Are you prepared for Meaningful Measures?
January 31, 2018 •David Fletcher
By David Fletcher
Vice President – Innovations, Streamline Health, Inc.
Every day, when patients visit their doctors, care organizations generate data. Some of that information is highly relevant to the patient, such as lab/test results and medication prescriptions. Some is vital to quality managers, like task checklists and process outcomes. And some of that information is important for payment such as charge and procedure codes. As payment models shift from fee-for-service to value based, additional data elements are required to summarize the quality of care. In 2017, Centers for Medicare & Medicaid Services (CMS) Administrator Seema Verma states that inpatient hospitals report up to 61 CMS quality measures, of which 12 are “chart extracted”, while family practitioners report nearly 30 measures to seven different payers. Many medical professionals believe this latter segment takes up too much time and does little to benefit patients, and Verma agrees. The perception is that it’s an exercise in administrative futility, filling out forms and checking boxes, with no impact on care delivery or improved outcomes.
“Whether CMS is looking at the Quality Payment Program, Meaningful Use or Meaningful Measures, the data and metrics they need to track are all found in the same place: your documentation and coding.”
In October 2017, two months after announcing a year’s delay in Meaningful Use Stage 3—the phase that many assailed as an onerous reporting burden—CMS announced a new program called Meaningful Measures. Meaningful Measures aims to reduce this regulatory burden, restore the patient/physician relationship and create a free and dynamic market where providers compete for patients. It will also reinforce the growing importance of proactively managing documentation and coding accuracy.
The Meaningful Measures framework maintains a quality focus to drive payment models while also reducing the amount of process measures that are required in favor of higher level clinical outcome measures. Additionally, by focusing in “high priority areas”, it’s hoped that some regulatory burden may be relieved. In my opinion, process measurement will still be needed by providers even if they are not mandated to report them to CMS. Process measurement drives improvement in clinical outcomes. That said, internal measurement of process outcomes will certainly be less burdensome than preparing submissions to CMS for the same intent. Patients care about clinical outcomes, and that is where CMS is focusing.
The Meaningful Measures framework is summarized in the diagram from CMS below. The six “level 1” goals in the outer ring of the diagram include 18 “level 2” measurement areas that, in turn, will drive numerous “level 3” atomic measures. Ostensibly, these level 3 measurements would be left to providers to manage themselves. We’ll see how the rules for Meaningful Measures evolve.
Renewed Need for Documentation Accuracy
If Meaningful Use is a quantity-based approach to clinical reporting, then Meaningful Measurements could be seen as the quality-based approach that assesses the efficiency and efficacy of care delivery. Whether CMS is looking at the Quality Payment Program, Meaningful Use or Meaningful Measures, the data and metrics they need to track are all found in the same place: your documentation and coding.
As CMS continues to offer quality- and value-based payment models, concurrent monitoring and estimation of these measures is becoming a higher priority for the teams that ensure accuracy in billing such as Clinical Documentation Improvement (CDI) programs. The challenge is that data needed for these measures currently reside in multiple systems in the clinical environment, and like your documentation and coding, may require additional review and optimization in order to accurately reflect the patient experience, acuity of care, etc. Without the ability to access, review and manage this data in a timely manner, the ensuing lack of accuracy will cost your organization in terms of perceived clinical performance and revenue generation.
With siloed systems and lack of technical integration, most providers simply cannot pursue a strategy that enables proactive management of these mid-revenue cycle processes. Direct feedback on documentation and coding accuracy tends to occur in the form of denials and post-billing audits, while indirectly the poor accuracy contributes to lower quality ratings. Meanwhile, revenue leakage and compliance exposure continues to deny the organization of vital resources.
Instead, automated measurement, automated accuracy assessment and a responsive improvement team are critical to success under these payment models.
Whether addressing Meaningful Use or Meaningful Measures, your organization is still limited by its ability to proactively manage documentation and coding accuracy. As such, any organizational initiative that improves documentation and coding accuracy earlier in the revenue cycle will yield major benefits. When documentation and coding data accurately reflect the patient encounter, including acuity of care and all supporting details, the organization can confidently request reimbursement, track outcomes and report quality performance.
Improved Accuracy Helps All
A reactive strategy to managing accuracy—where most feedback occurs post-billing— requires a great deal of resources. However, with a proactive approach to confirming accuracy, more resources can be dedicated to providing better patient care. As such, any organizational initiative that improves documentation and coding accuracy will yield major benefits beyond the revenue cycle. This means that regardless of any regulatory requirements, pursuing a strategy that proactively improves documentation and coding accuracy will yield Meaningful Improvements for you and your patients.
To learn more about how to proactively improve documentation and coding accuracy at your organization, visit StreamlineHealth.net today.