OBJECTIVES: This study sought to evaluate the impact of a multimodality-appropriate use criteria decision support tool (AUC-DST) on rates of appropriate testing and clinical decision making. BACKGROUND: AUC have been developed to guide utilization of noninvasive imaging for individuals with suspected coronary artery disease (CAD). The effect of a point-of-order AUC-DST on rates of appropriateness and clinical decision making has not been examined. METHODS: We performed a prospective multicenter cohort study evaluating physicians who ordered CAD imaging tests for consecutive patients insured by 1 large private payer. During an 8-month study period, each study site was granted exemption from prior authorization requirements by radiology benefits managers. An AUC-DST was employed to determine appropriateness ratings for myocardial perfusion scintigraphy (MPS), stress echocardiography (STE), or coronary computed tomographic angiography (CCTA), as well as intended downstream testing and therapy. RESULTS: One hundred physicians used the AUC-DST for 472 patients (age 55.6 ± 9.6 years, 61% male, 52% prior known CAD) over 8 months for MPS (72%), STE (24%), and CCTA (5%). The AUC-DST required an average of 137 ± 360 s to determine the appropriateness category that, by American College of Cardiology AUC, was considered appropriate in 241 (51%), uncertain in 96 (20%), inappropriate in 85 (18%), and not addressed in 50 (11%). For tests ordered in the first 2 months compared with the last 2 months, appropriate tests increased from 49% to 61% (p = 0.02), whereas inappropriate tests decreased from 22% to 6% (p < 0.001). During this period, intended changes in medical therapy increased from 11% to 32% (p = 0.001). CONCLUSIONS: A point-of-order AUC-DST enabled rapid determination of test appropriateness for CAD evaluation and was associated with increased and decreased testing for appropriate and inappropriate indications, respectively. These changes in test ordering were associated with greater intended changes in post-test medical therapy.
OBJECTIVES: This study sought to evaluate the impact of a multimodality-appropriate use criteria decision support tool (AUC-DST) on rates of appropriate testing and clinical decision making. BACKGROUND: AUC have been developed to guide utilization of noninvasive imaging for individuals with suspected coronary artery disease (CAD). The effect of a point-of-order AUC-DST on rates of appropriateness and clinical decision making has not been examined. METHODS: We performed a prospective multicenter cohort study evaluating physicians who ordered CAD imaging tests for consecutive patients insured by 1 large private payer. During an 8-month study period, each study site was granted exemption from prior authorization requirements by radiology benefits managers. An AUC-DST was employed to determine appropriateness ratings for myocardial perfusion scintigraphy (MPS), stress echocardiography (STE), or coronary computed tomographic angiography (CCTA), as well as intended downstream testing and therapy. RESULTS: One hundred physicians used the AUC-DST for 472 patients (age 55.6 ± 9.6 years, 61% male, 52% prior known CAD) over 8 months for MPS (72%), STE (24%), and CCTA (5%). The AUC-DST required an average of 137 ± 360 s to determine the appropriateness category that, by American College of Cardiology AUC, was considered appropriate in 241 (51%), uncertain in 96 (20%), inappropriate in 85 (18%), and not addressed in 50 (11%). For tests ordered in the first 2 months compared with the last 2 months, appropriate tests increased from 49% to 61% (p = 0.02), whereas inappropriate tests decreased from 22% to 6% (p < 0.001). During this period, intended changes in medical therapy increased from 11% to 32% (p = 0.001). CONCLUSIONS: A point-of-order AUC-DST enabled rapid determination of test appropriateness for CAD evaluation and was associated with increased and decreased testing for appropriate and inappropriate indications, respectively. These changes in test ordering were associated with greater intended changes in post-test medical therapy.
Authors: David E Winchester; Andrew Kitchen; John C Brandt; Raman S Dusaj; Salim S Virani; Steven M Bradley; Leslee J Shaw; Rebecca J Beyth Journal: Clin Cardiol Date: 2015-04-13 Impact factor: 2.882
Authors: Siqin Ye; LeRoy E Rabbani; Christopher R Kelly; Maureen R Kelly; Matthew Lewis; Yehuda Paz; Clara L Peck; Shaline Rao; Sabahat Bokhari; Shepard D Weiner; Andrew J Einstein Journal: Circ Cardiovasc Qual Outcomes Date: 2015-01-06
Authors: Weihan Chen; David T Saxon; Michael P Henry; John R Herald; Rob Holleman; Debbie Zawol; Stacy Sivils; Mohamad A Kenaan; Theodore J Kolias; Hitinder S Gurm; Nicole M Bhave Journal: J Am Soc Echocardiogr Date: 2020-11-01 Impact factor: 5.251
Authors: Sigal Trattner; Gregory D N Pearson; Cynthia Chin; Dianna D Cody; Rajiv Gupta; Christopher P Hess; Mannudeep K Kalra; James M Kofler; Mayil S Krishnam; Andrew J Einstein Journal: J Am Coll Radiol Date: 2014-03 Impact factor: 5.532
Authors: Islam Y Elgendy; Ahmed Mahmoud; Jonathan J Shuster; Rami Doukky; David E Winchester Journal: J Nucl Cardiol Date: 2015-08-08 Impact factor: 5.952