5 reasons to get sold on analytics
Welcome to the data world. Many secrets are hidden in big data, and now, with the computing power to unearth them, analytics promises to deliver transformative power wherever it is put to work. Still, the technology is a relative newcomer in the healthcare world. Brett Furst, CEO of Arbormetrix, says there is nothing to fear – and that analysis of clinical data has much to offer the medical world. Here, he shares his top five requirements to succeed with, or at least get excited about, the power of clinical analytics.
1. Know the difference between solutions. Analytics solutions vary widely in size and shape. Furst says it is important to know what the different kinds are, and how to apply each one to specific problems, whether they have to do with population health and disease management, episodic delivery or post-acute care. Population health and disease management focuses on "improving the general health of a population and keeping them out of a hospital," according to Furst. Think screening a database to find people who might be at risk for a certain condition and reaching out to them. Episodic analytics "focuses on identifying variation in the delivery and associated outcomes of specialty and acute care." This kind of analytics is about looking back and finding ways to improve care in the future based on how it was provided previously, says Furst. Post-acute analytics centers around "utilization management so patients receive the appropriate level of care after hospitalization, with a focus on cutting down on wasted resources." Essentially, the three flavors Furst outlines could be seen as the analytical equivalents of before, during and after.
2. What's in the data? Knowing which analytics can be applied to which problems opens the door to immense functionality. With the rise of ACOs and the paradigm shift of reimbursement for quality of care, healthcare providers are scrambling to approach the health of their populations proactively. Clinical analytics has a role in this shift, and Furst says harnessing its power means that organizations will be able to more intelligently identify, solve, and manage the challenges that they are beginning to face. Furst says being able to ask questions such as, "Where the spending is, how many readmits do we have every year, and how do outcomes stack up against variances of treatment?" have a massive "effect on clinical performance [that] goes to the actual outcome of the patient." By taking the data generated in a hospital and making sense of it with clinical analytics, Furst says there is a real ability to find and tackle performance issues. "When you combine good clinical data with good accounting data, you can pinpoint what types of conditions might make for readmits," he says.
3. Make data actionable. Furst says there's a common malaise in the industry around the promises analytics and big data seem to offer. He is careful to caution that "just aggregating your data isn't going to lead to big benefits," and that "data is just going to be a reference point." The important thing to remember, he says, is that clinical analytics is a tool first and foremost, and that without knowing which problems need to be solved, their use is limited. Furst says the ideal way to look at it is as if a hospital were like any other type of business: trying to do a top-to-bottom complete overhaul is a tough pill to swallow, and one that may not end up being that effective. Instead, he recommends taking the approach of "Let's start zeroing in on one area, and use the data to find where to start." Furst says the best results will come from focusing on a specific area to approach, with clearly defined goals and steps to take. "I see the real opportunity ... when you apply a higher level of algorithms to make the data more actionable," he says.
4. Understand the additional benefits. Who says clinical analytics is a one trick pony? By its very nature, analytics is the practice of taking a close look at a large amount of data and then driving outcomes with its findings. Furst says this can be put to a variety of uses in the healthcare world. When the lens is turned in an analytical fashion to the ways doctors work, the results can drive and change the development of best practices. Furst says that in the old fee-for-service world, "surgeons would do what they thought was medically appropriate, but they did so in a vacuum." Now, "when you come to them saying this device is $15,000 and this one is $2,000. And guess what, the $2,000 one is actually better, you're improving care and impacting your bottom line."
5. Provide evidence based on the demographics of the patient. As well as being a powerful tool to drive changes in the operating theatre and the board room, clinical analytics has a role in communicating with the patient. Furst says a clinician should be able to sit down with his or her patient and be able to pull up treatment outcomes that match that patient's demographics as a way of saying "based on evidence the better procedure is A instead of B." Compared to already existing tools such as WebMD, which Furst feels contain "a deluge of information," that may not necessarily be relevant to the person reading it, clinical analytics has the ability to filter what's unimportant and to provide better information. Furst says the analytics enables practitioners to say, "Our statistical science shows this treatment option will deliver the best probable outcome for you."