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Cost Savings Associated With Decolonization of Postdischarge MRSA Carriers: Results From the CLEAR Randomized Trial
- Natasha K. Stout, Grace M. Lee, Anastasiia S. Weiland, Caleb S. Chen, Syma Rashid, Raveena D. Singh, Thomas Tjoa, Jiayi He, James A. McKinnell, Loren G. Miller, Susan S. Huang
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- Journal:
- Infection Control & Hospital Epidemiology / Volume 41 / Issue S1 / October 2020
- Published online by Cambridge University Press:
- 02 November 2020, pp. s28-s29
- Print publication:
- October 2020
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Background: Greater than 10% of hospitalized MRSA carriers experience serious MRSA infection in the year following discharge. Prevention opportunities have primarily focused on hospital stays; however postdischarge interventions have the potential to reduce morbidity, mortality and healthcare costs. The CLEAR trial found a 30% hazard reduction in postdischarge MRSA infections among patients who had inpatient MRSA cultures and were given postdischarge decolonization (5 days twice-a-month for 6 months) relative to hygiene education alone. We conducted a cost analysis of the CLEAR intervention to quantify the economic implications and understand the value of adopting this MRSA decolonization strategy. Methods: We constructed a decision model to estimate the one-year healthcare utilization and costs associated with postdischarge decolonization relative to hygiene education. Trial results for MRSA infection risk and downstream outcomes (including outpatient and emergency room visits, hospitalizations, related nursing home stays, and postdischarge antibiotics) were used to parameterize the model. Other medical care and prescription drug costs were based on Medicare Fee Schedules, Red Book and the literature. Patient out-of-pocket costs and time costs associated with subsequent infections were from a survey of trial participants experiencing infection (n=405). All costs were reported in 2019 US dollars. The analysis was conducted using healthcare system and societal perspectives. Sensitivity analyses were conducted on key parameters. Results: Among a hypothetical cohort of 1,000 hospitalized MRSA carriers, we estimated that a postdischarge decolonization intervention versus hygiene education would result in at least 36 fewer subsequent MRSA infections (130 vs 93 of 1,000, respectively) and >40 fewer MRSA-attributable healthcare events including 32 hospitalizations and 6 postdischarge nursing home visits over the course of a year. Assuming an intervention cost of $185 per individual, the program would result in an overall cost savings of $469,000 per 1,000 MRSA carriers undergoing decolonization. This translates to an overall savings of $13,200 per infection averted and $9,000 per infection averted from the healthcare system perspective. Even assuming a lower infection rate or a less effective intervention (15% reduction in infections vs 30% in the CLEAR trial), or a more expensive (up to $653 per patient) intervention, a decolonization program would still result in cost-savings for society, the healthcare system and patients. Conclusions: In addition to health benefits of preventing infections, postdischarge decolonization of MRSA carriers yields substantial savings to society and the healthcare system. Future recommendations for reducing postdischarge MRSA-related disease among MRSA carriers should consider routine decolonization at hospital discharge.
Funding: This study was supported by a grant from the AHRQ Healthcare-Associated Infections Program (R01HS019388) and by the University of California Irvine Institute for Clinical and Translational Science, which was funded by a grant from the NIH Clinical and Translational Sciences Award program (UL1 TR000153).
Disclosures: Dr. Huang reports conducting clinical studies in which participating nursing homes and hospitals received donated products from Stryker (Sage Products), Mölnlycke, 3M, Clorox, Xttrium Laboratories, and Medline. Ms. Singh reports conducting clinical studies in which participating nursing homes and hospitals received donated products from Stryker (Sage Products), 3M, Clorox, Xttrium Laboratories, and Medline. Dr. Rashid, conducting clinical studies in which participating nursing homes and hospitals received donated products from Stryker(Sage Products), Clorox, and Medline. Dr. McKinnell reports receiving grant support to his institution from Melinta Therapeutics, and fees for serving as a research investigator from Lightship, conducting clinical studies in which participating nursing homes and hospitals received donated products from Stryker (Sage Products), 3M, Clorox, Xttrium Laboratories and Medline, and serving as cofounder of Expert Stewardship. Dr. Miller reports receiving grant support from Gilead Sciences, Merck, Abbott, Cepheid, Genentech, Atox Bio, and Paratek Pharmaceuticals, grant support and fees for serving on an advisory board from Achaogen and grant support, consulting fees, and fees for serving on an advisory board from Tetraphase and conducting clinical studies in which participating nursing homes and hospitals received donated products from Stryker (Sage Products), 3M, Clorox, Xttrium Laboratories, and Medline.
Statistical Mechanics: Undamaged ⇐-radiation-⇒ Damaged Atomic Lattice Density Evolution and Stochastic Deformation Functional
- Ray B. Stout, Natasha K. Stout
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- Journal:
- MRS Online Proceedings Library Archive / Volume 887 / 2005
- Published online by Cambridge University Press:
- 26 February 2011, 0887-Q08-03
- Print publication:
- 2005
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The deformation kinematics for radiation damage response of bulk materials is presently semi-empirical and phenomenological based on a continuum mechanics supposition: there exists a function space of continuous functions to describe material displacement, strain, strain-rate metrics by using the mathematics of differential calculus. Existing data being assembled from tests on nano-length-scale(NLS) samples provide objective evidence that the continuum mechanics supposition is not an adequate generic mathematical description for radiation damage response in surface-dominated material structures at NLS. An alternative approach will be described that uses concepts and methods from classical statistical mechanics and describe deformation kinematics as a stochastic accumulation of discrete damage events at atomic lattice nano-length-scales. Although radiation damage deformation at a lattice length-scale in solids is mechanistically different from velocity scattering developed by Boltzmann for a kinetic theory of gases, the two problem areas are technically similar and in some simply cases there are useful mathematical analogs. The technical similarities and mathematical analogs will be used to define probability density functions (number per unit volume functions) for undamaged and damaged “size and size change” lattice species (similarity to a probability density function for atomic velocities in gas theory). In general, equations for undamaged and damaged lattice density function evolution are Boltzmann-type equations, which can be approximated and solved for simple cases of radiation induced material damage. Using a path integral approach and the two probability density functions, a stochastic functional will be derived for the relative deformation between any two arbitrary spatial points in a radiation damaged material. Given the relative deformation as an explicit functional of the undamaged and damaged lattice density functions, the kinematics metrics of relative velocity, strain, strain rate, etc., will also be functionals. In the case of radiation damage and annealing, the two lattice density functions are analog expressions to those commonly used to model “birth and death” population evolution.
AN ELEMENTARY INTRODUCTION TO BAYESIAN COMPUTING USING WINBUGS
- Dennis G. Fryback, Natasha K. Stout, Marjorie A. Rosenberg
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- Journal:
- International Journal of Technology Assessment in Health Care / Volume 17 / Issue 1 / January 2001
- Published online by Cambridge University Press:
- 25 May 2001, pp. 98-113
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Bayesian statistics provide effective techniques for analyzing data and translating the results to inform decision making. This paper provides an elementary tutorial overview of the WinBUGS software for performing Bayesian statistical analysis. Background information on the computational methods used by the software is provided. Two examples drawn from the field of medical decision making are presented to illustrate the features and functionality of the software.