Background: Through recent advances in omics technologies, precision medicine (PM) promises to fundamentally change the way we approach health, disease and illness. Imperative applications of omics-based biomarkers are gradually moving from research to clinical settings, with huge long-term clinical and public health implications. Whereas much of research in PM is mainly focused on basic biomedical discoveries, currently there is little research on the clinical implementation of omics biomarkers, especially at health systems level.

Aim And Methods: This study investigated the application of multidimensional item response theory (IRT) models to validate a hypothesized PM implementation measurement model. This is a contribution to PM implementation at health systems level. Data obtained through an item-sort procedure involving 496 observations from 124 study participants formed the basis of a 22-item PMI measurement model.

Conclusion: Statistical significance of the bifactor model suggests PM implementation may have to be examined using factors that reflect a single common underlying implementation construct, as well as factors that reflect unique variances for the identified four content-specific factors.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8661177PMC

Publication Analysis

Top Keywords

precision medicine
8
health systems
8
factors reflect
8
implementation
6
health
5
modeling factors
4
factors critical
4
critical implementation
4
implementation precision
4
medicine health
4

Similar Publications

Exogenous neural stem cells (NSCs) have great potential to reconstitute damage spinal neural circuitry. However, regulating the metabolic reprogramming of NSCs for reliable nerve regeneration has been challenging. This report discusses the biomimetic dextral hydrogel (DH) with right-handed nanofibers that specifically reprograms the lipid metabolism of NSCs, promoting their neural differentiation and rapid regeneration of damaged axons.

View Article and Find Full Text PDF

Sodium-glucose co-transporter 2 inhibitors, such as enavogliflozin, offer promising metabolic benefits for patients with type 2 diabetes (T2D), including glycemic control and improved cardiac function. Despite the clinical evidence, real-world evidence is needed to validate their safety and effectiveness. This study aims to evaluate the effects of weight loss and safety of enavogliflozin administration in patients with T2D in a real-world clinical setting over 24 weeks.

View Article and Find Full Text PDF

Background: Patient-reported outcome measures (PROMs) are crucial for informed medical decisions and evaluating treatments. However, they can be burdensome for patients and sometimes lack the reliability clinicians need for clear clinical interpretations.

Objective: Patient-reported outcome measures (PROMs) are crucial for informed medical decisions and evaluating treatments.

View Article and Find Full Text PDF

Background: Recent research has revealed the potential value of machine learning (ML) models in improving prognostic prediction for patients with trauma. ML can enhance predictions and identify which factors contribute the most to posttraumatic mortality. However, no studies have explored the risk factors, complications, and risk prediction of preoperative and postoperative traumatic coagulopathy (PPTIC) in patients with trauma.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!