We have been told that data leads to information, and information leads to knowledge. It is this knowledge, then, that drives innovation – the engine powering transformation in healthcare. While the luster of innovation is what grabs our attention, data and analytics are what make it possible in the first place.
What Used to Be
According to the archives of healthcare planning, future bed need was once based on the “Roemer Effect.” Named for Milton Roemer, a noted professor who first noticed this phenomenon, it refers to an industry’s ability to create its own demand. In other words, “build it and they will come.”
Now, this tactic has long since been dispelled, as government has taken a more utilitarian approach to healthcare regulation and as consumers demand greater transparency. Under a utility approach, the goal is no longer “heads in beds.” Even CMS is moving away from cost-based pricing focused on the hospital experience and instead beginning to set the price they are willing to pay for healthcare services (e.g., bundled payments) – what I refer to as price-based costing. Significant hospital closures and conversions (often to ambulatory) during the past 5 to 10 years speak clearly to a different way of using hospitals than was possible before. Better understanding the data related to the utilization of health services has allowed us to use hospitals in a different manner, and we are now able to do so much more clinically outside of the hospital.
Jeff Goldsmith forecasted this change in utilization in his 1980 book, Can Hospitals Survive? Looking back at his own predictions, Goldsmith noted that in the 30 years since his book was published, U.S. hospital inpatient census fell more than 30%, despite there being 90 million more Americans. During this same time, ambulatory service volume more than tripled, far offsetting inpatient volume losses. Additionally, the hospital industry’s total revenues grew almost tenfold. And I would argue that much of this growth occurred opportunistically, with little real capacity planning (especially on the ambulatory side).
Community-based ambulatory care is the new core of healthcare delivery, and this requires analyzing and understanding different population indicators than those used previously for bed need assessments.
The New Math
Population health management is a true paradigm shift. Like most significant shifts, it takes time for change to gain traction. But, in the end, it can replace and improve upon the previous mind-set. With the realization that 1% of patients account for 23% of care expense, and 5% account for an estimated 50%,1 a new calculus is required to address the country’s health needs. Effectively and efficiently managing the health of the population demands a more robust understanding of healthcare analytics. And like calculus for many of us when we were in college, it initially can be hard to wrap your arms around. However, the perceived complexity of this approach does not mitigate its necessity. This new math is not lost on savvy healthcare leaders. Even graduate schools (including my alma mater, George Washington University) are adding an M.S. degree in healthcare analytics to their menu of specialty programs.
Data Should Tell a Story
Analytics is allowing us to connect the dots between data points, revealing a detailed story that tells leaders what is going on within and beyond their organizations. Analytics provides the information health systems and consultants need to develop knowledge, and this knowledge dictates the strategic directions organizations should pursue. As a result, healthcare is getting much more sophisticated. What was once a comparison of broad trends has now become a granular comparison among population segments. Analytics provides us with far more insightful information that is truly creating new knowledge of how best to approach service needs and resource consumption, especially among higher-risk patients.
Data Becomes Strategic When…
This new era of analytics allows for far greater innovation and strategic insights across the healthcare industry than was possible before. Yet as I have seen time and again, many planning processes start out merely reinforcing anecdotal information or what is commonly referred to as “conventional wisdom.” Too often we cling to our views of the world, often despite overwhelming evidence to the contrary.
In today’s healthcare environment, it is not enough to simply plan for hospital beds. Episodes of care likely involve the Internet, a phone call or two, visits to a doctor’s office, some ancillary testing, a hospital stay, and perhaps post-acute follow-up. This fragmented system has been roundly criticized for its lack of coordination and inability to provide patients with the care they need when and where they need it. With data and new analytics, we now have the opportunity to better understand the needs of patients and operate in ways that are more appropriate for managing the health of the population. Advancing this new knowledge to improve the patient experience, provide greater access to care, and reduce costs cannot happen quickly enough.
National Institute for Health Care Management (NIHCM) analysis of data from 2012 Medical Expenditure Panel Survey.