Faculty Bibliography

PURPOSE/OBJECTIVE:To explore associations between county-level measures of radiologist supply and subspecialization and county structural and health-related characteristics. METHODS:Medicare Physician and Other Supplier Public Use Files were used to subspecialty characterize 32,844 radiologists participating in Medicare between 2012 and 2014. Measures of radiologist supply and subspecialization were computed for 3,143 US counties. Additional county characteristics were identified using the 2014 County Health Rankings database. Mann-Whitney tests and Spearman correlations were performed. RESULTS:Counties with at least one (versus no) Medicare-participating radiologist had significantly (P < .001) larger populations (197,050 ± 457,056 versus 20,253 ± 23,689), lower rural percentages (39.5% ± 26.5% versus 74.6% ± 25.6%), higher household incomes ($47,608 ± $12,493 versus $42,510 ± $9,893), higher mammography screening rates (62.4% ± 7.0% versus 56.6% ± 15.3%), and lower premature deaths (7,581 ± 2,085 versus 7,784 ± 3,409 years of life lost). Counties' radiologists per 100,000 population and percent of subspecialized radiologists showed moderate positive correlations with counties' population (r = +0.505-+0.599) and moderate negative correlations with counties' rural percentage (r = -0.434 to -0.523). Radiologist supply and degree of subspecialization both showed concurrent positive or negative weak associations with counties' percent age 65+ (r = -0.256 to -0.271), percent Hispanic (r = +0.209-+0.234), and income (r = +0.230-+0.316). Radiologists per 100,000 population showed weak positive correlation with mammography screening (r = +0.214); percent of radiologists subspecialized showed weak negative correlation with premature death (r = -0.226). CONCLUSION/CONCLUSIONS:Geographic disparities in radiologist supply at the community level are compounded by superimposed variation in the degree of subspecialization of those radiologists. The potential impact of such access disparities on county-level health warrants further investigation.

RATIONALE AND OBJECTIVES/OBJECTIVE:To assess associations between screening mammography utilization and Medicare beneficiaries' relationships with, and impressions of, their primary care physicians. MATERIALS AND METHODS/METHODS:Using the Medicare Current Beneficiary Survey Access to Care Public Use File, we retrospectively studied responses from a national random cross section of Medicare beneficiaries surveyed in 2013 regarding perceptions of their primary care physicians and their screening mammography utilization. Statistical analysis accounted for subject weighting factors to estimate national screening utilization. RESULTS:Among 7492 female Medicare beneficiaries, 62.0% (95% confidence interval 59.8%-64.2%) underwent screening mammography. Utilization was higher for beneficiaries having (vs. not) a regular medical practice or clinic (63.2% vs. 34.6%) and a usual physician (63.8% vs. 50.3%). Utilization was higher for beneficiaries very satisfied (vs. very dissatisfied) with the overall quality of care they received (66.0% vs. 35.8%), their ease of getting to a doctor (67.7% vs. 43.2%), and their physician's concerns for their health (65.7% vs. 53.4%), as well as for beneficiaries strongly agreeing (vs. strongly disagreeing) that their physician is competent (66.0% vs. 54.1%), understands what is wrong (66.3% vs. 47.1%), answers all questions (67.0% vs. 46.7%), and fosters confidence (66.0% vs. 50.6%). Independent predictors of screening mammography utilization (P < .05) were satisfaction with quality of care, having a regular practice or clinic, and satisfaction with ease of getting to their physician. CONCLUSIONS:Screening mammography utilization is higher among Medicare beneficiaries with established primary physician relationships, particularly when those relationships are favorable. To optimize screening mammography utilization, breast imagers are encouraged to support initiatives to enhance high-quality primary care relationships.

PURPOSE/OBJECTIVE:The Medicare Access and CHIP Reauthorization Act (MACRA) provides CMS flexibility to evaluate radiologists using hospital outpatient quality measures in place of conventional physician measures. We explore radiologist characteristics associated with variation in performance in two such measures: abdomen and chest CT "double scan" rates (percentage of total examinations performed both with and without intravenous contrast). METHODS:Radiologists' claims for abdomen and chest CT examinations in a facility setting were identified using 2014 Medicare Physician and Other Supplier data. Individual radiologist double scan rates were computed. Associations were explored between rates and radiologist characteristics extracted from the CMS public data sets using multivariable regression with cross-validation. RESULTS:Radiologists' double scan rates averaged 5.9% ± 10.0% (0.0% for 52.8% of radiologists) for abdomen CT (19,867 radiologists) and 1.0% ± 4.7% (0.0% for 91.3% of radiologists) for chest CT (18,684). At multivariable analysis, abdomen rates were best predicted by geography (lowest in Northeast, greatest in West), practice size (greatest for small practices), and specialty practice pattern (lowest for general radiologists; greatest for nuclear medicine physicians). Agreement for double scan rates among radiologists within the same practice was moderate, though slightly higher for chest (intraclass correlation = 0.70) than abdomen (0.59). CONCLUSION/CONCLUSIONS:Radiologists' facility double scan rates vary systematically based on an array of professional characteristics. MACRA grants CMS the authority to use these measures for evaluating radiologists, thereby aligning Medicare's hospital and physician performance programs and better incentivizing population radiation dose and cost reduction. Greater variation in abdomen CT double scan rates, compared with ubiquitously excellent chest CT performance, supports a particular role for abdomen rates in distinguishing disparities in radiologist performance.

