Cost Analysis of Multiplex PCR Testing for Diagnosing Respiratory Virus Infections
Bibliographic record
Abstract
We performed a cost analysis study using decision tree modeling to determine whether the use of multiplex PCR testing for respiratory viruses (xTAG RVP test) is a more or less costly strategy than the status quo testing methods used for the diagnosis of respiratory virus infections in pediatric patients. The decision tree model was constructed by using four testing strategies for respiratory virus detection, viz., direct fluorescent-antibody staining (DFA) alone, DFA plus shell vial culture (SVC), the xTAG RVP test alone, or DFA plus the xTAG RVP test. A review of the charts of 661 pediatric patients was used to determine the length of hospital stay, the number of days in isolation, antibiotic usage, and all other medical procedures performed. The cost of hospitalization by diagnostic status was determined on the basis of the average cost per patient and the number of patients in each arm of the decision tree. The cost per case was the highest for DFA plus SVC at $3,914 (in Canadian dollars), and the lowest was for the xTAG RVP test alone at $3,623, while the costs of DFA alone ($3,911) and DFA plus RVP ($3,849) were intermediate. When all four diagnostic strategies were compared, the least costly strategy was the xTAG RVP test alone when the prevalence of infection was 11% or higher and DFA alone when the prevalence was under 11%. These data indicate a savings of $291 per case investigated if the strategy of using the xTAG RVP test alone was used to replace the status quo test of DFA plus SVC, resulting in a savings of $529,620 per year in direct costs for the four Hamilton, Ontario, Canada, hospitals on the basis of the testing of specimens from 1,820 pediatric inpatients. We conclude that the use of the xTAG RVP test is the least costly strategy for the diagnosis of respiratory virus infections in children and would generate a significant savings for hospitals.
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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 | 0.008 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".