Just as many patient advocates and community groups are saying about their personal stored electronic medical records, so too are others very interested in studying the warehouses of information:
What kind of data and what type of analytics are in the offing?
Four types of data analytics that providers are using to improve population health
The push by the government to reduce healthcare costs and the increased liability providers have is forcing them to more easily identify and help chronic care patients to better manage their conditions.
Healthcare IT vendors are expanding their big data armories to help providers, particularly accountable care organizations mine claims and clinical data to get a better sense of patient outcomes, performance and how they can reduce costs
Dr. Anil Jain, the CMIO of Explorys, a spinout from the Cleveland Clinic, highlighted some of the different analytics approaches it is offering clients as they get more involved in population health.
Descriptive Analytics This accounts for the biggest chunk of big data across industries and it tends to focus on what went wrong or assessing why outcomes are more or less than what was expected. . In other words, what is happening now.
Predictive Analytics Big data is chiefly being used to identify patterns, predict how to predict future outcomes, and avoid preventable events as a way to reduce healthcare costs.
Prescriptive Analytics Prescriptive analytics involves helping a provider measure and manage a patient population. (Obesity, Diabetes, Hypertension.
Comparative Analytics One of the most interesting ways providers can use big data is to compare their performance to other healthcare facilities.
This big data analytics is only possible now at large institutional providers and integrated health systems, such as Kaiser, Cleveland Clinic, or the Mayo Clinic.
Data from small hospitals, providers and even University Medical Centers would be so disparate as to defy meaningful analysis.