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Record W4404696349 · doi:10.1186/s12913-024-11952-7

Effectiveness of the community paramedicine at home (CP@home) program for frequent users of emergency medical services in Ontario: a randomized controlled trial

2024· article· en· W4404696349 on OpenAlexafffundabout
Gina Agarwal, Ricardo Angeles, Jasdeep Brar, Melissa Pirrie, Francine Marzanek, Brent McLeod, Lehana Thabane

Bibliographic record

VenueBMC Health Services Research · 2024
Typearticle
Languageen
FieldMedicine
TopicEmergency and Acute Care Studies
Canadian institutionsSt. Joseph’s Healthcare HamiltonImpactMcMaster University
FundersCanadian Institutes of Health Research
KeywordsMedicineRandomized controlled trialHealth informaticsNursing researchHealth administrationHealth services researchHouse callMedical homePublic healthNursing homesFamily medicineNursingMedical emergencyGerontologyPrimary careInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To evaluate the impact of the Community Paramedicine at Home (CP@home) program, a community paramedicine home-visit intervention, on reducing emergency medical services (EMS) calls among frequent users. DESIGN: A 6-month, open-label, pragmatic, randomized controlled trial with parallel intervention and control arms. An online automated platform (randomizer.org) was used to randomly allocate participants using a 1:1 allocation sequence. SETTING: In homes of frequent EMS users in four paramedic services and regions across Ontario, Canada. PARTICIPANTS: Eligible participants were frequent callers (≥ 3 EMS calls within six months and ≥ 1 EMS call within the previous month), or had ≥ 1 lift assist call within the previous month, or were referred by paramedics. INTERVENTION: Community paramedics conducted risk assessments, provided health education, referred appropriate resources, and reported to family physicians for up to three home visits. The control arm received usual care. PRIMARY OUTCOME MEASURE: EMS calls in 6 months during intervention. RESULTS: Two thousand two hundred eighty four eligible participants were randomly allocated to the intervention and control groups, with 265 participants lost to follow-up due to inability to retrieve participant records from EMS databases. There were 1025 intervention participants (52.7% female, mean age 69.65 years [standard deviation (SD) = 19.98]) and 994 control participants (52.0% female, mean age 69.78 years [SD = 19.09]). In the post-intervention intention-to-treat analysis (zero-inflated negative binomial regression), the EMS call rate was not significantly lower in the intervention group compared to the control group (incidence rate ratio [IRR] = 0.88, 95% confidence interval [CI]: 0.76, 1.01). In the subgroup analysis, the intervention had a significant effect in the lift assist caller subgroup (IRR = 0.73, 95% CI: 0.58, 0.92), but no significant effect among the frequent caller subgroup (IRR = 0.97, 95% CI: 0.82, 1.14). The sensitivity analyses found a similar association for the lift assist caller subgroup. There was a significant subgroup effect (p-value for interaction < 0.01). CONCLUSIONS: CP@home had a significant impact on reducing EMS calls for those with a lift assist call but not for the overall sample. This program filled a healthcare gap by shifting primary care delivery, which could reduce the disproportionate number of EMS calls, thus reducing healthcare costs. TRIAL REGISTRATION: Registered with ClinicalTrials.gov NCT02835989 on July 14, 2016.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.881
Threshold uncertainty score0.236

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0060.000

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.

Opus teacher head0.057
GPT teacher head0.452
Teacher spread0.395 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2024
Admission routes3
Has abstractyes

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