As an organization participating in the federal Pioneer accountable care organization (ACO) program, Allina Health, based in Minneapolis, has a natural incentive to improve clinical performance. Even so, the decision on the part of senior leaders at the 13-hospital, 90-clinic, 26,000-employee Allina to commit to achieving exceptional outcomes—senior executives strove to be in the top decile of performance on every meaningful, measurable quality metric—was ambitious enough to give the project a semifinalist award in this year’s Healthcare Informatics Innovator Awards program.
In population health, where no one single metric exists, the organization would demonstrate that it could measurably improve a health index measure. Further, in terms of affordability, the organization would be at or close to mid-market cost for the patients it serves, according to Allina Health officials. Indeed, Allina Health set out to make this commitment by 2016. To move in that direction, Allina adopted a multi-pronged strategy that encompassed new payment models and contracts, care redesign, and technology and analytics.
Specifically, Allina team members aggregated clinical, financial, operational, patient satisfaction, and other data into its enterprise-wide data warehouse (EDW), to create consistent views of the data. They then decided to use analytics to identify the clinical programs in greatest need of optimization and waste reduction, focusing initially on congestive heart failure (CHF) readmissions, spine care, length of stay, and venous thromboembolism (VTE) care. They chose to drill down particularly intensively on reducing CHF-related 30-day readmissions.
The leaders who created that EDW are the founding members of Salt Lake City, Utah-based data warehousing and analytics vendor Health Catalyst, a company that “aggregated a lot of information from a lot of different sources, allowing for data to be pulled out of Epic and put it in place so our leaders could use it clinically and drive improvement,” says Tim Sielaff, M.D., Ph.D., chief medical officer of Allina Health. “We have been doing this for a long time. Our organization is organized around clinical service lines such as oncology, cardiology, and orthopedics, so care processes and improvements of care processes driven by data is baked into our genes,” Sielaff says.
Tim Sielaff, M.D., Ph.D.
When Health Catalyst the company was formed and the data warehouse that Allina was running independently became bigger and more complicated, the cultural fit to connect the organizations was obvious, Sielaff notes. “It was a way of helping to exponentially accurate the function of our data resources within the organization,” he says. Simply put, Sielaff says the goal is for Allina to serve as a resource for the rest of the community and country. “As we learn how to do things well, such as develop dashboards and improvement projects, we have a vehicle to share those with society now,” he says. “The ability for us to use data to do improvement was something we have been doing, and the collaboration with Health Catalyst has made it better by that much, made it that much more rapid cycle, and that much more rigorous based on what we might have been able to do on our own.”
Sielaff notes that data by itself is not very useful; the goal, he says, is to turn data into information and information into knowledge, and from there enact improvements. “Our organization is designed around care process improvement, and that is always driven by data that is in the hands of people close to the work—clinicians in an OR, catheterization lab, or clinic, they have that information and knowledge available to them to help create improvement,” he says.
The way Allina does improvement originates oftentimes out of identifying variation in care, Sielaff continues. “Where there is variation that is not warranted by the needs and preferences of the people we serve—our patients—that’s where we start working on improvement. Any organization that starts looking at variation within any part of an organization, will find it. The ability of putting that data into the hands of clinicians so they can determine if it’s warranted, relative to our patients or not, and then take that from there, that’s the sauce. Trust and transparency are the two key tactics that allow us to enact improvement.”
Sielaff offers examples of finding variations in care and then driving improvement. It can be anything from the timeliness between having an abnormal diagnostic mammogram and a biopsy to bleeding rates post-percutaneous coronary intervention to the cost and value of delivering a spinal fusion operation, he explains. “There are literally hundreds of examples of using data to drive improvement, which is almost always less expensive. Better care is linked to less expensive care, and that is value. The value equation is outcomes divided by cost, and I say [multiplied by] appropriateness. And value doesn’t mean cheap,” he says.
Taking it to the Next Level