You may have seen the news: Mayo Clinic was one of a small number of hospitals in the country awarded a five-star rating by the CMS on its Hospital Compare website when the ratings were released in July. Mayo was also named the top hospital in the country by U.S. News and World Report in its annual Best Hospitals Honor Roll.
What may be surprising, in light of these accolades, is our concern about the way value is being measured.
Why would a top-performing health system have misgivings about measurement? It's simple, really. The mission of Mayo Clinic is to ensure that the needs of the patient come first, and we believe that evaluation programs must reflect the diverse needs of patients. Unfortunately, today, we find that many approaches to measuring value in hospital settings fail to meet this standard.
Many measurement programs currently in use—and others being developed—do not differentiate complexity of patient conditions nor account for their settings of care, which results in inaccurate reports on value. Inaccurate patient attribution cascades throughout the entire measurement process. It creates major gaps in quality and efficiency data, which ultimately renders the corresponding analyses highly suspect, if not useless. When conclusions are drawn based on the wrong numbers of patients in the incorrect category, the results misrepresent reality and do a disservice to patients and the system at large.
To address this problem, we must fix a fundamental element of measurement known as “patient attribution.” While attribution, or the assigning of patients or services to the right category of care, is a highly technical process, it is a cornerstone for accurate measurement of quality and efficiency in healthcare. For example, many models erroneously attribute patients with highly complex care needs, such as those who require the expertise of a specialist, to a hospital's primary-care unit simply because they first came into the hospital through one door instead of another. This can result in “counting” a patient with advanced cancer similarly to a patient being treated for a head cold.
Further, these evaluations fail to account for the patient journey. Mayo Clinic serves high volumes of referred patients from all over the country and the world, often providing care to the sickest patients with the most complex—and often multiple—diagnoses and care needs. Patients regularly come to us after other providers have run out of options, ideas or resources to diagnose and provide the care they need. Because of this, we see many of our patients only after they have previously seen several other providers. Despite their histories, these same patients are often erroneously labeled as “primary care” under some current measurement programs. This creates a significant problem, as analysts expect primary-care patients to have relatively lower costs associated with their care compared with those managed by specialists.
We know that advancing the science of measurement will be a challenge, but it is essential to drive and measure value in healthcare. In fact, our Center for the Science of Health Care Delivery is committed to defining other, more patient-relevant and challenging metrics such as measuring cost of care over time, the speed to correct diagnosis and the value of avoiding some expensive treatments when other oftentimes safer and less expensive treatment options are advisable.
Mayo Clinic is also committed to collaborating with the CMS and leading national organizations such as the National Quality Forum to develop better methods for establishing appropriate patient and services attribution. Like the innovation in our research labs, clinics and hospitals—innovation driven by our collaborative care model—we must also work together to discover better ways to evaluate and measure what we are doing to make patient-driven care better today and in the future.
