Health data analytics is the third wave of health IT we’re undertaking, right after data capture and data sharing. Having excellent analytics capability will provide the return on investment for the massive amounts of spending happening in health IT in the past few years. Buzzwords, like “big data” and “analytics” are becoming commonplace., however this also takes away from their effectiveness. According to the Gartner Hype Cycle technology has five key phases in its lifecycle: Technology Trigger, Peak of Inflated Expectations, Trough of Disillusionment, Slop of Enlightenment, and Plateau of Productivity. Now that we have widespread adoption of EHRs, the superior use of analytics will be a dominant factor for success over the next four to five years.
Learn more about Brian Ahier
Guest contributor Brian Ahier is a nationally-known expert on health information technology with a focus on health data exchange. He serves as President of Advanced Health Information Exchange Resources, LLC, and sits on the Consumer Technology Workgroup of the HIT Standards Committee. Brian has served on numerous boards and committees and currently serves on the Boards of DirectTrust, HIMSS Oregon, Q-Life. More of Brian’s insights can be found on his blog, http://www.ahier.net/.
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The Sustainable Growth Rate (SGR) Repeal and Medicare Provider Payment Modernization Act of 2014, introduced to Congress on February 6, 2014, is a bipartisan attempt to address perceived failings of the current Medicare physician payment system, the so-called “Doc Fix.” Below, two industry experts provide commentary on the bill’s proposed changes and the implications for health systems and providers.
In this article, Brian Ahier – a Health Catalyst guest contributor and industry expert – predicts that 2014 will prove to be the year of healthcare data analytics. There will be a marked shift away from volume and toward value for both healthcare delivery and payments. ACOs and Patient-centered Medical Homes will flourish. 2014 will be a perfect storm of regulatory change, business drivers, and technology solutions. The ACA established the value-based purchasing program and it will be essential to leverage healthcare data effectively to drive value-based decision-making. Predictive analytics solutions can generate and evaluate hypotheses, and determine a confidence level for the hypotheses. But comparative analytics, predictive analytics, and NLP will not solve all of health care’s problems. A successful organization must have tools with the ability to score predicted outcomes to better guide the care team on the need to intervene, when and how to intervene, and a feedback loop to create a learning healthcare system.
Guest contributor, Brian Ahier, describes the transition from “meaningful use” to meaningful analytics and achieving high-quality care. Since meaningful use is requiring greater interoperability and data sharing, there is now much greater opportunity to aggregate data at a community level and have an even broader data set than just the EHR to mine for clinical intelligence. One benefit from HIE, besides improved care coordination, is the ability to perform queries and apply analytical tools to those data that were not previously available. The five health outcomes policy priorities included in meaningful use are:
1. Improve quality, safety, efficiency and reduce health disparities
2. Engage patients and families
3. Improve care coordination
4. Improve population and public health
5. Ensure adequate privacy and security protections for personal health information
Healthcare has been slowly moving through three waves of digitization and health data management: data collection, data sharing, and data analytics. Data collection and sharing waves have been having some success, spurred on by the HITECH Act and implementation of electronic health records and health information exchanges. They have not yet significantly impacted costs or quality in healthcare. The third wave of analytics is ready to crash on our shores and I believe we will actually begin to see an IT infrastructure that support the new payment and care delivery models which are emerging. Guest blogger Brian Ahier explains how healthcare can work to realize the value of their IT systems and the healthcare analytics adoption model.