Developing Management Information from an Administrative Database of Dental Services: Identifying Factors that Influence Costs
Bibliographic record
Abstract
OBJECTIVE: We describe service patterns and compare changes in program expenditures with the Consumer Price Index over eight years in a dental program with a controlled-fee schedule offered to Canadian First Nations and Inuit people. METHODS: We obtained the computerized records of dental services for the period from 1994 to 2001. Each record identified the date and type of service, region and type of provider, age of the client and encrypted identifying information on clients, bands, and providers. We classified the individual services into related types (diagnostic, preventive, etc.). We aggregated the records by client and developed indices for the numbers of clients, mean numbers of services per client, cost per service, and prices. FINDINGS: Over the 8 years, 16.0 million procedures, totaling 811.8 million dollars, were provided to 538,034 different individuals, approximately 76% of the eligible population. Restorative procedures accounted for 36% of all expenditures followed by diagnostic (12.7%), preventive (12.2%), and orthodontic (8.9%) services. For much of the period, increases in program expenditures were exceeded by increases in the Consumer Price Index. This was consistent with fewer services per client, a less expensive mix of services, and relatively flat prices. However, in 2000 and 2001 higher prices and more clients resulted in increasing expenditures. CONCLUSIONS: Program expenditures were influenced by different factors over the study period. In the final two years, increasing expenditures were driven by price increases and increasing numbers of clients, but not by increasing numbers of services per client, nor a 'richer' mix of services.
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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 | 0.006 | 0.049 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.009 | 0.013 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".