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This blog post is the first of an eight-part ACCCBuzz series highlighting the achievements of the 2020 ACCC Innovator Award Winners. You can learn more about the innovations being recognized this year and the people who pioneered them by joining us at the ACCC 37th [Virtual] National Oncology Conference, September 14-18, 2020.
Quality measure OP-35—the first chemo-specific measure in the Centers for Medicare & Medicaid Services (CMS) Hospital Outpatient Quality Reporting (OQR) Program—officially went into effect for payment determination this year.
Michelle Smith, DC, director of oncology services at Mercy Cancer Care, explains that measure OP-35 looks at the rate of inpatient admissions and emergency department (ED) visits for 10 potentially preventable conditions (i.e., anemia, dehydration, diarrhea, emesis, fever, nausea, neutropenia, pain, pneumonia, and sepsis) within 30 days of each hospital-based outpatient chemotherapy treatment for non-leukemia patients age 18 years or older. In addition to reducing costly hospital admissions and ED services, the new quality measure provides cancer programs with valuable data on how often their patients seek care related to their cancer treatment outside of the oncology care setting. As a claims-based measure, OP-35 does not require hospitals to report data. CMS uses paid fee-for-service claims to calculate the measure’s results.
Because the OQR Program is a pay-for-reporting program, the only financial penalty is a two percent reduction in the annual payment update for hospitals that do not collect and submit required data for measures included in the program or that do not meet the administrative, data collection and submission, validation, and reporting requirements of the OQR Program. For example, CY 2020 payment determination was based on measure performance results based on claims data from January 1, 2018 to December 31, 2018.
The addition of OP-35 to the OQR measures was finalized under the CY 2017 Outpatient Prospective Payment System (OPPS) final rule, which brought OP-35 into the OQR for payment determination in CY 2020 and subsequent years.
At the time, Mercy Cancer Care—part of Mercy Health in St. Louis, Missouri—knew that it needed to get ahead of the curve to be fully prepared for the new measure.
“Mercy Health did not have a model to identify patients as being at risk,” says Smith. In some cases, patients were admitted to an inpatient setting or had two or three ED visits before the cancer care team was made aware of these encounters. So Smith and her Mercy Health team began developing a predictive algorithm to help providers and staff across the healthcare system identify patients who are at risk for an inpatient admission or ED visit after receiving chemotherapy.
Creating this predictive model required the multidisciplinary team at Mercy Health to conduct a retrospective review of patients’ charts to determine how many had an inpatient admission or ED visit(s) and then identify the variables that could have contributed to those events. “We had medical oncologists across the [health] ministry, practitioners, and other clinic support staff, quality team members, and infusion staff collaborate on this project,” says Smith. The end goal: to gather enough data to create an algorithm that could be applied across the entire health system.
After receiving Institutional Review Board (IRB) approval to review patients’ medical histories, the team mined three years of patient data (from January 1, 2016 to December 31, 2018) across all Mercy Health Cancer Care locations. “We looked at 90,000 qualifying chemotherapy visits that met the criteria for measure OP-35,” says Smith.
The review identified multiple clinical variables that were significantly associated with patients’ increased risk of hospital admissions or ED visits. “Some variables were discrete and pulled from our EHR, while others required natural language processing to identify and extract,” explains Smith. Using these variables, the Mercy Cancer Care team developed and tested a predictive algorithm that identifies patients at risk for hospital admissions and ED visits within 30 days of chemotherapy treatment(s).
Mercy implemented its algorithm across the system in early 2020. Using this tool, any clinic or cancer center can create automatic daily reports via its Mercy Oncology Dashboard, which pulls the required information from its EHR. These reports are sent to providers and staff so they can proactively manage at-risk patients. “It was exciting to see how rapidly the clinical team integrated this real-world evidence into their daily practice and to hear the stories of how the risk score changed clinical care,” says Smith.
Michelle Smith will give an in-depth presentation on exactly how her team developed and implemented its predictive algorithm at the ACCC 37th [Virtual] National Oncology Conference, September 14-18, 2020. To find out more about how this algorithm is helping Mercy Cancer Center successfully meet measure OP-35, register for the session, "Reducing Readmissions After Chemotherapy With Predictive Modeling of Risk Factors."
Attend the ACCC 37th National Oncology Conference and learn about the accomplishments of the other 2020 ACCC Innovator Award winners on topics ranging from a nurse navigator-led cardio-oncology clinic to a 3D educational tool that reduces patient distress.