Faculty Bibliography
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Exploring Which Medical Schools Cost the Most: An Assessment of Medical School Characteristics Associated With School Tuition
OBJECTIVE:To assess medical school characteristics associated with school tuition. MATERIALS AND METHODS/METHODS:US medical schools' tuitions, and various medical school characteristics, were extracted from the Association of American Medical Colleges' online MSAR database, using in-state tuition when applicable. US News ranking and National Institutes of Health (NIH) award ranking from the Blue Ridge Institute for Medical Research were obtained, when available. Geographic population density was obtained using Governing magazine's online database. Cost of living estimates were obtained from online American Chamber of Commerce Research Association Cost of Living Index. Spearman correlations were determined, and multivariable linear regression was performed. RESULTS:Among 148 included medical schools, adjusted average ± standard deviation tuition was $47,612 ± $23,765 (range $12,761-$141,464). Tuition demonstrated positive correlations with regional population density (r = +0.577) and years established (r = +0.265). Among ranked schools, tuition showed negative correlations with US News rank (r = -0.469) and NIH rank (r = -0.336). Average tuition varied by geographic region: Northeast: $49,662, Midwest: $43,560, West: $37,701, and South: $34,270. Among states with at least 3 medical schools, average tuition was highest in MA ($53,520), PA ($53,034), $51,547 (DC), and lowest in TX ($21,002), FL ($30,440), LA ($36,066). At multivariable linear regression, the strongest independent predictor of tuition was US News rank (β = -396.0, P= 0.05). CONCLUSIONS:US medical school tuition is highly variable by over a 10:1 ratio. Tuition is greater in higher ranked, longer established schools, in more densely populated regions. Objective data regarding medical education quality may be warranted to assess whether higher tuition in schools with higher US News and NIH rankings is justified.
PMID: 31303440
ISSN: 1535-6302
CID: 3977562
Journal of the American College of Radiology : JACR. 2018:15(2):243-249.DOI: 10.1016/j.jacr.2017.08.028
Historic Physician Quality and Reporting System Reporting by Radiologists: A Wake-up Call to Avoid Penalties Under the Medicare Access and CHIP Reauthorization Act (MACRA)
PURPOSE: The Medicare Access and CHIP Reauthorization Act (MACRA) Quality performance category is the successor to the Physician Quality and Reporting System (PQRS) program and now contributes to physicians' income adjustments based upon performance rates calculated for a minimum of six measures. We assess radiologists' frequency of reporting PQRS measures as a marker of preparedness for MACRA. METHODS: Medicare-participating radiologists were randomly searched through the Physician Compare website until identifying 1,000 radiologists who reported at least one PQRS measure. Associations were explored between the number of reported measures and radiologist characteristics. RESULTS: For PQRS-reporting radiologists, the number of reported PQRS measures was 1 (25.2%), 2 (27.3%), 3 (18.2%), 4 (19.3%), 5 (8.3%), and 6 (1.7%). The most commonly reported measures were "documenting radiation exposure time for procedures using fluoroscopy" (64.3%) and "accurate measurement of carotid artery narrowing" (56.8%). Reporting at least two measures was significantly (P < .001) more likely for nonacademic (77.3%) versus academic (44.9%) radiologists, generalists (82.7%) versus subspecialists (59.1%), and radiologists in smaller (/=100 members) (39.7%) practices. Reporting six measures was significantly (P < .05) more likely for generalists (2.6%) versus subspecialists (0.4%). CONCLUSION: Most PQRS-reporting radiologists reported only one or two measures, well below MACRA's requirement of six. Radiologists continuing such reporting levels will likely be disadvantaged in terms of potential payment adjustments under MACRA. Lower reporting rates for academic and subspecialized radiologists, as well as those in larger practices, may relate to such radiologists' reliance on their hospitals or networks for PQRS reporting. Qualified clinical data registries should be embraced to facilitate more robust measure reporting.
