66HIGHER LEVELS OF APOMORPHINE AND ROTIGOTINE PRESCRIBING SPEND REDUCE THE TOTAL HEALTHCARE COSTS FOR PARKINSON'S PATIENTS
Bibliographic record
Abstract
Background Parkinson's affects around 100,000 patients in the UK with significant impact on quality of life and health and social care needs, economic burden is estimated at over £2 billion/year. It is a long term condition with onset in older age with median age of patients 78 years. Patients are initially treated with oral levodopa and/or dopamine agonist and other adjuncts that improve both the quality of life and reduce the patients need for health and social care. However over time other more resource intensive delivery methods may be needed including pumps, pens and patches, these are currently limited to the most severely affected patients (1% – 5%). Methods In Parkinson's diagnosis, severity, therapy and outcomes are not consistently measured or published. Using the annual 7,990 GP practice age profiles, primary care prescribing data and Hospital Episode Statistical data over 3 years 2011-12 to 2013-14, we investigated at GP practice level correlations between prescribing mix including Apomorphine injections and Rotigotine patches, against diagnosed Parkinson's patients need for secondary health care including admission, outpatient and accident & emergency.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".