Geographical and Temporal Distribution of Radiologists, Computed Tomography and Magnetic Resonance Scanners in Croatia.

The aim of the study was to analyse the temporal and geographic distribution of radiologists, computed tomography and magnetic resonance scanners in Croatia. In this observational study we estimated radiologists' number per 100,000 population for 1997, 2006, and 2017 and compared private and public CT and MR scanners between 2011 and 2018. We analyzed the availability of radiologists and scanners, and the relationship between the radiological workforce and economic strength among counties. The workforce increased significantly from 1997 to 2017 and was associated with economic strength categories in 2017. In 2018, there were more CT scanners in the public sector, while MR scanners were distributed evenly. In 2011, there was similar distribution of CT and MR between sectors, while in 2018 there were significantly more public CT scanners. Counties with a medical school had significantly more radiologists and MR scanners. The high-to-low ratios per CT and MR were 11 and 8.2, suggesting inequality of health care. Croatia significantly increased its radiological workforce; however, cross-county inequality remained. Counties with higher economic strength and medical schools have better availability of radiologists and equipment. To ensure the sustainable activity of the health care system, a precise estimate of supply and demand of radiology services is needed.

The analysis of waiting time and utilization of computed tomography and magnetic resonance imaging in Croatia: a nationwide survey.

AIM: To assess the variation in the waiting time for diagnostic imaging (DI) services among Croatian public hospitals and the utilization of computed tomography (CT) and magnetic resonance imaging (MRI) scanners. METHODS: We analyzed aggregated data from public hospitals. Counties were classified according to economic strength, and utilization was expressed as the average number of exams per machine. We compared the waiting times for 2018 and utilization for 2015 according to hospital category (high and low level) and economic strength by county. RESULTS: The waiting time was longer for MRI compared with CT, 268 vs 77.61 days. Overall CT waiting time was in the unfavorable European Health Consumer Index category. High-level hospitals had longer waiting time for MRI and CT. The waiting time positively correlated with economic strength for MRI (P=0.019), but not for CT. In low-level hospitals, MRI utilization ranged from 104 to 6032, whereas CT utilization ranged from 48 to 17852. In high-level hospitals, MRI utilization ranged from 3846 to 11 026, while CT utilization ranged from 503 to 17 234. CT (P=0.041) and MRI (P=0.031) utilization in high-level hospitals was significantly higher than in low-level hospitals. CONCLUSION: The waiting times for CT and MRI were exceptionally long regardless of the hospital category, with highly varying utilization. Croatia performed more exams per scanner compared with other EU countries, but not significantly so. High-level hospitals' utilization was significantly higher than that of low-level hospitals, and CT utilization was significantly higher than EU average, while the difference for MRI utilization was not significant.

Quantification of coronary atherosclerotic burden with coronary computed tomography angiography: adapted Leaman score in Croatian patients.

The aim of the study was to quantify the total coronary atherosclerotic burden in patients with suspected coronary artery disease (CAD) defined by coronary computed tomography adapted Leaman score (CT-LeSc) and to estimate its cut-off level for high coronary atherosclerotic burden. We enrolled 434 consecutive patients referred to coronary computed tomography angiography, of which 261 patients fulfilled the study inclusion criteria. Demographic and clinical characteristics, as well as CAD risk factors were obtained. CAD pre-test probabilities were estimated by the Diamond-Forrester model and Morise score. The coronary atherosclerotic burden was estimated using CT-LeSc. As a cut-off for a high coronary atherosclerotic burden, we used 3rd tercile (Tc3) (CT-LeSc ≥ 5.52). We evaluated the association of clinical characteristics and risk factors with Tc3 in univariate and multivariate analysis. There were 60.9% males and 39.1% females, 81% of patients had above-normal weight, 68.2% hypertension, 54.0% dyslipidemia, 15.3% diabetes mellitus, 12.3% positive smoking history and 11.9% had a family history of CAD. According to the Diamond-Forrester model and Morise score the majority of patients had intermediate risk, 59.7 and 52.8%, followed by the high-risk group, 36.0 and 34.4%, respectively. Age, dyslipidemia, hypertension and pre-test risk scores in the univariate analysis significantly predicted Tc3. In the multivariate analysis, male sex (p = 0.004), dyslipidemia (p = 0.002) and coronary calcium score (< 0.001) were identified as predictors of Tc3. CT-LeSc quantified the total coronary atherosclerotic burden and showed an association of risk factors and pre-test probabilities with Tc3.