PMID: 29107575
ISSN: 1558-349x
CID: 2773202
Impact of patient questionnaires on completeness of clinical information and identification of causes of pain during outpatient abdominopelvic CT interpretation
PURPOSE: To evaluate the impact of questionnaires completed by patients at the time of abdominopelvic CT performed for abdominal pain on the completeness of clinical information and the identification of potential causes of pain, compared with order requisitions alone. METHODS: 100 outpatient CT examinations performed for the evaluation of abdominal pain were retrospectively reviewed. The specificity of the location of pain was compared between the order requisition and patient questionnaire. An abdominal imaging fellow (Reader 1) and abdominal radiologist (Reader 2) reviewed the examinations independently in two sessions 6 weeks apart (one with only the order requisition and one also with the questionnaire). Readers recorded identified causes of pain and rated their confidence in interpretation (1-5 scale; least to greatest confidence). RESULTS: In 30% of patients, the questionnaire provided a more specific location for pain. Among these, the pain was localized to a specific quadrant in 40%. With having access to the questionnaire, both readers identified additional causes for pain not identified in session 1 (Reader 1, 8.6% [7/81]; Reader 2 5.3% [4/75]). Additional identified causes of pain included diverticulitis, cystitis, peritoneal implants, epiploic appendagitis, osseous metastatic disease, umbilical hernia, gastritis, and SMA syndrome. Confidence in interpretation was significantly greater using the questionnaire for both readers (Reader 1: 4.8 +/- 0.6 vs. 4.0 +/- 0.5; Reader 2: 4.9 +/- 0.3 vs. 4.7 +/- 0.5, p < 0.001). CONCLUSION: Patient questionnaires provide additional relevant clinical history, increased diagnostic yield, and improve radiologists' confidence. Radiology practices are encouraged to implement questionnaires and make these readily available to radiologists at the time of interpretation.
PMID: 28647766
ISSN: 2366-0058
CID: 2614502
Refractory Ulcerated Necrobiosis Lipoidica: Closure of a Difficult Wound with Topical Tacrolimus
OBJECTIVE: To report a case of refractory ulcerated necrobiosis lipoidica (NL) with significant response to treatment with topical tacrolimus. SUBJECT: A 55-year-old woman without diabetes and with a previous history of NL presented to the Helen L. and Martin S. Kimmel Hyperbaric and Advanced Wound Healing Center of NYU Langone Medical Center, New York, with bilateral lower-leg ulcerations resistant to wound healing techniques at other institutions. MATERIALS AND METHODS: Repeat biopsy performed at the author's institution confirmed the diagnosis of NL. Initial therapy was based on reports of other successful treatment methods, which included collagen wound grafts and collagen-based dressings coupled with compression. These methods initially showed promising results; however, the wounds reulcerated, and any gains in wound healing were lost. Alternative options were initiated, including topical clobetasol and narrowband ultraviolet B; however, no significant improvement was observed. The patient's lower-extremity wounds began to deteriorate. The patient also refused systemic therapy. Treatment was changed to topical 0.1% tacrolimus ointment and was applied daily for 10 months with multilayer compression wraps. RESULTS: Both lower-extremity ulcerations began to show significant improvement, with the ulcers progressing toward closure except for 1 very small area on the left lower extremity. CONCLUSIONS: Topical tacrolimus seems to be an effective treatment option for patients with refractory chronic ulcerated NL who do not want systemic oral therapy. The authors found that successful wound closure may require a multimodal approach, which promotes wound healing, but also concurrently addresses the underlying disease process.
PMID: 28914682
ISSN: 1538-8654
CID: 2701322
Academic Radiologist Subspecialty Identification Using a Novel Claims-Based Classification System
OBJECTIVE: The objective of the present study is to assess the feasibility of a novel claims-based classification system for payer identification of academic radiologist subspecialties. MATERIALS AND METHODS: Using a categorization scheme based on the Neiman Imaging Types of Service (NITOS) system, we mapped the Medicare Part B services billed by all radiologists from 2012 to 2014, assigning them to the following subspecialty categories: abdominal imaging, breast imaging, cardiothoracic imaging, musculoskeletal imaging, nuclear medicine, interventional radiology, and neuroradiology. The percentage of subspecialty work relative value units (RVUs) to total billed work RVUs was calculated for each radiologist nationwide. For radiologists at the top 20 academic departments funded by the National Institutes of Health, those percentages were compared with subspecialties designated on faculty websites. NITOS-based subspecialty assignments were also compared with the only radiologist subspecialty classifications currently recognized by Medicare (i.e., nuclear medicine and interventional radiology). RESULTS: Of 1012 academic radiologists studied, the median percentage of Medicare-billed NITOS-based subspecialty work RVUs matching the subspecialty designated on radiologists' own websites ranged from 71.3% (for nuclear medicine) to 98.9% (for neuroradiology). A NITOS-based work RVU threshold of 50% correctly classified 89.8% of radiologists (5.9% were not mapped to any subspecialty; subspecialty error rate, 4.2%). In contrast, existing Medicare provider codes identified only 46.7% of nuclear medicine physicians and 39.4% of interventional radiologists. CONCLUSION: Using a framework based on a recently established imaging health services research tool that maps service codes based on imaging modality and body region, Medicare claims data can be used to consistently identify academic radiologists by subspecialty in a manner not possible with the use of existing Medicare physician specialty identifiers. This method may facilitate more appropriate performance metrics for subspecialty academic physicians under emerging value-based payment models.
