The 2020 guidlines recommend Bayesian estimation of AUC as the preferred vancomycin dosing method. The change is based on clinical evidence that the ratio of AUC<\/a> to Minimum Inhibitory Concentration (MIC), or AUC:MIC, is a more useful pharmacodynamic parameter to estimate vancomycin exposure, predict effectiveness, improve patient safety, and lower the risk of adverse events<\/a>, especially acute kidney injury (AKI).3-5 <\/sup>An AUC:MIC ratio \u2265400 is recommended for optimizing efficacy while minimizing the risk of adverse events.<\/p>\n\n\n\n When the 2009 guidelines were published, commercially available Bayesian dosing software tools were not yet widely available. For years, hospital clinicians had to perform AUC calculations by hand using two vancomycin serum concentration levels. Now, with Bayesian dosing software, you have the option to streamline care and make precise vancomycin recommendations before the first dose is given. As new patient data becomes available, you can make dosing regimen adjustments quickly and easily. Your team will never want to go back.<\/p>\n\n\n\n Cost-saving opportunities for your institution can be substantial, including fewer vancomycin laboratory draws, improved patient safety, lower costs related to adverse events, streamlined workflow, and reduced labor costs for your institution.<\/p>\n\n\n\n The concept of Bayesian dosing<\/a> is based on Bayes\u2019 Theorem, which is a statistical method that is used to determine the probability of an event occurring based on conditions placed on the event and past data.6<\/sup><\/p>\n\n\n\n In Bayesian vancomycin dosing, a population model forms the Bayesian prior and is used as a starting point for calculating individualized vancomycin dosing recommendations. Then, as new information about the patient’s unique Vancomycin pharmacokinetics becomes available, the regimen can be recalculated.<\/p>\n\n\n\n With Bayesian dosing software, algorithms use published population models that take into account patient details, such as height, weight, sex, and genotype. Several vancomycin models<\/a> are available within DoseMeRx, including:<\/p>\n\n\n\n Visit our Bayesian dosing resource hub<\/a> to learn more about the benefits, clinical evidence, and science behind Bayesian dosing to improve mortality, risk, and patient outcomes.<\/em><\/p>\n\n\n\n Leading hospitals, pharmacy services, infusion services, and outpatient clinics are implementing Bayesian dosing software for vancomycin dosing. Following are some key benefits keep in mind when considering your strategy for vancomycin dosing.<\/p>\n\n\n\n For years, pharmacists have based vancomycin dosing based on trough vancomycin concentrations. The 2020 vancomycin dosing guidelines recommend a shift away from dosing based on the vancomycin trough levels alone, in favor of the AUC:MIC ratio.<\/p>\n\n\n\n The change is based on clinical evidence<\/a> that this approach reduces exposure and the risk of toxicity. With the implementation of Bayesian software, your institution\u2019s adherence to the 2020 guidelines can be seamlessly integrated into your workflow.<\/p>\n\n\n\n With Bayesian dosing software such as DoseMeRx, you can immediately view your patient\u2019s pharmacokinetic responses to previous doses, simulate individualized dosage recommendations, and create customizable progress notes in your electronic health record (EHR).<\/p>\n\n\n\n Intravenous vancomycin dosing via a targeted AUC has shown a lower risk of AKI.7,8<\/sup> Bayesian dosing software allows you to model a predicted dosing outcome before you administer doses to your patients. The software helps you easily keep your patients within therapeutic range, improve patient safety, and reduce the risk of AKI and other adverse events at your institution.<\/p>\n\n\n\n While two levels are still recommended according to the 2020 vancomycin dosing guidelines, with Bayesian dosing you can calculate an AUC with a single vancomycin level. Levels can be obtained within the first 24 to 48 hours of therapy, so you no longer have to wait until steady-state is achieved.<\/p>\n\n\n\n There\u2019s nothing more inconvenient than having to ask a nurse to draw a trough level in the middle of the night. Because Bayesian models are dynamic, you can generate a dose recommendation at any time, without being stuck with the rigid laboratory draw and dosing schedules of trough-based vancomycin dosing.<\/p>\n\n\n\n Bayesian dosing software allows a streamlined workflow and collaborative team approach to therapy in the following ways.<\/p>\n\n\n\n Visit our <\/em>guide<\/a> to learn more about the benefits of Bayesian dosing.<\/em><\/em><\/p>\n\n\n\n Implementing Bayesian dosing software for vancomycin requires a tailored solution to fit your health system\u2019s budget and workflow. If you are updating your vancomycin dosing protocol<\/a> to adhere to new guidelines, you will need to determine your institution\u2019s vancomycin dosing approach based on specific patient parameters, monitoring protocols, management of laboratory draws, and integration with your EHR. Your interdisciplinary team will need to be trained and supported in your transition<\/a>, including physicians, pharmacists, nursing, laboratory, and information technology.<\/p>\n\n\n\n Did you know that Bayesian software can be integrated into electronic health record systems, allowing for even faster data entry and interpretation? Partner with your information technology team from the start to streamline your implementation.