Background: Elimination of wasteful diagnostic testing will improve value for the United States health care system.
Objective: Design and implement a multimodal intervention to improve evidence-based ordering of cardiac biomarkers for the diagnosis of acute coronary syndrome (ACS).
Design: Interrupted times series.
Subjects: A total of 60,494 adult inpatient admissions from January 2009 through July 2011 (pre-intervention) and 24,341 admissions from November 2011 through October 2012 (post-intervention) at an academic medical center in Baltimore, Maryland.
Intervention: Multimodal intervention introduced August through October 2011 that included dissemination of an institutional guideline and changes to the computerized provider order entry system.
Main measures: The primary outcome was percentage of patients with guideline-concordant ordering of cardiac biomarkers, defined as three or fewer troponin tests and zero CK-MB tests in patients without a diagnosis of ACS. Secondary outcomes included counts of tests ordered per patient, incidence of diagnosis of ACS, and estimated change in charges for cardiac biomarker tests in the post-intervention period.
Key results: Twelve months following the intervention, we estimated that guideline-concordant ordering of cardiac biomarkers increased from 57.1 % to 95.5 %, an absolute increase of 38.4 % (95 % CI, 36.4 % to 40.4 %). We estimated that the intervention led to a 66 % reduction in the number of tests ordered, and a $1.25 million decrease in charges over the first year. At 12 months, there was an estimated absolute increase in incidence of primary diagnosis of ACS of 0.3 % (95 % CI, 0.0 % to 0.5 %) compared with the expected baseline rate.
Conclusions: We implemented a multimodal intervention that significantly increased guideline-concordant ordering of cardiac biomarker testing, leading to substantial reductions in tests ordered without impacting diagnostic yield. A trial of this approach at other institutions and for other diagnostic tests is warranted and if successful, would represent a framework for eliminating wasteful diagnostic testing.