Reader agreement studies.
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Data Interpretation, Statistical↗
Biomedical subjects
Philip E Crewson
Publications and source records attributed to Philip E Crewson.
Statistical literacy.
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Clinical Trials as Topic↗
Hypothesis testing II: means.
Whenever means are reported in the literature, they are likely accompanied by tests to determine statistical significance. The t test is a common method for statistical evaluation of the difference between two sample means. It provides information on whether the means from two samples are likely to be different in the two populations from which the data originated. Similarly, paired t tests are common when comparing means from the same set of patients before and after an intervention. Analysis of variance techniques are used when a comparison involves more than two means. Each method serves a particular purpose, has its own computational formula, and uses a different sampling distribution to determine statistical significance. In this article, the authors discuss the basis behind analysis of continuous data with use of paired and unpaired t tests, the Bonferroni correction, and multivariate analysis of variance for readers of the radiology literature.
Analysis of Variance↗
Does training in the Breast Imaging Reporting and Data System (BI-RADS) improve biopsy recommendations or feature analysis agreement with experienced breast imagers at mammography?
PURPOSE: To determine whether training in the Breast Imaging Reporting and Data System (BI-RADS) improves observer performance and agreement with the consensus of experienced breast imagers with regard to mammographic feature analysis and final assessment. MATERIALS AND METHODS: A test set of mammograms was developed, with 54 proven lesions consisting of 28 masses (nine [32%] malignancies) and 26 microcalcifications (10 [38%] malignancies). Three experienced breast imagers reviewed cases independently and by means of consensus. Twenty-three practicing mammogram-interpreting physicians reviewed mammograms before and after a day's lectures on BI-RADS. Observer performance before and after training was measured by means of agreement (kappa) with consensus description and assessments, rate of biopsy of malignant and benign lesions, and areas under receiver operating characteristic (ROC) curves. Performance was also measured for 11 participants 2-3 months after training. RESULTS: Improved agreement with consensus feature analysis was found for mass margins and/or asymmetries, with a pretraining generalized kappa value of 0.36 and a posttraining generalized kappa value of 0.41. Similar improvement was seen for description of calcification morphology (pretraining kappa value of 0.36 improving to 0.44 after training). No improvement was seen in describing calcification distribution. Final assessments were more consistent after training, with a pretraining kappa value of 0.31, as compared with 0.45 after training. The mean biopsy rate for malignant lesions improved from 73% (range, 53%-89%) before training to 88% (range, 74%-100%) after training, with minimal increase in mean biopsy rate of benign lesions (43% [range, 26%-60%] before to 51% [range, 31%-63%] after training), and no net change in area under the ROC curve, as compared with histopathologic findings. For the subset of participants with delayed follow-up, no significant decline in posttraining results was seen. CONCLUSION: BI-RADS training resulted in improved agreement with the consensus of experienced breast imagers for feature analysis and final assessment. It is important that trainees showed improved rates of recommending biopsy for malignant lesions. This effect was maintained over 2-3 months.
Biopsy↗
An introduction to biostatistics.
This introduction to biostatistics and measurement is the first in a series of articles designed to provide Radiology readers with a basic understanding of statistical concepts. Although most readers of the radiology literature know that application of study results to their practice requires an understanding of statistical issues, many may not be fully conversant with how to interpret statistics. The goal of this series is to enhance the ability of radiologists to evaluate the literature competently and critically, not make them into statisticians.
Biometry↗
Comparison of heel ultrasound and finger DXA to central DXA in the detection of osteoporosis. Implications for patient management.
The goal of the study was to investigate the potential discordance in patient management when a clinician assumes that a peripheral device is a diagnostic surrogate for central DXA in the detection and treatment of osteoporosis. Over a period of 2 mo, asymptomatic women seeking conventional central DXA evaluation for osteoporosis at a diagnostic imaging center were also evaluated with heel ultrasound and finger DXA peripheral imaging devices. T-Scores of -2.5 or less in screening examinations were used to evaluate the discordance between the two peripheral devices and central DXA in the identification of patients with osteoporosis. Higher T-score cutoffs (>-2.5) were also evaluated. Using central DXA as the standard for comparison, the sensitivity of heel ultrasound for screening cases was 0.34 and specificity was 0.92. For finger DXA, sensitivity was 0.23 and specificity was 0.92. Overall discordance between the peripheral devices and central DXA was 21% (heel) and 23% (finger). Heel ultrasound identified 7 out of every 22 osteoporotic patients diagnosed with central DXA. Finger DXA identified 5 out of every 22 osteoporotic patients. Using lower T-scores for the peripheral devices increased sensitivity but markedly increased discordance with DXA. The peripheral devices we studied cannot be considered equivalent surrogates for central DXA in the screening of asymptomatic women for osteoporosis.
Absorptiometry, Photon↗
Compliance with prompt payment legislation: the initial experiences of New Jersey radiologists.
OBJECTIVE: Prompt payment has emerged as a dominant issue in managed care reform, with 47 states passing laws or regulations requiring prompt remuneration for medical services. The New Jersey Prompt-Pay Act, effective on December 28, 1999, requires payment within 30 days of electronic submission and within 40 days for nonelectronic submission. This study was undertaken to assess compliance with the New Jersey Prompt-Pay Act for radiology claims submitted 1 and 5 months after implementation (7-11 months after passage of the statute). MATERIALS AND METHODS: A retrospective prompt payment analysis was undertaken of all claims submitted in February and June 2000 to six major payers by a common third-party billing company on behalf of 11 radiology practices of various sizes, settings, and locations in New Jersey. A total of 33,537 claims were assigned to one of six time periods on the basis of timeliness of payment: less than or equal to 30 days, 31-40 days, 41-50 days, 51-60 days, 61-90 days, and greater than 90 days or a separate unpaid category after 170 days had elapsed. A detailed analysis of 3156 claims from one practice was performed to estimate a clean claims submission rate. RESULTS: The overall percentage of claims paid within 40 days was 70%. After 170 days, the overall percentage of paid claims was 93%. The annualized interest lost on delayed payments was $23,939 for the practice analyzed. CONCLUSION: Prompt payment for radiology services remains an elusive goal in New Jersey, despite passage and implementation of prompt payment legislation.
Guideline Adherence↗