The authors of the assigned article, “A Patient-Driven Adaptive Prediction Technique to Improve Personalized Risk Estimation for Clinical Decision Support (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3392846/) 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?

Solution:

Patient-driven, adaptive technologies are increasingly influencing the minimization of risks to patients, promoting health and supporting patient engagements. Patient and data-driven adaptive prediction technique provides the capacity to assess and prevent risks to patients without incorporation of external knowledge (Collins et al., 2017). Its applicability relies on its propensity to produce narrow individualized confidence intervals. Through the personalized risk estimation and prediction, the clinical decision support is improved for prevention of possible risks to patients. Engaging patients entails leveraging technology to attain optimal patient involvement in healthcare. According to Cronin et al. (2018), technology facilitates patient-provider communication, promotes shared decision-making as well as patient accountability for self-management. For instance, patient portals augment patient engagement by providing patient-provider communication. Further, medication apps provide a platform for patients to record…..Please click the Paypal icon below to purchase full solution for only $5