Financial Ratios in Diagnostic Radiology Practices: Variability and Trends
Bibliographic record
Abstract
PURPOSE: To evaluate variation in financial ratios for radiology practices nationwide and trends in these ratios and in payments. MATERIALS AND METHODS: In 1999, the American College of Radiology surveyed radiology practices by mail. The final response rate was 66%. Weighting was used to make responses representative of all radiology practices in the United States. Self-reported financial ratios (payments, charges, accounts receivable turnover) were analyzed; 449 responses had usable data on these ratios. Comparison with results of a similar 1992 survey and combined analysis with Medicare data on billed charges provided information on trends. RESULTS: All measures of payment collections declined sharply from 1992 to 1999, with the gross collections rate (revenues as percentage of billed charges) decreasing from 71% to 55%. Average payment for a typical radiology service decreased approximately 4% in dollar terms or approximately 19% in inflation-adjusted terms. In 1999, nonmetropolitan practices appeared to fare better than others. Among insurers, Medicaid stood out as a low and slow payer, but neither managed care nor Medicare had a consistent effect on financial ratios. The gross collections rate varied substantially across geographic areas, as did, in an inverse pattern, the level of billed charges. One-quarter of practices had accounts receivable equal to 90 or more days of billings. CONCLUSION: The opposing geographic pattern of billed charges and gross collection rate suggests that geographic variation in the latter is driven more by variation in billed charges than by variation in payment levels. Radiologists saw a substantial decrease in the real (inflation-adjusted) value of payment per service during the 1990s. The large fraction of practices with accounts receivable of 90 or more days of billings-a level considered potentially imprudent by financial management advisors-suggests that many practices should improve financial management and that state prompt-payment laws have not had a substantial positive effect.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".