As a clinician, health IT
architect and computational model-builder, I’ve been focused for
the past three decades on how to use health IT to transform data into information and information into knowledge, in a way that improve care value. I’ve come to
realize that highly effective and efficient care delivery (including prevention, assessment
of risk, and the diagnosis oand treatment of health problems) depends on useful, valid clinical
knowledge providing evidence-based decision support.
In any case, gaining this crucial knowledge depends on creating, continually evolving and disseminating useful, actionable, valid information and presenting it in a way that avoids overloading the clinician and patient.
And generating such valuable information requires adequate amounts and diversities of valid and reliable data. Some of these requisite data can come from today’s "Big Data" stores, which are typically insurance claims (administrative) data. While such claims data have usefulness, they are grossly inadequate when it comes to creating the kinds of information and emerging the kinds of clinical knowledge necessary to improve care quality and cost in any truly meaningful way.