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Record W4403657002 · doi:10.1177/08404704241293051

The Integrated Care Team: A primary care based-approach to support older adults with complex health needs

2024· article· en· W4403657002 on OpenAlexafffund
George Heckman, Sarah Gimbel, Chantelle Mensink, Brittany Kroetsch, Aaron Jones, Anooshah Nasim, Melissa Northwood, Jacobi Elliott, Adam Morrison

Bibliographic record

VenueHealthcare Management Forum · 2024
Typearticle
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsEmmanuel Bible CollegeMcMaster UniversityUniversity of WaterlooLawson Health Research InstituteWestern University
FundersUniversity of WaterlooCanadian Foundation for Healthcare Improvement
KeywordsMedicineMedical prescriptionPharmacistIntervention (counseling)NursingInstitutionalisationDementiaIntegrated careEmergency departmentInformation and Communications TechnologyPrimary careFamily medicineHealth carePharmacyPsychiatry

Abstract

fetched live from OpenAlex

Many older adults have complex needs and experience high rates of acute care use and institutionalization. Comprehensive Geriatric Assessment (CGA) is a specialized multidimensional interprofessional intervention to prevent such outcomes, but access to CGA in the community is limited. The Integrated Care Team (ICT) is a proactive case-finding intervention to support older adults with complex needs in primary care. The ICT provides nurse practitioner-led shared-care supported by a pharmacist, family physician, and geriatrician. Patients undergo a CGA, and a person-centred plan of care is implemented. We conducted a mixed-methods evaluation of the ICT. Patients were 81 ± 9.2 years old, 71% were women. Patients had a high burden of dementia and multimorbidity and received 12.8 ± 5.8 prescriptions daily. The ICT improved prescribing and reduced emergency department visits by 49.5% ( P = 0.0001). Patients, care partners, and referring physicians reported high satisfaction with care. The ICT is currently being expanded to support additional primary care providers.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.926
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.019
GPT teacher head0.290
Teacher spread0.270 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations8
Published2024
Admission routes2
Has abstractyes

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