The authors of the assigned article, “A Patient-Driven Adaptive Prediction Technique to Improve Personalized Risk Estimation for ClinicalDecision Support” (http://jamia.bmj.com/content/early/2012/04/03/amiajnl-2011-000751.full) have found that using patient-driven, adaptive technologies to guide clinical decision making are influencing the quality of patient care. How might these technologies minimize risk, promote health, and encourage patient engagement in their own care?
A data driven approach that proposed to utilize individualized confidence interval (CIs) to select the most appropriate model from a pool of candidates to assess the individual patient’s clinical condition. The approach was compared to other strategies like the BEST model, the ideal model, the can only achieved by access to data or knowledge of which population is most similar to individual, CROSS model, and RANDOM model selection.
The goal of the predictive models is to estimate outcomes in new patients, a critical challenge in research is to determine what evidence beyond validation is …
This solution discusses patient-driven, adaptive technologies in clinical decision making, and how this influences patient care.