The time has come …
Everyone talks about Big Data’s potential to transform healthcare. They understand it’s needed to achieve the Triple Aim: improving patient outcomes, lowering cost of care, and increasing patient engagement. Yet there are very few tangible examples of organizations realizing this potential. One reason is our industry is historically slow to adopt change, even when we know what change needs to happen.
It was Ben Franklin, back in 1791, who spearheaded the movement to establish hospitals. And here we are, more than 200 years later, just recently embracing the idea of going paperless. If it weren’t for Meaningful Use and other regulations driving the move toward digitization, you have to wonder if we’d be as far along as we are.
Fortunately, 85 percent of healthcare organizations now use EMRs, which makes accessibility of data possible throughout the continuum. Turning that data into actionable insight, however, requires technology. And technology investments are difficult to justify without a clear return on investment. I love a statement by Dr. Rick LeMoine, System Clincal Director at Sharp Healthcare, “To develop a predictive model, hospitals need a digital dividend from investments in these systems.” Advanced analytics presents a clear opportunity to deliver on that need.
Most hospitals already have several years of data. What they don’t realize is that their data is actually an asset that can be used to generate data models and benefit across clinical, operational, and revenue cycle processes. In addition, the right people, processes and technology, along with both short-term and long-term strategies are critical components of any effort to leverage data.
One mistake many organizations make is to think this is a technology discussion. You can have the best technology in the world, but without organizational alignment it won’t create a scalable shift to data-driven organization. The place to start is to look to other industries to see what types of teams they’ve put in place, what types of technology investments they’ve made, and what types of problems they’ve faced and overcome. The latter is one of the most important things to consider; if you aren’t focused on the right problem, you put your strategy – and your ROI – at risk.
Executives in other industries who are responsible for advanced analytics have a mix of short-term actionable projects and long-term Big Hairy Audacious Goals, or some blend of two, especially if it’s a new program. You have to weight short-term actionable items to build credibility to justify further investment. At the same time, you have to have a few “change the world” projects running with staged graduation. Then as the program matures, you can take on more, which enables you to grow the program in scope and size over time.
Most hospitals and health systems face the same constraints when it comes to execution on their strategy, the most obvious being resources. They just can’t afford to hire and train data scientists and other skilled technology professionals. Many will need to use vendors to lead the process. Operational and financial projects can be easier to push forward and don’t have the regulation around clinical workflow. This means progress can be made faster, which can help to justify further investment. As an example, practical predictive analytics applied to existing workflow can support billing teams in working smarter and not harder moving the needle on financial outcomes for hospitals. Companies like Connance, are doing this across the revenue cycle continuum, finding ways to make a difference today that has the added benefit of maintaining patient financial relationships.
Whether organizations realize it or not, making analytics a critical component of their go-forward strategy creates a significant competitive advantage. Look at purely digital industries such as Amazon and Google. They use data analytics across the full spectrum of their businesses to understand their buyers, and to engage them in a meaningful way. The result is improved customer engagement and increased efficiencies, both of which positively impact their bottom line.
While healthcare is coming from a different place, the need for advanced analytics is just as critical. Those organizations that do not embrace this fact or act on it will not survive against those that do. The winners will figure out how to use data analytics to improve efficiencies across their entire organization to be more thoughtful, more proactive, and more efficient with resources.