Predictive analytics is an emerging healthcare technology where analytic models predict future trends based upon retrospective or real-time data.
How will patients have the potential benefit of better outcomes due to predictive analytics?
Do you envision predictive analytics taking on an even larger role in patient outcomes in the future?
How would predictive analytics be beneficial in your profession?
Explain two ethical issues relative to predictive analysis in public health.
An innovative strategy for enhancing patient outcomes is predictive analytics. Machine learning algorithms may be trained to offer insight into the kind of treatments that will work best for the present patients by considering the data and outcomes of previous patients (Van Calster et al., 2019). Predictive analytics may also be used to spot warning indications before they became serious (Mehta & Pandit, 2018). As the COVID-19 epidemic dominates healthcare, researchers are investing time and money in creating predictive analytic strategies to fight the virus. The COVID-19 virus has presented a special challenge to the healthcare system since the infection’s intensity might differ from person to person (Mehta & Pandit, 2018).In a new study published in JAMA, researchers used machine learning algorithms and predictive modeling to identify risk variables linked to severe COVID-19 cases (Van Calster et al., 2019). The severity of COVID-19 can be estimated using predictive analytic techniques that vary from person to person. Researchers from the American Chemical Society have just created a blood test that predicts whether or not a person may have severe COVID-19 symptoms using predictive analytics. Providers can identify patients who may be at high risk for developing certain chronic illnesses including cancer, cardiovascular disease, obesity, and renal disease by using predictive analytics. Cont
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