Retrospective database analysis on the demographics and resource utilization of patients with Parkinson’s disease in Quebec, Canada
Bibliographic record
Abstract
Introduction: Parkinson's disease (PD) is the most prevalent neurodegenerative movement disorder. Despite its recognized significance, there remains a paucity of recent studies reporting treatment utilization and the economic impact of PD in a real-world setting, especially in Canada. This study aimed to analyze real-world treatment patterns and health care resource utilization (HCRU) of patients with PD in Quebec, Canada. Methods: This was a retrospective observational study using data between 2010-2019 from the Régie de l'assurance maladie du Québec (RAMQ) databases. Patients with PD were compared to age- and sex-matched controls. Treatment adherence and persistence were measured over 24 months. All-cause and PD-related HCRU and costs were characterized on an annual basis. Results: Overall, 303 PD patients and 909 age- and sex-matched controls were selected. Adherence rates were high (≥85 %) among all drug classes, but lower with dopamine agonists. Persistence to PD treatment declined over time, with nearly 50 % discontinuation rates at 24 months in all PD drug classes, except the levodopa class (discontinuation rate: 20.4 %). PD patients had a significantly higher total costs per year than the matched control group ($17,405 vs. $6,431), mainly driven by higher inpatient costs. Conclusion: Many pharmacological options exist for PD patients and, though patients are adherent while on therapy, treatment discontinuation rates are high. This suggests potential long-term challenges in PD management, especially since PD continues to place a substantial burden on the health care system. This study underscores the need for enhanced therapeutic strategies, particularly for patients inadequately controlled with standard therapies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".