In this interview, Andrew Cousin, MBA, FACHE, senior director of strategic planning for Mayo Clinic Laboratories, discusses how his organization uses EHR and claim data to identify opportunities to reduce unnecessary utilization and the total cost of care.
On preparing for value-based care. In 2015, leaders at Mayo Clinic Laboratories recognized that combating unnecessary utilization was essential to thriving under value-based care. Specifically, they wanted to reduce orders for tests that were not appropriate for patients’ conditions or did not add value to patient care plans.
Leaders recognized that clinicians often struggle to keep up with the latest in laboratory medicine, given that the lab adds 150 new tests to its menu of 3,000 tests each year. And because treatment guidelines are continually evolving, “no practitioner could possibly be expected to keep abreast of all the dynamic changes on our menu and in our best practices,” Cousin says.
To remedy this problem, leaders set out to collect data on clinicians’ ordering patterns and identify strategies to reduce inappropriate utilization, such as changing default order sets.
On investing in analytics. To begin the project, leaders tapped into Mayo Clinic Laboratories’ in-house analytics experts and data tools. “Our team has made investments in process engineers and business analysts who can really look at data from different points of view,” he says.
Because Mayo Clinic Laboratories is a global reference laboratory that provides testing and pathology services to 4,000 healthcare organizations, leaders could use their analytics tools to compare Mayo Clinic’s ordering volumes by specialty against median ordering points at their peer institutions. From there, they could identify outliers.
“When we saw an outlier that didn’t fit with the macro patterns, we tried to understand why and what was driving that difference,” Cousin says. “We wanted to understand if clinicians’ [ordering habits] were clinically appropriate and clinically additive. If the answer was no, that gave us a place to dig into and effect change in that particular area of practice.”
To understand differences in ordering patterns, analysts also looked at specific categories of practitioners. Were residents over-ordering compared with more senior practitioners? Or vice versa?
On reducing inappropriate genetic testing. To identify potential cost-savings opportunities from the data, Mayo Clinic Laboratories used their multidisciplinary clinical teams called disease-oriented groups, which include surgeons, pathologists, pharmacists, genetic counselors and other clinicians. The groups, which receive support from a financial analyst, discuss the appropriate application of laboratory testing, pathology and genetic testing to manage various conditions, Cousin says.
In one example, a disease-oriented group examined clinician ordering of Factor V Leiden mutation analysis, a type of genetic test that detects an inherited blood clotting disorder. After reviewing the claims data, they estimated that 81% of testing was unnecessary — many clinicians ordered it before ordering a less costly enzyme test called activated protein C resistance (APCR) screening that can detect a patient’s risk for developing a blood clot. The disease-oriented group reviewed the latest research and determined that the more costly genetic test should only be used when the patient has a family history, or the answers cannot be ascertained through an APCR test.
“The over-ordering of genetic tests was driving unnecessary costs for those clinical episodes,” Cousin says. “That change alone would result in an estimated savings of almost $317,000 per year for that patient population.” That translated to $0.01 cent saved per member per month.
On promoting genotype testing to decrease the total cost of care. Leaders also wanted to examine the claims and EHR data to determine how they could use appropriate laboratory testing to reduce adverse drug events and decrease the total cost of care. Specifically, they examined what would happen if they promoted a specific type of pharmacogenomic test (CYP2C19) for patients requiring a percutaneous coronary intervention (PCI). This test would help ensure that clinicians used the right blood thinner based on patients’ genotypes.
After conducting their analysis, they realized that making this test the standard of care for PCI patients could prevent costly adverse drug events, saving an estimated $1.7 million per year, or approximately $0.04 cents per member, per month.
This example demonstrates the importance of how laboratory testing affects the entire episode of care. “As we’re looking at utilization, we need to make sure we do not manage our balance sheet in a silo,” Cousin says. “Some of the savings that we are driving are not creating savings in the laboratory. In some cases, we are increasing laboratory costs, but we are doing so in a way that decreases the total cost of care by reducing length of stay, pharmaceutical spend or readmissions. So we have to measure the cause and effect longitudinally of what laboratory medicine is doing to an episode of care.”
On using clinical decision support. After reviewing these two genetic testing hypotheses, leaders at Mayo Clinic programmed new rules into their clinical decision support platform, which now displays “smart alerts” in the EHR to promote appropriate test ordering by physicians at the time of order entry. The alerts let clinicians know when they are ordering an inappropriate test, such as with Factor V mutation testing for certain patients. Or an alert may suggest pharmacogenomics testing when a specific blood thinner is ordered for PCI patients.
Leaders also are using their analytics tools to monitor clinicians’ current ordering behaviors. This continuous review process is critical to sustaining behavior change and realizing cost savings, Cousin says.
On what operational and finance leaders can do. In many cases, default order sets in the EHR are to blame for over-ordering of tests, Cousin says. Operational leaders can support clinicians and promote more appropriate ordering by working with IT and service line leaders to change order sets.
Finance leaders also can help support service line leaders looking to change clinicians’ ordering behavior by helping them understand the latest coding rules affecting laboratory tests, Cousin says.
On understanding laboratory costs. Cousin recognizes that laboratory medicine can be a difficult area for finance leaders to understand, in part because of the complexity of today’s emerging genetic tests. However, “there are tremendous opportunities at the enterprise level to think about how the laboratory can be a financial catalyst to your organization and drive savings not just in your own shop but also across different areas of practice, such as inpatient care, pharmacy, readmissions and length of stay,” he says. “We are proving in our own practice that cost increases in the lab can be offset by greater savings elsewhere along that episode of care.”
Cousin urges finance leaders to recognize that two factors can drive up laboratory costs: the cost per test and the number of tests ordered. “There is a tremendous amount of rigor at the private and public level to drive down the cost per unit,” he says. “The other opportunity for big savings is to drive down the number of unnecessary units ordered.”
Cousin says providers and insurers need to work together to address inappropriate utilization of laboratory tests. As such, healthcare providers are using their data analyses to demonstrate to payers that they can drive down costs. Specifically, they plan to use the analyses to design shared savings and capitated laboratory contracts with payers. “We have to look at other ways of contracting so the payer and the provider are jointly aligned to benefit from the savings created,” he says.
Advice for reducing inappropriate utilization. “Start small and move fast,” Cousin says. “Even just one utilization initiative can have a massive financial impact. Don’t be so overwhelmed by the scope that you do not take that first small step. For us, it’s been a one-step-at-a-time journey. Even organizations with limited ability to invest in this can drive some meaningful change.”
This article is based in part on a presentation at the 2019 ACHE Congress.