Short‐ and long‐term cost and utilization of health care resources in Parkinson's disease in the UK
Bibliographic record
Abstract
BACKGROUND: There is currently no robust long-term data on costs of treating patients with Parkinson's disease. The objective of this study was to report levels of health care utilization and associated costs in the 10 years after diagnosis among PD patients in the United Kingdom. METHODS: We undertook a retrospective population-based cohort study using linked data from the UK Clinical Practice Research Datalink and Hospital Episode Statistics databases. Total health care costs of PD patients were compared with those of a control group of patients without PD selected using 1:1 propensity score matching based on age, sex, and comorbidity. RESULTS: Between 1994 and 2013, 7271 PD patients who met study inclusion criteria were identified in linked Clinical Practice Research Datalink-Hospital Episode Statistics; 7060 were matched with controls. The mean annual health care cost difference (at 2013 costs) between PD patients and controls was £2471 (US$3716) per patient in the first year postdiagnosis (P < 0.001), increasing to £4004 (US$6021) per patient (P < 0.001) 10 years following diagnosis because of higher levels of use across all categories of health care utilization. Costs in patients with markers of advanced PD (ie, presence of levodopa-equivalent daily dose > 1100 mg, dyskinesias, falls, dementia, psychosis, hospital admission primarily due to PD, or nursing home placement) were on average higher by £1069 (US$1608) per patient than those with PD without these markers. CONCLUSIONS: This study provides comprehensive estimates of health care costs in PD patients based on routinely collected data. Health care costs attributable to PD increase in the year following diagnosis and are higher for patients with indicators of advanced disease. © 2018 International Parkinson and Movement Disorder Society.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".