Semantic Computing, Predictive Analytics Need Reliable Metadata
Our Healthcare Partners at Montefiore were interviewed at Health Analytics:
Reliable metadata is the key to leveraging semantic computing and predictive analytics for healthcare applications, such as population health management and crisis care.
As the healthcare industry reaches the saturation point of electronic health record adoption, and slowly moves past the pain of the implementation process, it may seem like the right time to stop thinking so much about hammering home basic data governance principles for staff members and start looking at the next phase of health IT implementation: the big data analytics environment.
After all, most providers are now sitting on an enormous nest egg of patient data, which may be just clean, complete, and standardized enough to start experimenting with population health management, operational analytics, or even a bit of predictive risk stratification.Many healthcare organizations are experimenting with these advanced analytics projects in an effort to prepare themselves for the financial storm that is approaching with the advent of value-based care.
The immense pressure to cut costs, meet quality benchmarks, shoulder financial risk, and improve patient outcomes is causing no small degree of anxiety for providers, who are racing to batten down the hatches before the typhoon overtakes them.
While it may be tempting to jump into quick-win analytics that use “good enough” datasets to solve a specific pressing use case, providers may be at risk of repeating the same mistakes they made with slapdash EHR implementations: creating data siloes, orphaned reports, and poor quality datasets that cannot be used in a reliable, repeatable way for meaningful quality improvements.
Read the full article at Health Analytics