With unsustainably high costs and tremendous gaps in quality and patient safety, the health care system is ripe with opportunities for improvement. For years, many have seen quality measurement as a means to drive needed change. Private and public payers, public health departments, and independent accreditation organizations have asked health care providers to report on quality measures, and quality measures have been publicly reported or tied to financial reimbursement or both.
Throughout the Affordable Care Act (ACA), quality measures are tied to reimbursements in multiple programs. It is critical that the Department of Health and Human Services (HHS) move forward with a strategy for measure harmonization that will accommodate local and national needs to evaluate outcomes and value. Additionally, a standard for calculation measures such as the use of a minimal data set for the universe of measures should be considered.
The field of quality measurement is at a critical juncture. The Affordable Care Act (ACA)—which mentions “quality measures,” “performance measures,” or “measures of quality,” 128 times—heightened an already growing emphasis on quality measurement. With so much focus on quality, the resource burden on health care providers of taking and reporting measures for multiple agencies and payers is significant.
Furthermore, the field itself is being transformed with the continued adoption of electronic health records (EHRs). Traditional measures are largely based on administrative or claims data. The increased use of EHRs create the opportunity to develop sophisticated electronic clinical quality measures (eQMs) leveraging clinical data, which when linked with clinical decision support tools and payment policy, have the potential to improve quality and decrease costs more dramatically than traditional ones. Innovative electronic measures on the horizon include “delta measures” calculating changes in patient health over time and care coordination measures for the electronic transfer of patient information (i.e., hospital discharge summary or consultant note successfully transmitted to the primary care physician). Additionally, traditional data abstraction methodologies for clinical data require labor intensive, chart review processes, which would be eliminated if data could be electronically extracted.