PMID: 28301213
ISSN: 1546-3141
CID: 2490072
How Satisfied Are Patients With Their Radiologists? Assessment Using a National Patient Ratings Website
OBJECTIVE: The purpose of this study is to assess features of patient satisfaction scores for U.S. radiologists using a popular physician rating website. MATERIALS AND METHODS: Patient reviews were retrieved from the website RateMDs for all listed radiologists in all 297 U.S. cities with population 100,000 or greater. Reviews included rating scores of 1-5 (5 = highest) in four categories (staff, punctuality, knowledge, and helpfulness). Additional physician information was obtained from Medicare files. Common words in patient free-text comments were assessed. Statistical analyses were performed. RESULTS: We identified 1891 patient reviews for 1259 radiologists. In all four categories, the most common score was 5 for excellent (62.7-74.3%), and the second most common score was 1 for terrible (13.5-20.4%); scores of 2-4 were far less frequent (1.9-11.6%). Scores for all four categories highly correlated with one another (r = 0.781-0.951). Radiologists in the Northeast scored significantly lower (p < 0.001) than those elsewhere for both staff and punctuality. Radiologists attending a designated top 50 medical school showed nonsignificant trends toward lower scores for helpfulness (p = 0.073) and knowledge (p = 0.062). The most common words in free-text comments for positive reviews were "caring," "knowledgeable," and "professional." For negative reviews, "rude," "pain," and "unprofessional" were most common. CONCLUSION: Overall, most radiologists rated online by their patients score well, but reviews tended to be either strongly positive or negative. Scores across various categories are highly correlated, suggesting that there is a halo effect. Radiologists should recognize the effect of both facility- and radiologist-related factors in influencing patients' overall perceptions.
PMID: 28199131
ISSN: 1546-3141
CID: 2449202
Associations Between Academic Rank and Advanced Bibliometric Indices Among United States Academic Radiologists
RATIONALE AND OBJECTIVES: This study aimed to evaluate associations between traditional and advanced bibliometric indices with academic rank for radiologists in the United States. METHODS: Faculty web pages were searched to classify 538 members of the Association of University Radiologists as assistant (n = 212), associate (n = 128), or full (n = 198) professors. Radiologists' publication and citation records were extracted from Scopus to compute the following indices: publication count, citation count, h-index, i-10 index, hc-index, m-quotient, e-index, and g-index. Analysis of variance, multivariable logistic regression, and receiver operating characteristic curve analysis were performed. RESULTS: All indices were significantly different among the three groups (P
PMID: 27692589
ISSN: 1878-4046
CID: 2273822
Use of a Machine-learning Method for Predicting Highly Cited Articles Within General Radiology Journals
RATIONALE AND OBJECTIVES: This study aimed to assess the performance of a text classification machine-learning model in predicting highly cited articles within the recent radiological literature and to identify the model's most influential article features. MATERIALS AND METHODS: We downloaded from PubMed the title, abstract, and medical subject heading terms for 10,065 articles published in 25 general radiology journals in 2012 and 2013. Three machine-learning models were applied to predict the top 10% of included articles in terms of the number of citations to the article in 2014 (reflecting the 2-year time window in conventional impact factor calculations). The model having the highest area under the curve was selected to derive a list of article features (words) predicting high citation volume, which was iteratively reduced to identify the smallest possible core feature list maintaining predictive power. Overall themes were qualitatively assigned to the core features. RESULTS: The regularized logistic regression (Bayesian binary regression) model had highest performance, achieving an area under the curve of 0.814 in predicting articles in the top 10% of citation volume. We reduced the initial 14,083 features to 210 features that maintain predictivity. These features corresponded with topics relating to various imaging techniques (eg, diffusion-weighted magnetic resonance imaging, hyperpolarized magnetic resonance imaging, dual-energy computed tomography, computed tomography reconstruction algorithms, tomosynthesis, elastography, and computer-aided diagnosis), particular pathologies (prostate cancer; thyroid nodules; hepatic adenoma, hepatocellular carcinoma, non-alcoholic fatty liver disease), and other topics (radiation dose, electroporation, education, general oncology, gadolinium, statistics). CONCLUSIONS: Machine learning can be successfully applied to create specific feature-based models for predicting articles likely to achieve high influence within the radiological literature.
