ganglia. This study examined differences in the apparent transverse relaxation rates [R2* (1/T2*), estimate of Fe accumulation] in the basal ganglia (caudate nucleus, putamen, and globus pallidus) between welders and controls, and the dose–response relationship between estimated Fe exposure and R2* values. Occupational questionnaires estimated recent and lifetime Fe exposure, and blood Fe levels and brain magnetic resonance imaging (MRI) were obtained. Complete exposure and MRI R2* and R1 (1/T1: measure to estimate Mn accumulation) data from 42 subjects with welding exposure and 29 controls were analyzed. Welders had significantly greater exposure metrics and higher whole-blood Fe levels compared with controls. R2* in the caudate nucleus was significantly higher in welders after controlling for age, body mass index, respirator use, caudate R1, and blood metals of Cu and Mn, whereas there was no difference in R1 values in the basal ganglia between groups. The R2* in the caudate nucleus was positively correlated with whole-blood Fe concentration. This study provides the first evidence of higher R2* in the caudate nucleus of welders, which is suggestive of increased Fe accumulation in this area. Further studies are needed to replicate the findings and determine the neurobehavioral relevance

Nonadherence in hemodialysis: Associations with mortality, hospitalization, and practice patterns in the DOPPS

Nonadherence in hemodialysis: Associations with mortality, hospitalization, and practice patterns in the DOPPS.BackgroundNonadherence among hemodialysis patients compromises dialysis delivery, which could influence patient morbidity and mortality. The Dialysis Outcomes and Practice Patterns Study (DOPPS) provides a unique opportunity to review this problem and its determinants on a global level.MethodsNonadherence was studied using data from the DOPPS, an international, observational, prospective hemodialysis study. Patients were considered nonadherent if they skipped one or more sessions per month, shortened one or more sessions by more than 10 minutes per month, had a serum potassium level openface>6.0mEq/L, a serum phosphate level openface>7.5mg/dL (>2.4mmol/L), or interdialytic weight gain (IDWG)>5.7% of body weight. Predictors of nonadherence were identified using logistic regression. Survival analysis used the Cox proportional hazards model adjusting for case-mix.ResultsSkipping treatment was associated with increased mortality [relative risk (RR) = 1.30, P = 0.01], as were excessive IDWG (RR = 1.12, P = 0.047) and high phosphate levels (RR = 1.17, P = 0.001). Skipping also was associated with increased hospitalization (RR = 1.13, P = 0.04), as were high phosphate levels (RR = 1.07, P = 0.05). Larger facility size (per 10 patients) was associated with higher odds ratios (OR) of skipping (OR = 1.03, P = 0.06), shortening (OR = 1.03, P = 0.05), and IDWG (OR = 1.02, P = 0.07). An increased percentage of highly trained staff hours was associated with lower OR of skipping (OR = 0.84 per 10%, P = 0.02); presence of a dietitian was associated with lower OR of excessive IDWG (OR = 0.75, P = 0.08).ConclusionNonadherence was associated with increased mortality risk (skipping treatment, excessive IDWG, and high phosphate) and with hospitalization risk (skipping, high phosphate). Certain patient/facility characteristics also were associated with nonadherence

Human Proteome Project Mass Spectrometry Data Interpretation Guidelines 3.0

The Human Proteome Organization’s (HUPO) Human Proteome Project (HPP) developed Mass Spectrometry (MS) Data Interpretation Guidelines that have been applied since 2016. These guidelines have helped ensure that the emerging draft of the complete human proteome is highly accurate and with low numbers of false-positive protein identifications. Here, we describe an update to these guidelines based on consensus-reaching discussions with the wider HPP community over the past year. The revised 3.0 guidelines address several major and minor identified gaps. We have added guidelines for emerging data independent acquisition (DIA) MS workflows and for use of the new Universal Spectrum Identifier (USI) system being developed by the HUPO Proteomics Standards Initiative (PSI). In addition, we discuss updates to the standard HPP pipeline for collecting MS evidence for all proteins in the HPP, including refinements to minimum evidence. We present a new plan for incorporating MassIVE-KB into the HPP pipeline for the next (HPP 2020) cycle in order to obtain more comprehensive coverage of public MS data sets. The main checklist has been reorganized under headings and subitems, and related guidelines have been grouped. In sum, Version 2.1 of the HPP MS Data Interpretation Guidelines has served well, and this timely update to version 3.0 will aid the HPP as it approaches its goal of collecting and curating MS evidence of translation and expression for all predicted ∼20 000 human proteins encoded by the human genome.This work was funded in part by the National Institutes of Health grants R01GM087221 (EWD/RLM), R24GM127667 (EWD), U54EB020406 (EWD), R01HL133135 (RLM), U19AG02312 (RLM), U54ES017885 (GSO), U24CA210967-01 (GSO), R01LM013115 (NB) and P41GM103484 (NB); National Science Foundation grants ABI-1759980 (NB), DBI-1933311 (EWD), and IOS-1922871 (EWD); Canadian Institutes of Health Research 148408 (CMO); Korean Ministry of Health and Welfare HI13C2098 (YKP); French Ministry of Higher Education, Research and Innovation, ProFI project, ANR-10-INBS-08 (YV); also in part by the National Eye Institute (NEI), National Human Genome Research Institute (NHGRI), National Heart, Lung, and Blood Institute (NHLBI), National Institute of Allergy and Infectious Diseases (NIAID), National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institute of General Medical Sciences (NIGMS), and National Institute of Mental Health (NIMH) of the National Institutes of Health under Award Number U24HG007822 (SO) (the content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health)