Meaningful Use, Secondary Use and Big Data

February 27, 2012
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EXCLUSIVE POST – At HIMSS 2012 in Las Vegas, everyone was anticipating the announcement on Stage 2 of Meaningful use from the Center for Medicare and Medicaid (CMS).  The announcement laid out the details of the next phase of Meaningful Use of EHRs in the coming years.

EXCLUSIVE POST – At HIMSS 2012 in Las Vegas, everyone was anticipating the announcement on Stage 2 of Meaningful use from the Center for Medicare and Medicaid (CMS).  The announcement laid out the details of the next phase of Meaningful Use of EHRs in the coming years. “Just as in Stage 1, CMS proposes that Eligible Providers, eligible hospitals, and Critical Access Hospitals be required to report on specified clinical quality measures (CQMs) in order to qualify for incentive payments under the Medicare and Medicaid EHR Incentive Programs.” Specifically, there are more details on reporting quality measures. Eligible providers will find that the new standards require aligning measures with the Physician Quality Reporting System (PQRS).  The quality reporting will also align with National Council for Quality Assurance (NCQA) for medical home accreditation.  Hospital reporting will align with Joint Commission’s hospital quality measures among others which should in some ways simplify reporting. Hospitals are inundated with reporting requirements from a variety of regulatory organizations so utilizing existing reporting for Meaningful Use in some ways simplifies their task. A preconference workshop on Meaningful Use and several sessions during the conference demonstrates this as a key them of HIMSS 2012.

But secondary use of EHR data is not limited to Meaningful Use. In a preconference workshop, the whole day explored secondary use, everything from interpreting to securing data for studying quality and research. The day began with a presentation by Charles Friedman of the University of Michigan discussing “Toward a Learning Healthcare System: Following the Data into a New Future for Healthcare.” This moves us beyond Meaningful Use to the broader us of EHR data to changing healthcare. The Learning Healthcare system is a concept developed in a white paper by the Institute of Medicine in 2007 which is now coming to fruition. The concept is a system “in which progress in science, informatics, and care culture align to generate new knowledge as an ongoing, natural by-product of the care experience, and seamlessly refine and deliver the best practices for continuous improvement in health and healthcare.” With a growing number of hospitals and providers on track with EHRs, we can now envision a healthcare system like this. It is being led by centers of excellence, first adopters who have figured out how to exploit this data to develop a cycle of continuous improvement. Institutions like Kaiser Permanente, Mayo Clinic, the VA, HMO Research Network and others. Also, several organizations are moving the change toward this nation-wide system including the Institute of Medicine, ASCO, FasterCures, CDISC and in Europe EHR4CR. Key to this transformation is a Digital Infrastructure as described another IOM report. This report states that “progress in computational science, information technology, and health research methods have made it possible to foresee the emergence of a learning health system which enables both the seamless and efficient delivery of best care practices and the real-time generation and application of new knowledge.” I would say that we are now beginning to realize this system with best practices becoming integrated into care, if not in real time, within short time spans, implemented into clinical decision support within mature EHRs. What will be required is Ultra-Large-Scale Systems with a “just right” level of standardization for openness to innovation.

This large scale is now described as Big Data. There was plenty of attention on Big Data at HIMSS 2012, led by IBM Watson which was demonstrated not only on the exhibit floor but also in several sessions including the innovative HIT X.0 session. Watson seems poised to use natural language processing to take medical case studies bounce them off of knowledge sources like PubMed and present diagnostic and treatment options. This is no game anymore; Watson is ready to take on clinical decision support in real time at the point of care. Others are prepared to be part of the learning healthcare system including Nuance which is moving beyond just speech to text but to clinical improvement. See more detail about Dragon Medical 360 | QualityAnalytics. Oracle demonstrated several technologies around big data including their significant investments in translational informatics – the real challenge of managing genomics data, the really big data problem.

In future years we will see more about how others are moving beyond Meaningful Use to secondary use enabling the real time use of Big Data.