<\/em><\/p>\n\n\n\n When selecting AUC-based dosing approaches, the options include home-grown spreadsheets, free online web-based calculators<\/a>, and Bayesian dosing software. When evaluating the costs versus benefits of implementing Bayesian software for vancomycin at your institution, you\u2019ll need to consider the cost of software against the projected savings.<\/p>\n\n\n\n Potential cost savings include:<\/p>\n\n\n\n A cost-benefit analysis study<\/a> designed to evaluate the costs of two-sample AUC and single-sample Bayesian strategies, versus trough-guided dosing, found significant institutional cost savings with the software.9<\/sup> For each patient encounter, two-sample AUC dosing saved an average of $846 over trough-based dosing, whereas single-sample Bayesian dosing saved an average of $2,065. The analysis assumed 1,000 vancomycin-treated patients per year and a budget of $100,000 per year for Bayesian software. According to the study, an institution would need to treat at least 41 patients with vancomycin for at least 48 hours to break even.<\/p>\n\n\n\n To learn more about the different options for Bayesian dosing and to find out which approach is right for you, visit our guide<\/a><\/em>.<\/p>\n\n\n\n When you are considering your transition from trough-based dosing to AUC:MIC, there are several considerations to take into account. In transitioning to AUC dosing for vancomycin to comply with the 2020 guidelines, DoseMeRx provides a fully supported Bayesian dosing software solution for dosing and monitoring vancomycin that helps you make a seamless transition.<\/p>\n\n\n\n When you’re ready to try DoseMeRx, kick things off by setting up a discovery call<\/a> to identify your individual needs and get the most out of your free trial of the platform.<\/em><\/p>\n\n\n\n For years, pharmacists have been basing vancomycin dosing based on trough levels. However, several studies have shown that targeted trough levels of 15-20 mcg\/mL had a tendency to overshoot optimal dosage and increase the risk of AKI. Therefore, the updated 2020 vancomycin dosing guidelines recommend moving away from trough levels in favor of dosing based on AUC. More specifically, area under the serum concentration versus time curve for 0-24 hours (AUC24<\/sub>), which is proportional to the total daily dose, has emerged as the preferred method for monitoring vancomycin therapy in patients with staphylococcal bacteremia, endocarditis, and invasive infection. A ratio of AUC to MIC, with a target AUC:MIC ratio of 400-600, is recommended for reliable efficacy while improving patient safety and minimizing the risk of AKI.10<\/sup><\/p>\n\n\n\n The Bayesian dosing model for vancomycin uses patient data and population data to estimate a patient\u2019s pharmacokinetic parameters and create individualized dosing recommendations. The concept of Bayesian dosing is based on Bayes\u2019 Theorem, a statistical method to determine the probability of an event occurring based on past data and current conditions. Before laboratory results are available, published population data can be used to predict pharmacokinetic parameters for an individual patient. As laboratory results become available, the regimen can be recalculated to individualize dosing to reach a therapeutic target.<\/p>\n\n\n\n Implementing Bayesian methods for vancomycin dosing requires a custom solution to fit your needs. You will want to consider the cost of Bayesian dosing software<\/a> against potential cost savings, such as fewer laboratory draws, reduced costs associated with adverse events, and reduced labor costs, especially in pharmacy and laboratory.11<\/sup><\/p>\n\n\n\n If you are integrating Bayesian software with your EHR, your information technology team will be involved in the process. If you are updating your facility\u2019s vancomycin strategy from trough-based to AUC-based dosing, you will need to determine your institution\u2019s dosing approach and patient parameters for inclusion in Bayesian dosing. Your interdisciplinary team will be engaged in the transition, including pharmacists, laboratory, nursing, and physicians.<\/p>\n\n\n Scopri quanto \u00e8 facile usare e integrare DoseMeRx nel tuo lavoro quotidiano.<\/p>\n Richiedi una dimostrazione di prova qui sotto. Puoi anche chiamarci al numero +1 (832) 358-3308<\/a>\u00a0oppure scriverci all\u2019indirizzo\u00a0hello@dosemehealth.com<\/a><\/p>\n<\/div>\t\t\r\n\r\nWhat is Bayesian Vancomycin Dosing?<\/h2>\n\n\n\n
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<\/li><\/ul>\n\n\n\nBenefits of Integrating Bayesian Dosing Software into an Electronic Health Record<\/h2>\n\n\n\n
1. Adhere to Current Vancomycin Dosing Guidelines<\/h3>\n\n\n\n
2. Individualize Patient Care<\/h3>\n\n\n\n
3. Reduce Adverse Events<\/h3>\n\n\n\n
4. Streamline Lab Draws and Dosing Times<\/h3>\n\n\n\n
5. Integrate and Optimize Workflow<\/h3>\n\n\n\n
Considerations When Implementing a Bayesian Dosing Solution for Vancomycin<\/h2>\n\n\n\n
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<\/figure>\n\n\n\nPro Tip<\/h3>\n\n\n\n
The Cost of Bayesian Dosing Software for Vancomycin<\/h2>\n\n\n\n
<\/li><\/ul>\n\n\n\nStreamline Vancomycin Dosing with DoseMeRx<\/h2>\n\n\n\n
<\/li><\/ul>\n\n\n\nFAQs<\/h2>\n\n\n\n
1) What is AUC dosing for vancomycin?
<\/h3>\n\n\n\n2) What is the Bayesian model for vancomycin?<\/h3>\n\n\n\n
3) What are the keys to the successful application of Bayesian methods?<\/h3>\n\n\n\n
Richiedi una dimostrazione di prova<\/h2>\r\n\t