Shift Volume Directly Impacts Neuroradiology Error Rate at a Large Academic Medical Center: The Case for Volume Limits.

BACKGROUND AND PURPOSE: Unlike in Europe and Japan, guidelines or recommendations from specialized radiological societies on workflow management and adaptive intervention to reduce error rates are currently lacking in the United States. This study of neuroradiologic reads at a large US academic medical center, which may hopefully contribute to this discussion, found a direct relationship between error rate and shift volume. MATERIALS AND METHODS: CT and MR imaging reports from our institution's Neuroradiology Quality Assurance database (years 2014-2020) were searched for attending physician errors. Data were collected on shift volume specific error rates per 1000 interpreted studies and RADPEER scores. Optimal cutoff points for 2, 3 and 4 groups of shift volumes were computed along with subgroups' error rates. RESULTS: A total of 643 errors were found, 91.7% of which were clinically significant (RADPEER 2b, 3b). The overall error rate (errors/1000 examinations) was 2.36. The best single shift volume cutoff point generated 2 groups: ≤ 26 studies (error rate 1.59) and > 26 studies (2.58; OR: 1.63, P < .001). The best 2 shift volume cutoff points generated 3 shift volume groups: ≤ 19 (1.34), 20-28 (1.88; OR: 1.4, P = .1) and ≥ 29 (2.6; OR: 1.94, P < .001). The best 3 shift volume cutoff points generated 4 groups: ≤ 24 (1.59), 25-66 (2.44; OR: 1.54, P < .001), 67-90 (3.03; OR: 1.91, P < .001), and ≥ 91 (2.07; OR: 1.30, P = .25). The group with shift volume ≥ 91 had a limited sample size. CONCLUSIONS: Lower shift volumes yielded significantly lower error rates. The lowest error rates were observed with shift volumes that were limited to 19-26 studies. Error rates at shift volumes between 67-90 studies were 226% higher, compared with the error rate at shift volumes of ≤ 19 studies.

CT predictors of sub-centimeter occult lymph node metastases in oral cavity squamous cell carcinoma: A case-control study.

BACKGROUND: For patients with oral cavity squamous cell carcinoma (OCSCC) without evidence of nodal metastasis (cN0) on pre-operative evaluation, there are no clear guidelines who should undergo elective neck dissection (END) versus clinical surveillance. OBJECTIVE: To identify CT imaging characteristics of sub-centimeter lymph nodes that would help predict the likelihood of nodal metastases on pathology. METHODS: Retrospective review of cN0 OCSCC patients at a tertiary academic medical center was performed. Inclusion criteria included elective neck dissection, pre-operative CT imaging and presence of metastatic disease within lymph nodes. Control group consisted of patients without nodal metastases on pathology. CT features that were evaluated included asymmetric size, disrupted fatty hilum, asymmetric number, presence of cortical nodule, cortical nodule size, and round/oval shape. We evaluated the associations between CT LN features and the presence of metastases using multi-level mixed-effects logistic regression models. Model evaluation was performed using 5-fold cross-validation. The positive predictive value (PPV) and negative predictive value (NPV) were calculated. RESULTS: 26 patients in each study and control groups were included. Three-level mixed-effects logistic regression models indicated round/oval shape (OR = 1.39, p = .01), asymmetric number (OR = 7.20, p = .005), and disrupted fatty hilum (OR = 3.31, p = .04) to be independently predictive in a 3-variable model with sensitivity = 38.0%, specificity = 92.0%, and PPV = 93.8%. CONCLUSIONS: In cN0 OCSCC patients undergoing END, round/oval shape, asymmetric number, and disrupted fatty hilum of lymph nodes on pre-operative CT imaging are novel and highly predictive of occult nodal disease.

Factors Associated With Neuroradiologic Diagnostic Errors at a Large Tertiary-Care Academic Medical Center: A Case-Control Study.