PURPOSE/OBJECTIVE:To optimize the flexibility and relevancy of its Merit-Based Incentive Payment System (MIPS), CMS exempts selected physicians and groups from participation and grants others relaxed reporting requirements. We assess the practical implications of such special status determinations. METHODS:For a random sample of 1,000 Medicare-participating radiologists, the CMS MIPS Participation Lookup Tool was manually searched. Individual radiologists' and associated groups' participation requirements and special statuses were assessed. RESULTS:Although only 55% of radiologists were required to participate in MIPS as individuals when considering only one associated taxpayer identification number (TIN), 83% were required to participate as individuals when considering all associated TINs. When using the group reporting option, 97% of radiology groups were required to participate. High participation requirements persisted across generalist and subspecialist radiologists, small and rural, and both academic and nonacademic practices. Non-patient-facing and hospital-based statuses were assigned to high fractions of individual radiologists (91% and 71%, respectively), but much lower fractions of group practices (72% and 25%). Rural and health professional shortage area statuses were assigned to higher percentages of groups (27% and 39%) than individuals (13% and 23%). Small practice status was assigned to 22% of individuals versus 16% of groups. CONCLUSION/CONCLUSIONS:Although not apparent if only considering individual radiologist-TIN combinations, the overwhelming majority of radiologists will be required to participate in MIPS, at the individual or group level. Radiology groups are strongly encouraged to review their physicians' MIPS participation requirements and special statuses to ensure optimal performance scores and payment bonuses.

OBJECTIVE/OBJECTIVE:The objective of our study was to use a new modality and body region categorization system to assess changing utilization of noninvasive diagnostic imaging in the Medicare fee-for-service population over a recent 20-year period (1994-2013). MATERIALS AND METHODS/METHODS:All Medicare Part B Physician Fee Schedule services billed between 1994 and 2013 were identified using Physician/Supplier Procedure Summary master files. Billed codes for diagnostic imaging were classified using the Neiman Imaging Types of Service (NITOS) coding system by both modality and body region. Utilization rates per 1000 beneficiaries were calculated for families of services. RESULTS/RESULTS:Among all diagnostic imaging modalities, growth was greatest for MRI (+312%) and CT (+151%) and was lower for ultrasound, nuclear medicine, and radiography and fluoroscopy (range, +1% to +31%). Among body regions, service growth was greatest for brain (+126%) and spine (+74%) imaging; showed milder growth (range, +18% to +67%) for imaging of the head and neck, breast, abdomen and pelvis, and extremity; and showed slight declines (range, -2% to -7%) for cardiac and chest imaging overall. The following specific imaging service families showed massive (> +100%) growth: cardiac CT, cardiac MRI, and breast MRI. CONCLUSION/CONCLUSIONS:NITOS categorization permits identification of temporal shifts in noninvasive diagnostic imaging by specific modality- and region-focused families, providing a granular understanding and reproducible analysis of global changes in imaging overall. Service family-level perspectives may help inform ongoing policy efforts to optimize imaging utilization and appropriateness.

Purpose To assess subspecialty practice characteristics of the U.S. radiologist workforce. Materials and Methods This study used the Medicare Physician and Other Supplier Public Use File and did not constitute human subject research. The authors identified 33 090 radiologists who billed for professional services between 2012 and 2014 and used a validated classification system to map services to seven subspecialties and quantify subspecialty-focused effort on the basis of work relative value units (RVUs). Radiologists with more than half of their billed work RVUs in a single subspecialty were designated subspecialists; the remainder were classified as generalists. Matching radiologists with various characteristics extracted from other publicly available data sets, associations were explored through use of analysis of variance and multivariable logistic regression. Results More than half (55.3%) of U.S. radiologists practice predominantly as generalists but dedicate on average 36.0% effort to one subspecialty. Among radiologists practicing as majority subspecialists, neuroradiologists (10.1% of all radiologists) and breast imagers (8.4%) are most common. Subspecialization is more common (P < .001) among radiologists who are female, are earlier in their career, work in larger practices, have academic affiliations, and practice in the Northeast. By subspecialty, female representation varies from 8.6% (interventional radiology) to 63.1% (breast imaging); cardiothoracic imagers were more commonly early career radiologists, and nuclear medicine physicians were later career radiologists. Subspecialization is considerably more common in larger (>/=100 members) practices (63.1%). An academic affiliation is the strongest independent predictor of subspecialization (odds ratio, 3.56; 95% confidence interval: 3.30, 3.84). Conclusion Despite an increased focus on radiology subspecialization, most U.S. radiologists are majority general radiologists on the basis of their work RVUs. Subspecialization is by far more prevalent in larger and academic practices. ((c)) RSNA, 2017 Online supplemental material is available for this article.

