Vakaramoko (Karam) Diaby’s Post

if you have been toying with the idea of leveraging R Shiny for health economic assessment and wonder if there are resources you can use, look no further. my colleague Vakaramoko (Karam) Diaby has a workshop on this very topic that will be hosted by ISPOR. Pls see details below and enroll in this workshop.

 Revolutionizing RCTs: Boosting Power with Observational Data Tired of limited sample sizes hindering your RCTs?  Xi Lin et. al. (2023) new power likelihood approach offers a game-changer! By combining RCTs with observational data, they're significantly improving causal inference for underrepresented subgroups. Key benefits: Increased statistical power Enhanced causal inference for underrepresented subgroups Data-adaptive learning rate for optimal information integration Connect with us to learn more about our method and how it can benefit your research. Share your thoughts on the challenges you face in your work. #RCTs #CausalInference #ObservationalData #DataScience #Research #Healthcare #Statistics https://lnkd.in/g2aaaA2i

Many thanks for submitting to #PharmacoEconomics

Are you passionate about using some if not all of your prior knowledge to inform your decisions? Then this educational tutorial on how to perform Bayesian meta-analysis of health state utility values using R is a must-read for you! https://lnkd.in/deaFXJ7Z Bayesian meta-analysis stands out for several reasons: 1. Valuable prior information: Integrates previous study findings to enhance the meta-analysis, providing more robust and precise estimates. 2. Explicit heterogeneity handling:  More transparently handles the degree of heterogeneity among studies, which is crucial since utility values can be highly variable across studies. 3. Enhanced uncertainty assessment: Generates comprehensive posterior distributions, allowing for better assessment of uncertainties around estimates. This can be incorporated into probabilistic sensitivity analysis during cost-utility analyses—enabling clearer interpretation and informed decision-making. Imagine harnessing these capabilities to produce precise, reliable estimates and make well-informed inferences about utility values. Be empowered—embrace Bayesian meta-analysis in your health economic modelling projects. After all, Bayesian is just intuitive! Thank you, Joseph Alvin Ramos Santos, Robert Grant, and Gian Luca Di Tanna, for sharing your knowledge and empowering us!! #Research #BayesianAnalysis #MetaAnalysis #HSUV

Ready to boost your public health knowledge? Enroll in our newly launched self-paced online courses in Research Methodology, Biostatistics, and Health Economics! These courses are your gateway to becoming a more skilled professional. Join public health experts from around the world in shaping the future of health. Start your journey today and become a leader in global health innovation! Learn More and Enroll: https://bit.ly/3WWLcpR #PublicHealth #ResearchMethodology #Biostatistics #HealthEconomics #IAPH #ProfessionalDevelopment

We are pleased to share our latest paper, "Bayesian Meta-Analysis of Health State Utility Values: A Tutorial with Practical Application in Heart Failure," published in #PharmacoEconomics. https://lnkd.in/deaFXJ7Z This tutorial is designed to support researchers in generating robust pooled estimates of health state utility values to inform economic evaluations. Specifically, this work shows the applicability of #Bayesian #meta-analysis for pooling health state utility values through an illustrative example among patients with heart failure.   Using data from a systematic review encompassing 21 studies and ready-to-use codes and scripts, this study provides a step-by-step guide for conducting Bayesian meta-analysis using #R. The tutorial adheres to the structured workflow as follows:   - Setting up the data - Imputing missing standard deviations - Defining the priors - Fitting the model - Diagnosing model convergence - Interpreting results - Performing sensitivity analyses   We showed that the pooled utility value for #HeartFailure was 0.66 with a 95% credible interval of [0.60, 0.70] which was consistent across a series of scenarios according to the imputation of missing standard deviations.   This tutorial aimed to foster interest in Bayesian methods and their application to bridge the gap in estimating health state utility values for economic evaluations and policy decisions. We encourage the adoption of Bayesian meta-analysis in synthesising utility values, as it offers a principled means to integrate prior knowledge and handle heterogeneity, leading to intuitive probabilistic interpretations that are critical in decision making.   Robert Grant Chris Carswell

The OM1 team will be at ISPOR—The Professional Society for Health Economics and Outcomes Research in Atlanta! Stop by the booth, or schedule a meeting with us 📩 (info@om1.com) to discuss: ✅ Predictive #AI and #digitalphenotying that synthesizes patterns from a range of data sources to identify patients of interest and deliver personalized care ✅ Transformed insights driven by representative clinical data linked to various sources, including #SDoH, claims, and mortality ✅ Leverage #RWD to identify interventions that are most effective for specific patient populations Rich Gliklich, Shawn W. Bates, Sonja Wustrack, Eric Schrock, Jessica Probst, Tom Engel, Matthew Jungers, MBA, David Giannino Samantha C. Register, MBA, Monika J. Dziuba (Nowak), Bradley Snipes #ISPORAnnual #HEOR #DigitalHealth

We’re ready to hit the floor at ISPOR—The Professional Society for Health Economics and Outcomes Research Europe and deliver better access to real-world data (#RWD)! 🤘 If you spot Dr Or Shaked, MD-MPH and Ruth Levi Lotan, Briya’s Medical Research Lead and VP of Sales, be sure to stop them and learn how better, faster access to high-quality real-world data can transform your research and #ClinicalTrial projects. Reliable data is the foundation for generating robust scientific evidence and is essential for health economics and outcomes research (#HEOR). Yet too often, data is outdated, fragmented, or incomplete, leading to less impactful and inaccurate outcomes. Briya's RWD access platform is changing the game with live data. We deliver accurate, comprehensive real-world data to enable the most reliable and impactful results.💡 #ISPOREU #Ispor #HEOR

Are you interested in improving your team’s processes to make collaborative science more effective and efficient? MICHR (Michigan Institute for Clinical & Health Research) is actively recruiting for a #NIH funded study: Information Management Prototype for Clinical and Translational Research (IMPACT-CTR). This study will evaluate tools and strategies teams use to conduct collaborative translational research. Findings will be used to develop a learning module to help teams improve their approach to information management. Learn more about participating in this study here: https://ow.ly/u0tq50UcHkC #TranslationalScience #InformationManagement #CollaborativeScience #CTSAProgram

#ITACAScience 🔵 Today we share an article📝 with the participation of 👨🔬 Pablo  Ferri, Carlos Sáez and Juan Miguel García, researchers from BDSLab - Biomedical Data Science Lab - ITACA (UPV). ✏️This study developes and evaluates a deep classifier that can  effectively prioritize Emergency Medical Call Incidents (#EMCI) according to their life-threatening level under the presence of dataset shifts. 👨🏫"Considering the advanced capabilities of deep continual text models in assessing the life-threatening level of the most severe incidents, the implementation of the CL routines developed in this study for EMCI triage will have a significant and positive direct impact on patient well-being and the sustainability of health services", say the ITACA researchers. 👉Full article here🔗: https://lnkd.in/d6aEjQs7 #ITACAScience #DeepLearning #EmergencyCare #MedicalInnovation