Predictive analytics and data analysis are becoming more common in medical practices as a way to improve outcomes and predict risk.
A study conducted by Atlanta-based health IT company Jvion found that 15 percent of providers are using advanced predictive modeling in their practices. Of those, 92 percent are using the outputs to predict patient risk or illness, according to a news release.
Of the providers that said yes, 15 percent worked in academic medical centers and 85 percent worked in hospitals or multi-hospital systems. Most were in the 101- to 530-bed range. The illnesses and conditions most often targeted include readmissions, patient deterioration, sepsis and general patient health, according to the study.
The majority of those using advanced predictive analysis are using vendor solutions, but 18 percent are using "home-grown" systems. Of those who are not currently using predictive analytics, 96 percent said they would or were unsure if they would, according to the report.
Advanced predictive modeling solutions are gaining a foothold in the healthcare provider landscape," the report said. "This new landscape requires a different analytic approach that can identify at-risk patients before they get sick so that interventions can be applied and penalties avoided. The clinical focus of those respondents who are currently leveraging predictive solutions aligns with this movement and the overall shift within the healthcare industry."