Who is missing from the measures? Trends in the proportion and treatment of patients potentially excluded from publicly reported quality measures

Abstract

Background: The Centers for Medicare and Medicaid Services provides public reporting on the quality of hospital care for patients with acute myocardial infarction (AMI). The Centers for Medicare and Medicaid Services Core Measures allow discretion in excluding patients because of relative contraindications to aspirin, β-blockers, and angiotensin-converting enzyme inhibitors. We describe trends in the proportion of patients with AMI with contraindications that could lead to discretionary exclusion from public reporting.

Methods: We completed cross-sectional analyses of 3 nationally representative data cohorts of AMI admissions among Medicare patients in 1994-1995 (n = 170,928), 1998-1999 (n = 27,432), and 2000-2001 (n = 27,300) from the national Medicare quality improvement projects. Patients were categorized as ineligible (eg, transfer patients), automatically excluded (specified absolute medical contraindications), discretionarily excluded (potentially excluded based on relative contraindications), or "ideal" for treatment for each measure.

Results: For 4 of 5 measures, the percentage of discretionarily excluded patients increased over the 3 periods (admission aspirin 15.8% to 16.9%, admission β-blocker 14.3% to 18.3%, discharge aspirin 10.3% to 12.3%, and angiotensin-converting enzyme inhibitors 2.8% to 3.9%; P < .001). Of patients potentially included in measures (those who were not ineligible or automatically excluded), the discretionarily excluded represented 25.5% to 69.2% in 2000-2001. Treatment rates among patients with discretionary exclusions also increased for 4 of 5 measures (all except angiotensin-converting enzyme inhibitors).

Conclusions: A sizeable and growing proportion of patients with AMI have relative contraindications to treatments that may result in discretionary exclusion from publicly reported quality measures. These patients represent a large population for which there is insufficient evidence as to whether measure exclusion or inclusion and treatment represents best care.

Figure 1

Schematic of Sample and Patient Categories

Figure 2

Percentage of patients with discretionary exclusions among measure eligible patients