BACKGROUND. Numerous studies have explored factors associated with diagnostic errors in neuroradiology; however, large-scale multivariable analyses are lacking. OBJECTIVE. The purpose of this study was to evaluate associations of interpretation time, shift volume, care setting, day of week, and trainee participation with diagnostic errors by neuroradiologists at a large academic medical center. METHODS. This retrospective case-control study using a large tertiary-care academic medical center's neuroradiology quality assurance database evaluated CT and MRI examinations for which neuroradiologists had assigned RADPEER scores. The database was searched from January 2014 through March 2020 for examinations without (RADPEER score of 1) or with (RADPEER scores of 2a, 2b, 3a, 3b, or 4) diagnostic error. For each examination with error, two examinations without error were randomly selected (unless only one examination could be identified) and matched by interpreting radiologist and examination type to form case and control groups. Marginal mixed-effects logistic regression models were used to assess associations of diagnostic error with interpretation time (number of minutes since the immediately preceding report's completion), shift volume (number of examinations interpreted during the shift), emergency/inpatient setting, weekend interpretation, and trainee participation in interpretation. RESULTS. The case group included 564 examinations in 564 patients (mean age, 50.0 ± 25.0 [SD] years; 309 men, 255 women); the control group included 1019 examinations in 1019 patients (mean age, 52.5 ± 23.2 years; 540 men, 479 women). In the case versus control group, mean interpretation time was 16.3 ± 17.2 [SD] minutes versus 14.8 ± 16.7 minutes; mean shift volume was 50.0 ± 22.1 [SD] examinations versus 45.4 ± 22.9 examinations. In univariable models, diagnostic error was associated with shift volume (OR = 1.22, p < .001) and weekend interpretation (OR = 1.60, p < .001) but not interpretation time, emergency/inpatient setting, or trainee participation (p > .05). However, in multivariable models, diagnostic error was independently associated with interpretation time (OR = 1.18, p = .003), shift volume (OR = 1.27, p < .001), and weekend interpretation (OR = 1.69, p = .02). In subanalysis, diagnostic error showed independent associations on weekdays with interpretation time (OR = 1.18, p = .003) and shift volume (OR = 1.27, p < .001); such associations were not observed on weekends (interpretation time: p = .62; shift volume: p = .58). CONCLUSION. Diagnostic errors in neuroradiology were associated with longer interpretation times, higher shift volumes, and weekend interpretation. CLINICAL IMPACT. These findings should be considered when designing work-flow-related interventions seeking to reduce neuroradiology interpretation errors.

Impact of Shift Volume on Neuroradiology Diagnostic Errors at a Large Tertiary Academic Center.

BACKGROUND AND PURPOSE: Medical errors can result in significant morbidity and mortality. The goal of our study is to evaluate correlation between shift volume and errors made by attending neuroradiologists at an academic medical center, using a large data set. MATERIALS AND METHODS: CT and MRI reports from our Neuroradiology Quality Assurance database (years 2014 - 2020) were searched for attending physician errors. Data were collected on shift volume, category of missed findings, error type, interpretation setting, exam type, clinical significance. RESULTS: 654 reports contained diagnostic error. There was a significant difference between mean volume of interpreted studies on shifts when an error was made compared with shifts in which no error was documented (46.58 (SD=22.37) vs 34.09 (SD=18.60), p<0.00001); and between shifts when perceptual error was made compared with shifts when interpretive errors were made (49.50 (SD=21.9) vs 43.26 (SD=21.75), p=0.0094). 59.6% of errors occurred in the emergency/inpatient setting, 84% were perceptual and 91.1% clinically significant. Categorical distribution of errors was: vascular 25.8%, brain 23.4%, skull base 13.8%, spine 12.4%, head/neck 11.3%, fractures 10.2%, other 3.1%. Errors were detected most often on brain MRI (25.4%), head CT (18.7%), head/neck CTA (13.8%), spine MRI (13.7%). CONCLUSION: Errors were associated with higher volume shifts, were primarily perceptual and clinically significant. We need National guidelines establishing a range of what is a safe number of interpreted cross-sectional studies per day.

Pre-styloid parapharyngeal space masses-Tumor margins as a predictor of benign versus malignant histology on pre-operative CT or MRI.

PURPOSE: Evaluate the frequency of benign versus malignant masses within the prestyloid parapharyngeal space (PPS) and determine if tumor margins on preoperative cross-sectional imaging can predict malignancy status. MATERIALS AND METHODS: The electronic health record at UC Davis Medical Center was searched for PPS masses surgically resected between 2015 and 2021. Cases located centrally within the prestyloid PPS with confirmed histologic diagnosis were included and separated into either benign or malignant groups. Margins of the tumors were categorized as "well defined" or "infiltrative" on preoperative cross-sectional imaging. Statistical analysis was performed to evaluate relationships between malignancy status and tumor margins. RESULTS: A total of 31 cases met the inclusion criteria. Fourteen separate histologic diagnoses were observed. Benign cases comprised 77% (24/31) and the remaining 23% (7/31) were malignant. Pleomorphic adenoma was the most common overall diagnosis at 48% (15/31). Adenoid cystic carcinoma 6% (2/31) was the most common malignant diagnosis. Well-defined tumor margins were seen in 81% (25/31) of cases. A benign diagnosis was found in 96% (24/25) of the cases with well-defined margins. Infiltrative tumor margins were displayed in 19% (6/31) of cases, all were malignant. The sensitivity and specificity of infiltrative tumor margins for malignancy were 85.7% and 100%, respectively. The negative predictive value of infiltrative margins for malignancy was 96%. CONCLUSION: Infiltrative tumor margins on preoperative imaging demonstrate high specificity and negative predictive value for malignant histology in prestyloid PPS masses. Margins should therefore be considered when determining clinical management for newly diagnosed PPS tumors.