Improving Healthcare Delivery through Clinical Predictive Analysis
Healthcare delivery methods are seeing major improvement in the current times. As the current scientific discoveries and inventions are highly efficient and improved; so are the ways of delivering healthcare.
Community Health Solutions, in earlier days was very difficult to analyze on grounds of the types of care delivery and expectations. The combined usage of artificial intelligence and historic and current clinical data analysis has proven to be helpful in the following ways:
· Easily targets individuals which are prone to high risk of certain illness· Facilitates better allocation of existing resources
· Reduce financial loss
· Reduced patient suffering
· Helps reduce unnecessary ER visits
Clinical Predictive Analytics uses a combination of technology and statistics in order to facilitate a thorough search of historic and present clinical data of patients yielding predictions for them as a result. Artificial intelligence as a technology incorporated with predictions has the ability to revolutionize the medical field. Healthcare is benefited by such analytics in the following way:
· Complex predictive algorithms promote accuracy in diagnoses
· It facilitates an early intervention, which helps in prevention of various diseases at an early stage reducing patients at suffering.
· It provides physicians with accurate and detailed prediction data helping them with patient-level care delivery.
· Helps reduce stress on resources by distributing existing resources where and when they are needed.
Using Jvion’s RevEgis clinical predictive analytics, providers can intervene to stop patient suffering, reduce readmissions, reduce length of stays, and stop the loss of hospital resources and finances while promoting patient-centered medicine.