An audit of imaging test utilization for the management of lymphoma in an oncology hospital: implications for resource planning?
Bibliographic record
Abstract
The purpose of this study was to assist with resource planning by examining the pattern of physician utilization of imaging procedures for lymphoma patients in a dedicated oncology hospital. The proportion of imaging tests ordered for routine follow up with no specific clinical indication was quantified, with specific attention to CT scans. A 3-month audit was performed. The reasons for ordering all imaging procedures (X-rays, CT scans, ultrasound, nuclear scan and MRI) were determined through a retrospective chart review. 411 lymphoma patients had 686 assessments (sets of imaging tests) and 981 procedures (individual imaging tests). Most procedures were CT scans (52%) and chest radiographs (30%). The most common reasons for ordering imaging were assessing response (23%), and investigating new symptoms (19%). Routine follow up constituted 21% of the assessments (142/686), and of these, 82% were chest radiographs (116/142), while 24% (34/142) were CT scans. With analysis restricted to CT scans (296 assessments in 248 patients), the most common reason for ordering CT scans were response evaluation (40%), and suspicion of recurrence and/or new symptom (23%). Follow-up CT scans done with no clinical indication comprised 8% (25/296) of all CT assessments. Staging CT scans were under-represented at 6% of all assessments. Imaging with CT scans for follow up of asymptomatic patients is infrequent. However, scans done for staging new lymphoma patients were unexpectedly low in frequency, due to scans done elsewhere prior to referral. This analysis uncovered utilization patterns, helped resource planning and provided data to reduce unnecessary imaging procedures.
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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 | 0.005 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".