- MACRA proposed rule published by HHS, streamlining federal programs including meaningful use
- CMS modernizes Medicaid managed care regulations, putting focus on improved health data exchange
- EPA chief Gina McCarthy: Public health is what we do
- ICD-10 check up: Are things really going as well as it seems?
- Health Data Exploration grants prove potential of personal health information
- Event Log Management & Compliance Best Practices: For Government & Healthcare Industry Sectors
- Case Study: Blood Systems Expands Remote Access Connectivity to Prepare for Disaster
- The Power of User Virtualization: Meeting Meaningful Use, Optimizing IT and Clinical Productivity
- New World Order: Effectively Securing Healthcare Data Through Secure Information Exchanges
- Beyond the EHR: Seamlessly Connecting Nurses and Physicians Using an EHR-Extender (EHR-e)
Ninety percent of the data in the world today has been created in the last two years and the healthcare industry is becoming a big contributor to this data deluge.
With so much data being created by payers, providers, and consumers, it is unsurprising that healthcare analytics is becoming the hottest topic in healthcare.
One of the most sizzling areas involves health plans trying to understand how their health population will look with the implementation of the Affordable Care Act and the health insurance marketplaces (HIX).
To be protected from adverse selection, payers must participate in the risk adjustment process. How they implement a risk adjustment strategy and the value of that solution is dependent on many things — data being one of the largest. The influx of information has enabled the analytic world to create more accurate algorithms to identify when “risk adjustable” disease codes are undocumented in the medical record, and hence not reimbursable; rules and associations in risk adjustment provide an opportunity to close gaps in documentation.
Perhaps the most intriguing development relates to non-traditional data, which supplement traditional information sources such as claims data and add precision when predicting which members in a plan have undocumented codes. For example: eye exams can detect systemic diseases such as hypertension, diabetes, and high cholesterol before a patient has visible symptoms.
By incorporating vision data into analytics, plans have been able to more precisely target members who would otherwise have had those conditions go undocumented.
Big data represents one of the greatest potentials in the history of healthcare. Just imagine what another two years will bring.
Infographic: HIX race begins with Big Data