HIMSS Analytics Predictions: Digital Innovation in 2018Published by csubelsky on Tue, 01/23/2018 - 11:09
As the market intelligence arm of HIMSS, HIMSS Analytics offers global healthcare IT data and insight, research, and standards, enabling clientele in both healthcare delivery and healthcare technology solutions business development to make lasting improvements in efficiency and performance.
HX360 recently spoke with Blain Newton, executive vice president, of HIMSS Analytics, about:
· how the organization collects data;
· whether he believes that predictive analytics will eventually lead to prescriptive analytics; and
· what he believes is the hottest health information and technology trend for 2018.
On What the Data is Saying…
We gather data on more than 370,000 hospitals, health systems and practices in 47 countries, on everything from technology inventories to usage information to financial and demographic information about hospitals. We collect this data for a variety of reasons, but the primary driver is to help our constituents – whether they be providers or supplier/vendor – understand where the market is going. Through our proprietary data set and our in-house predictive modeling engine, Logic Predict, HIMSS Analytics helps health leaders, within the HIMSS ecosystem and beyond, understand where they should be focusing moving forward.
We’ve identified, through our predictive modeling, for example, three dozen hospitals we are confident will invest in precision medicine within the next year. These systems will generally need to be of a certain size to maintain, advance and provide this level of sophistication which is one reason we’re seeing today’s era of mega acquisitions and consolidations, a trend we believe will continue because of the need to acquire critical mass to adopt and manage advanced analytics platforms and programs. We’re hopeful and, in fact, are seeing signs today that the knowledge gained by these large organizations eventually will be shared with smaller health systems so they too may implement these same best practices.
On Predictive Analytics and Prescriptive Analytics…
More and more organizations are turning to predictive analytics to better treat their patient base and proactively work within the geographic areas and demographics they serve to improve community and population health. As these initiatives become more commonplace we anticipate seeing growth in analysis of the data derived as a result of the efforts.
In the world of predictive modeling, where intelligence is best derived from repeating the process multiple times to gain granular insight, we likely will see the organizations using predictive analytics evolve to prescriptive analytics where they are using their granular predictive findings to direct changes in care before patients know there may be a problem.
NorthShore University HealthSystem, an organization at Stage 7 on the HIMSS Analytics EMRAM, has carefully calibrated its electronic medical records, provider workflows and clinical decision support tools to develop useful strategies for helping physicians better prescribe genetic tests for their patients.
This isn’t a capability that most EMRs offer out-of-the-box, though. "Fortunately, we have a very innovative IT department, and they've helped us maximize what [our EMR] can do and customize it to access genomic data as a discrete variable…," Peter Hulick, MD, director of the Center for Personalized Medicine at NorthShore University HealthSystem, recently told Healthcare IT News.
On Where Health IT is Headed…
A significant new area for advancement I see for the immediate future is in supply chain information management within health systems. While supply chain is often thought of as a procurement function, there is opportunity for advancement in the integration of clinical and supply information to create tracking and traceability at the point of care and throughout the treatment cycle.
This is particularly exciting because it will allow hospitals to track all the pieces and parts of, say, a total knee replacement through automated bar coding that transfers directly into clinical information systems. It will not only enable early fail detection in the case of recalls but will help normalize cost across health systems, and reduce waste and redundancies.
Precision medicine, personal connected health, and supply chain advancement are all interrelated at some level. They all require a certain level of sophistication, which goes back to that ability to leverage technology to improve care while also building and sustaining a culture that values strategic analytics.
I always counsel health IT leadership teams that technology, as promising as it is, is not a savior. Rather, it’s a combination of people, process and technology that will propel innovation forward. We must remember that.