Publications by authors named "G Hripcsak"
Article Synopsis
- This study compares the cardiovascular effectiveness of different second-line antihyperglycemic agents (SGLT2 inhibitors, GLP-1 receptor agonists, DPP-4 inhibitors, and sulfonylureas) in patients with type 2 diabetes and cardiovascular disease.
- Using data from over 1.4 million patients across multiple databases, the researchers analyzed the risk of major adverse cardiovascular events (MACE) over a follow-up period of several years.
- Results indicated that SGLT2 inhibitors and GLP-1 receptor agonists had significantly lower risks of MACE compared to DPP-4 inhibitors and sulfonylureas, pointing to their potential superiority as treatment options for
Article Synopsis
- The study explores using patient portal messaging to recruit underrepresented individuals for the All of Us Research Program, aiming to improve diversity in biomedical research.
- A large-scale outreach was conducted at Columbia University, where over 59,000 patients were messaged, resulting in a 15.1% response rate and showing varying engagement levels among different racial and ethnic groups.
- While the method increased outreach efficiency, the researchers found that underrepresented groups struggled more with initial consent and message engagement, highlighting the need for targeted strategies to enhance participation.
Objective: Healthcare continues to grapple with the persistent issue of treatment disparities, sparking concerns regarding the equitable allocation of treatments in clinical practice. While various fairness metrics have emerged to assess fairness in decision-making processes, a growing focus has been on causality-based fairness concepts due to their capacity to mitigate confounding effects and reason about bias. However, the application of causal fairness notions in evaluating the fairness of clinical decision-making with electronic health record (EHR) data remains an understudied domain.
View Article and Find Full Text PDFPropensity score adjustment addresses confounding by balancing covariates in subject treatment groups through matching, stratification, inverse probability weighting, etc. Diagnostics ensure that the adjustment has been effective. A common technique is to check whether the standardized mean difference for each relevant covariate is less than a threshold like 0.
View Article and Find Full Text PDFArticle Synopsis
- Translational research needs data from different levels of biological systems, but combining that data is tough for scientists.
- New technologies help gather more data, but researchers struggle to organize all the information effectively.
- PheKnowLator is a tool that helps scientists create customizable knowledge graphs easily, making it better for managing complex health information without slowing down their work.