Budget Impact Analysis: Digital Workflow Significantly Reduces Costs of Implant Supported Overdentures (<scp>IODs</scp>)
Bibliographic record
Abstract
BACKGROUND: For edentulism, an implant supported removable complete overdenture (IOD) is an attractive solution to restore patients' chewing capacity, aesthetics, and self‐esteem, however, treatment is expensive and time consuming. PURPOSE/AIM: To estimate the decline in costs for digitally designed and CAD/CAM fabricated IODs (3D‐IODs) compared to conventionally fabricated IODs (C‐IODs) at comparable general health related quality of life (GHRQoL). MATERIALS AND METHOD: A randomized crossover study enrolled 36 fully edentulous patients, in whom six maxillary implants were placed together with two mandibular implants, if not already present. At the start of the study, a set of C‐IODs and 3D‐IODs was fabricated for each patient. All patients wore each IOD‐type for 1 year: first the 3D‐IOD and the second year a C‐IOD, or vice versa. At all three‐time points patients general QoL was assessed using the EQ‐5D‐5L questionnaire as well as the SF‐36 from which the SF‐6D was obtained, to research the anticipation of no significant difference. To enable cost consequence analysis (CCA), both costs made within healthcare and patient costs were assessed. Subsequently, a budget impact analysis (BIA) was performed to demonstrate the potential savings. RESULTS: No differences in general GHRQoL were seen between C‐IOD (M = 0.840, SD = 0.177) and 3D‐IOD (M = 0.837, SD = 0.156) (paired t‐test (N = 31): p = 0.880). With respect to the total costs for a complete IOD, however, the digital approach showed a reduction in initial total costs of 14.2% (€4700.33 vs. €4030.61: p < 0,001), in treatment time of 41.1% (309 vs. 182 min: p < 0.001), and in number of treatment sessions of 47.1% (5.68 vs. 3.0: p < 0.001). For repairs for an IOD in both the upper and lower jaw, the C‐IOD and 3D‐IOD scored similar for treatment time as well as additional costs. CONCLUSION: Implementing a 3D workflow in the production of IOD's supplies patients with a high‐quality 3D‐IOD at lower costs. TRIAL REGISTRATION: NL‐OMON44248 https://onderzoekmetmensen.nl/en/trial/44248.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".