National variation in the utilization of alternative imaging in peripheral arterial disease

Abstract

Objective: The value and cost-effectiveness of less invasive alternative imaging (AI) modalities (duplex ultrasound scanning, computed tomography angiography, and magnetic resonance angiography) in the care of peripheral arterial disease (PAD) has been reported; however, there is no consensus on their role. We hypothesized that AI utilization is low compared with angiography in the United States and that patient and hospital characteristics are both associated with AI utilization.

Methods: The Nationwide Inpatient Sample (2007-2010) was used to identify patients with an International Classification of Diseases-Ninth Edition diagnosis of claudication or critical limb ischemia (CLI) as well as PAD treatment (surgical, endovascular, or amputation). Patients with AI and those with angiography or expected angiography (endovascular procedures without imaging codes) were selected and compared. Multivariable logistic regression was performed for receiving AI stratified by claudication and CLI and adjusting for patient and hospital factors.

Results: We identified 290,184 PAD patients, of whom 5702 (2.0%) received AI. Patients with AI were more likely to have diagnosis of CLI (78.8% vs 48.6%; P < .0001) and receive open revascularizations (30.4% vs 18.8%; P < .0001). Van Walraven comorbidity scores (mean [standard error] 5.85 ± 0.22 vs 4.10 ± 0.05; P < .0001) reflected a higher comorbidity burden in AI patients. In multivariable analysis for claudicant patients, AI was associated with large bed size (odds ratio [OR], 3.26, 95% confidence interval [CI], 1.16-9.18; P = .025), teaching hospitals (OR, 1.97; 95% CI, 1.10-3.52; P = .023), and renal failure (OR, 1.52; 95% CI, 1.13-2.05; P = .006). For CLI patients, AI was associated with black race (OR, 1.53; 95% CI, 1.13-2.08; P = .006) and chronic heart failure (OR, 1.29; 95% CI, 1.04-1.60; P = .021) and was negatively associated with renal failure (OR, 0.80; 95% CI, 0.67-0.95; P = .012). The Northeast and West regions were associated with higher odds of AI in claudicant patients (OR, 2.41; 95% CI, 1.23-4.75; P = .011; and OR, 2.59; 95% CI, 1.34-5.02; P = .005, respectively) and CLI patients (OR, 4.31; 95% CI, 2.20-8.36; P < .0001; and OR, 2.18; 95% CI, 1.12-4.22; P = .021, respectively). Rates of AI utilization across states were not evenly distributed but showed great variability, with ranges from 0.31% to 9.81%.

Conclusions: National utilization of AI for PAD is low and shows great variation among institutions in the United States. Patient and hospital factors are both associated with receiving AI in PAD care, and AI utilization is subject to significant regional variation. These findings suggest differences in systems of care or practice patterns and call for a clearer understanding and a more unified approach to imaging strategies in PAD care.