Emergency Room Visit Prevention for Older Patients with Parkinsonism in a Geriatric Clinic
Bibliographic record
Abstract
BACKGROUND: Older persons with parkinsonism (PWP) are at high risk for hospitalization and adverse outcomes. Few effective strategies exist to prevent Emergency Department (ED) visits and hospitalization. The interdisciplinary Geriatrics Clinic for Parkinson's ("our clinic") was founded to address the complexity of parkinsonism in older patients, supported by a pharmacist-led telephone intervention (TI) service. Our primary objective was to study whether TI could avert ED visits in older PWP. METHODS: Using a prospective, observational cohort, we collected data from all calls in 2016, including who initiated and reasons for the calls, patient demographics, number of comorbidities and medications, diagnoses, duration of disease, and intervention provided. Calls with intention to visit ED were classified as "crisis calls". Outcome of whether patients visited ED was collected within 1 week, and user satisfaction by anonymous survey within 3 weeks. RESULTS: We received 337 calls concerning 114 patients, of which 82 (24%) were "crisis calls". Eighty-one percent of calls were initiated by caregivers. Ninety-three percent of "crisis calls" resolved without ED visit after TI. The main reasons for "crisis calls" were non-motor symptoms (NMS) (39%), adverse drug effects (ADE) (29%), and motor symptoms (18%). Ninety-seven percent of callers were satisfied with the TI. CONCLUSION: Pharmacist-led TI in a Geriatrics Clinic for Parkinson's was effective in preventing ED visits in a population of older PWP, with high user satisfaction. Most calls were initiated by caregivers. Main reasons for crisis calls were NMS and ADE. These factors should be considered in care planning for older PWP.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".