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Record W2731872536 · doi:10.1093/geroni/igx004.201

ESTABLISHING THE EFFECTIVENESS OF THE INDEPENDENCE AT HOME COMMUNITY PARAMEDICINE MODEL

2017· article· en· W2731872536 on OpenAlexaff
Sasadhar Sinha, Anna Thurston, Jessica Klich, NELLIS B. FOSTER

Bibliographic record

VenueInnovation in Aging · 2017
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsSinai Health SystemUniversity of Toronto
Fundersnot available
KeywordsMedicineIndependence (probability theory)Scope (computer science)Family medicineGerontologyNursing

Abstract

fetched live from OpenAlex

Older adults are the highest users of paramedical services. To improve care integration, the Independence at Home initiative (IAH) was launched to broaden the scope of practice of paramedics to provide proactive home visits for low-income older adults who were high-users of 911 services (i.e. ≥5 911 calls 6-months). During the first-year, 908 primary and follow-up visits were conducted with 588 patients where paramedics conducted holistic assessments to ascertain unmet health and social care needs. Outcomes for 111 clients enrolled over a 3-month period for whom 6-months pre and post follow-up data was available showed that pre enrolment this group made 301 911 calls (17% from 10 high-users) resulting in 246 (82%) ED visits. Six-months following the visit there were 154 911 calls (19% from six high-users) resulting in 103 (67%) ED visits. Overall, this program reduced 911 calls by 41% and ED transports by 42% six-months after enrolment.

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)0.026
metaresearch head score (Gemma)0.032
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.139

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.032
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0030.003
Open science0.0020.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.081
GPT teacher head0.416
Teacher spread0.335 · 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 designObservational
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

Citations0
Published2017
Admission routes1
Has abstractyes

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