Descriptive Analytics:
What has happened?
To create comparisons, find trends, or draw new conclusions, descriptive analytics uses previously collected clinical data. Experts use the summary of previous events to guide their decision making for the future. By tracking the frequency of positive tests in a given area over time, these insights may make it possible to estimate the virus infection rate.
Diagnostic analytics:
Why something happened?
The analysis identifies the connection between a past event and a specific outcome. Physicians use this analysis to determine an injury or sickness based on the symptoms. It is usually a follow-up of a descriptive analysis.
Predictive Analytics: What will happen?
Based on historical and current data, predictive analytics can predict patient outcomes. Organizations use the insights from these analytics to identify opportunities, prepare for future demand, and develop services. Healthcare professionals use the data to deliver better outcomes and care for patients.
Prescriptive Analytics: How can something be achieved?
With the help of AI, prescriptive analytics supports clinicians in handling human bias and reducing human error. The advantage of these tools is the support for identifying pre-existing conditions in people and suggesting possible therapies. Healthcare providers use prescriptive and predictive analytics cumulatively to make well-informed decisions using data and statistical models.