PMID: 27692588
ISSN: 1878-4046
CID: 2273812
Interobserver Reproducibility of the PI-RADS Version 2 Lexicon: A Multicenter Study of Six Experienced Prostate Radiologists
Purpose To determine the interobserver reproducibility of the Prostate Imaging Reporting and Data System (PI-RADS) version 2 lexicon. Materials and Methods This retrospective HIPAA-compliant study was institutional review board-approved. Six radiologists from six separate institutions, all experienced in prostate magnetic resonance (MR) imaging, assessed prostate MR imaging examinations performed at a single center by using the PI-RADS lexicon. Readers were provided screen captures that denoted the location of one specific lesion per case. Analysis entailed two sessions (40 and 80 examinations per session) and an intersession training period for individualized feedback and group discussion. Percent agreement (fraction of pairwise reader combinations with concordant readings) was compared between sessions. kappa coefficients were computed. Results No substantial difference in interobserver agreement was observed between sessions, and the sessions were subsequently pooled. Agreement for PI-RADS score of 4 or greater was 0.593 in peripheral zone (PZ) and 0.509 in transition zone (TZ). In PZ, reproducibility was moderate to substantial for features related to diffusion-weighted imaging (kappa = 0.535-0.619); fair to moderate for features related to dynamic contrast material-enhanced (DCE) imaging (kappa = 0.266-0.439); and fair for definite extraprostatic extension on T2-weighted images (kappa = 0.289). In TZ, reproducibility for features related to lesion texture and margins on T2-weighted images ranged from 0.136 (moderately hypointense) to 0.529 (encapsulation). Among 63 lesions that underwent targeted biopsy, classification as PI-RADS score of 4 or greater by a majority of readers yielded tumor with a Gleason score of 3+4 or greater in 45.9% (17 of 37), without missing any tumor with a Gleason score of 3+4 or greater. Conclusion Experienced radiologists achieved moderate reproducibility for PI-RADS version 2, and neither required nor benefitted from a training session. Agreement tended to be better in PZ than TZ, although was weak for DCE in PZ. The findings may help guide future PI-RADS lexicon updates. (c) RSNA, 2016 Online supplemental material is available for this article.
PMCID:5006735
PMID: 27035179
ISSN: 1527-1315
CID: 2059362
Instructional Vignettes in Publication and Journalism Ethics in Radiology Research:: Assessment via a Survey of Radiology Trainees
RATIONALE AND OBJECTIVES: The aim of the present study was to assess the potential usefulness of written instructional vignettes relating to publication and journalism ethics in radiology via a survey of radiology trainees. MATERIALS AND METHODS: A literature review was conducted to guide the development of vignettes, each describing a scenario relating to an ethical issue in research and publication, with subsequent commentary on the underlying ethical issue and potential approaches to its handling. Radiology trainees at a single institution were surveyed regarding the vignettes' perceived usefulness. RESULTS: A total of 21 vignettes were prepared, addressing institutional review board and human subjects protection, authorship issues, usage of previous work, manuscript review, and other miscellaneous topics. Of the solicited trainees, 24.7% (16/65) completed the survey. On average among the vignettes, 94.0% of the participants found the vignette helpful; 19.9 received prior formal instruction on the issue during medical training; 40.0% received prior informal guidance from a research mentor; and 42.0% indicated that the issue had arisen in their own or a peer's prior research experience. The most common previously experienced specific issue was authorship order (93.8%). Free-text responses were largely favorable regarding the value of the vignettes, although also indicated numerous challenges in properly handling the ethical issues: impact of hierarchy, pressure to publish, internal politics, reluctance to conduct sensitive conversations with colleagues, and variability in journal and professional society policies. CONCLUSION: Radiology trainees overall found the vignettes helpful, addressing commonly encountered topics for which formal and informal guidance were otherwise lacking. The vignettes are publicly available through the Association of University Radiologists (AUR) website and may foster greater insights by investigators into ethical aspects of the publication and journalism process, thus contributing to higher quality radiology research.
PMID: 27052523
ISSN: 1878-4046
CID: 2066182