OBJECTIVE: To develop nomograms that predict the probability of overall PCa and clinically significant PCa (Gleason >/=7) on MRI targeted, and combined MRI-targeted and systematic, prostate biopsy. MATERIALS AND METHODS: From June 2012 to August 2014, MR-US fusion targeted prostate biopsy was performed on 464 men with suspicious regions identified on pre-biopsy 3T MRI along with systematic 12 core biopsy. Logistic regression modeling was used to evaluate predictors of overall and clinically significant PCa, and corresponding nomograms were generated for men who were not previously biopsied or had one or more prior negative biopsies. Models were created with 70% of a randomly selected training sample and bias-corrected using bootstrap resampling. The models were then validated with the remaining 30% testing sample pool. RESULTS: A total of 459 patients were included for analysis (median age 66 years, PSA 5.2 ng/ml, prostate volume 49 cc). Independent predictors of PCa on targeted and systematic prostate biopsy were PSA density, age, and MRI suspicion score. PCa probability nomograms were generated for each cohort using the predictors. Bias-corrected areas under the receiver-operating characteristic curves for overall and clinically significant PCa detection were 0.82 (0.78) and 0.91 (0.84) for men without prior biopsy and 0.76 (0.65) and 0.86 (0.87) for men with a prior negative biopsy in the training (testing) samples. CONCLUSION: PSA density, age, and MRI suspicion score predict prostate cancer on combined MRI-targeted and systematic biopsy. Our generated nomograms demonstrate high diagnostic accuracy and may further aid in the decision to perform biopsy in men with clinical suspicion of PCa.

PURPOSE: To evaluate radiologist preferences regarding specific content that warrants inclusion in prostate MRI reports. METHODS: Sixty-one members of the Society of Abdominal Radiology responded to a 74-item survey regarding specific content warranted in prostate MRI reports, conducted in August 2016. RESULTS: General items deemed essential report content by >/= 50% of respondents were prostate volume (80%), extent of prostate hemorrhage (74%), TURP defects (69%), coil type (64%), BPH (61%), contrast dose (61%), contrast agent (59%), medications administered (59%), and magnet strength (54%). Details regarding lesion description deemed essential by >/= 50% were overall PI-RADS category (88%), DCE (+/-) (82%), subjective degree of diffusion restriction (72%), T2WI intensity (72%), T2WI margins (65%), T2WI shape (52%), DWI 1-5 score (50%), and T2WI 1-5 score (50%). Details deemed essential to include in the report Impression by >/= 50% of respondents were lymphadenopathy and metastases (100%), EPE (98%), SVI (98%), neurovascular bundle involvement (93%), index lesion location (93%), PI-RADS category of index lesion (82%), number of suspicious lesions (78%), significance of index lesion PI-RADS category (53%), and PI-RADS category of non-index lesions (52%). Preferred methods for lesion localization were slice/image number (68%), 3-part craniocaudal level (68%), zonal location (65%), anterior vs. posterior location (57%), and medial vs. lateral position (56%). Least preferred methods for localization were numeric sector from the PI-RADS sector map (8%), annotated screen capture (10%), and graphical schematic of PI-RADS sector map (11%). CONCLUSION: Radiologists generally deemed a high level of detail warranted in prostate MRI reports. The PI-RADS v2 sector map was disliked for lesion localization.

RATIONALE AND OBJECTIVES: Meaningfully measuring physician outcomes and resource utilization requires appropriate patient risk adjustment. We aimed to assess Medicare patient complexity by physician specialty and to further identify radiologist characteristics associated with higher patient complexity. MATERIALS AND METHODS: The average beneficiary Hierarchical Condition Category (HCC) risk scores (Medicare's preferred measure of clinical complexity) were identified for all physicians using 2014 Medicare claims data. HCC scores were compared among physician specialties and further stratified for radiologists based on a range of characteristics. Univariable and multivariable analyses were performed. RESULTS: Of 549,194 physicians across 54 specialties, the mean HCC risk score was 1.62 +/- 0.75. Of the 54 specialties, interventional radiology ranked 4th (2.60 +/- 1.29), nuclear medicine ranked 16th (1.87 +/- 0.45), and diagnostic radiology ranked 21st (1.75 +/- 0.61). Among 31,175 radiologists, risk scores were higher (P < 0.001) for those with teaching (2.03 +/- 0.74) vs nonteaching affiliations (1.72 +/- 0.61), practice size >/=100 (1.94 +/- 0.70) vs