Traditional analytics in healthcare have long been carried out through separate online and analytical transaction processing systems using siloed data held hostage within healthcare provider organizations. This approach requires an inordinate amount of care and maintenance to keep these two systems in sync—and despite the time and energy invested, still result in operational inefficiencies, a lack of actionable insights, and a reactive way of managing the business of healthcare. Under volume-based reimbursement, care providers are paid for any service delivered. With no official accountability for outcomes or costs, there has been no real incentive for change, until now.
The Accountable Care Act is the biggest catalyst for transformation starting with digitizing health records and moving towards value-based payment and patient-centered care delivery models. Under value-based reimbursement, providers must act more like a business and have a complete picture of costs associated with patient level services. Understanding patient value measured in terms of costs, outcomes and satisfaction as well as practice variations and optimization around good business will be mission critical to survive in this new world order. Today’s Healthcare Executives must have immediate access to integrated patient-level cost and care delivery data to effectively manage care at both point of care and for the entire enterprise.
“Fixed and variable costs have to be integrated with care services in a meaningful way, ” said Walt Ellenberger, Senior Director, Business Development and Strategic Alliances at SAP Healthcare, “so you understand whether you’re hitting the mark or not, from a financial margin, risk management, and patient care perspective.”
Ellenberger pointed to Mercy as a great example of leveraging advanced analytics to better understand and manage enterprise performance under the new rules of engagement for value-based healthcare. Mercy is one of the top five large U.S. health systems, which serves millions annually through 40-plus acute care and specialty hospitals and more than 800 physician practices and outpatient facilities. Having the tools to dynamically identify practice variations and root cause in order to have factual based discussions with clinicians to align on best practices can have a significant impact, even for small changes in practice. For example, Mercy was assessing cost variations for knee replacements and noticed a blip associated with certain orthopedic surgeons. When they did a root-cause analysis they found these clinicians were using a larger bowl to mix cement for knee operations. When they asked the surgeons if there was specific reason they were using this sized bowl, their response was, no. In fact, they always questioned it because with a larger bowl they had to open two bags of cement to fill the bowl and threw half of the second bag away as excess. A change in bowl size on the enterprise scale of Mercy has led to a cost reduction.
A simple insight with a big impact—now, consider how many of these fundamental, easily remedied situations exist across a provider system and the potential impact on the bottom line.
Moving to a Patient-Centric World
Value-based reimbursement shift isn’t the only sea change. Another, Ellenberger pointed out, is the move from a provider-centric world to a patient-centric world. “It’s a hidden message that the industry must be more consumer savvy, where you’re not just treating a patient when they are sick but being a lot more proactive in preventing illness rather than treating illness. The reimbursement and care model shift are forcing the healthcare industry to be more proactive and more holistic, which across the board is going to be a good thing for any of us who are consumers of healthcare.”
In short, silos need to be broken and data needs to be unified throughout the system from various sources to facilitate holistic care, better manage costs, and reduce waste. The good news is, this technology does exist. Today’s Enterprise Advanced Analytics can sit above the tree line of a multitude of discrete systems to aggregate and unify disconnected data about patient care variable and fixed costs and outcomes, for analysis, insight, and decision making.
This next generation analytics adventure is in its infancy phase the clinical practitioners are still reeling from the move to mandated EHRs that require extensive electronic data input. Gone are the days when care delivery was more art than science and everything was recorded on paper. The pendulum shifted perhaps too far in the early days and not enough attention was paid to how that affected clinician behavior and productivity. Ellenberger acknowledged this process is an evolution and the next phase is to go back and figure out how to alleviate the burden placed on the front line—perhaps through AI and natural language processing—to allow clinicians to be more patient-centric.
“I call it the digitization hangover,” he said. “Now we have to reset the delivery mechanism again to address this new problem: How do we transition digitization that was more billing oriented to be clinical focused on improving productive and patient air time. The foundation is there to figure it out.”
Unlocking the Value of Data
And, most agree, it will be worth it. Not only in the context of patient-centric care, but related medication adherence and compliance. Tapping into meaningful data will help clinicians and larger systems achieve higher quality results on a broader scale. It has the potential to standardize care and enhance medical research by integrating large data sets and, having enterprise-wide data will help administrators improve productivity capacity planning as well as revenue cycle management. Providence St. Joseph Health, for example, has used insights to achieve a 25 percent reduction in approximately 800 documents that were previously required to report on the revenue cycle and was able to do a root-cause analysis for reimbursement denials.
Maximizing data also includes the potential for new revenue streams in a health care environment with paper-thin margins. Device and drug companies are eager to access and pay for that anonymous, real-world data and those who curate it are realizing they have an invaluable asset that provides the last mile of insight.
“We have to acknowledge that this whole process is evolutionary versus revolutionary,” Ellenberger noted. “But having enterprise-wide data through today’s Advanced Analytics Systems is the foundation for being more proactive, with more points of care, and the ability to be more predictive in managing care delivery. The need for this intelligent platform that can pull information together in a simple and often virtual way is filling a huge void and the shift in reimbursement is creating this demand.”