Earlier this week, I attended a symposium on healthcare data analytics held by Health Data Management in Chicago. This was the fourth year of the convention and the first year that I attended. I have attended many healthcare conventions over the last 30 years, mostly related to financial transactions, data and topics related to revenue cycle management. This meeting was unique in that it related data to all types of healthcare management and showed how numbers could be used to predict the future as well as analyze the past.
Forward thinking organizations were already using analytics to do some pretty amazing things. One facility had developed tools to predict future readmission rates of their own patients, another had predictive analytics for projecting future short term emergency department demand so that they could staff for these fluctuations in advance. This tool used internal data collected by the healthcare organization and external data like traffic, weather and social media.
Vendors had tools that could not only model historical data and test hypotheses, but could measure and identify trends from data unseen by users. New algorithms used in other industries can be applied to healthcare data to allow computers to assist users to explore their own information. Think of when Netflix shows you “other films you may like” or when Amazon suggests similar products. This technology can be used in healthcare to suggest things you may be looking for, but may not have thought of yet.
Several concepts hit home for me. In particular, a speaker from Oracle discussed the value of data as an asset, like cash, equipment and people. His message was to think of data as capital. Most organizations have improved and automated data collection through new EMRs, automated claims processing and payment collection, modern ancillary systems for pharmacy, lab and radiology not only provide better data for providers and patients, but create the potential for major breakthroughs in managing patient care, reducing costs, and uncovering new business opportunities. In most organizations, this data is just sitting there, waiting to be used.
If we look in the news, we see recent examples of analytics in healthcare making an impact on the industry. Healthcare Informatics recently reported that CMS used their analytics system to identify and/or prevent $840 million in fraudulent payments over the last three years, $454 million in 2014 alone, a 10:1 return on the taxpayer’s investment.
Analytics can also be applied to treatment. Recently, analytics has raised concerns about Ibuprofen and the risk of heart attacks and the recommended criteria for mammograms. As we begin to alter our systems to support outcome based payments, we will improve our ability to accurately record and measure outcomes, improving the data we currently collect. This will allow for improved predictive analytics that will provide new insight into what we do, if it actually works and suggest other courses of action. Combined with the financial data, we will be able to make more intelligent decisions of the cost/benefit of different treatment plans, medical devices, and strategies.
The organizations that can apply these tools to their existing data capital will have a major advantage over their competition. Unlike basic statistics, analytics can be useful with small data samples with limited scope. They can provide data you can act on immediately that will improve as you collect more information.
In the movie Moneyball, we saw how the Oakland A’s used analytics on historical data to find value in players considered ordinary in other organizations. Now, we see predictive analytics used by almost every baseball organization to shift the position of fielders for every hitter that comes to the plate based on a computer analysis of where they tend to hit the ball.
My background is not that of a healthcare provider, but as a businessman. Although the potential of this new opportunity to improve healthcare organizations from a clinical standpoint is tremendous, the potential for new products and services is what interests me. During this convention, another recurring theme was the lack of talent available in this field. Based on my observations from this meeting, the people who tend to excel in analytics are not necessarily IT gurus or accountants, but people with imagination and the ability to communicate between these groups and management.
Speakers from CMS and large healthcare organizations that had built departments dedicated to this effort all discussed their difficulties in selecting members of these teams that delivered the talents they needed. For those of you out there that that like to work with data and can see what it tells you with an open mind, there has never been a greater opportunity for well compensated employment or developing a new business.
All of this good news comes tempered with a personal warning. Just like in Moneyball, the conventional process used to analyze healthcare and make decisions on its delivery will resist this new process to trust data over educated intuition. It took nearly twenty years until baseball analytics was used in every organization, in each one, it was impeded by the established class of baseball scouts and other professionals that believed that the value of their intuition superseded the ability of analytics to predict outcomes.
In healthcare, analytics will be limited by the status quo as well. In many cases, the data will suggest courses of action that fly in the face of existing practices and even common sense. Organizations that can take a leap of faith and act on this information will thrive. Those that resist will fall behind. Most of all, analytics must be used to alter how patients are treated. This is a concept heavily resisted by many healthcare providers who consider this to be an effort to limit their ability to practice medicine as they see fit. As long as personal intuition and preferences outweigh new evidence relating to treatment and outcomes, the true benefit of this new opportunity will be limited. From what we have seen with the resistance to change particular to the healthcare industry in our transition to new computer systems, and even code sets, this will be a large hurdle to overcome.
By Kalon Mitchell, President – MEDTranDirect