Burden of Emergency Medical Services Usage by Dialysis Patients
Bibliographic record
Abstract
BACKGROUND: Patients receiving chronic dialysis often require emergent and inpatient care; however, only a minimal amount is known about their out-of-hospital/inter-hospital use of Emergency Medical Services (EMS). The purpose of this study was to describe the utilization of EMS in a cohort of dialysis patients. METHODS: We analyzed a cohort of adult (≥18 years) chronic dialysis patients within the Nova Scotia Health Authority Central Zone Renal Program who initiated chronic dialysis between January 1, 2009 and June 30, 2013 (last follow up July 1, 2015). Dialysis patient data was linked to regional EMS data. Requests for EMS, including encounter type, day of the week, and patient characteristics were described. RESULTS: The cohort consisted of 468 patients of whom 79% (N = 361) had an EMS encounter. There were a total of 8,774 EMS encounters for the entire cohort. Patients who had an EMS encounter tended to be older (64 ± 14 years), compared to those without an encounter (55 ± 16 years, P < 0.001) and also had a higher burden of comorbidity. Transfers (including those between facilities) accounted for 89% of all encounters (N = 7,826), followed by emergency department (ED) transports (N = 749, 9%). Overall, 79% of all non-transfers underwent transport to the ED. For patients receiving thrice weekly in-center hemodialysis, the highest EMS utilization for ED transport occurred on the first hemodialysis day after the long dialysis break (22%, P < 0.01). The lowest proportion of ED transports occurred on the day after hemodialysis day 3. CONCLUSION: Utilization of EMS services by dialysis patients is considerable, particularly for transfers. This highlights a potential area to be targeted for reducing resource utilization. Calls requiring transport to the ED occurred most often on Mondays and Tuesdays, the day after the long-dialysis break, and may represent a time of heightened risk for in-center hemodialysis patients.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.013 | 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".