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Record W2162709815

Physicians' perceptions of capacity building for managing chronic disease in seniors using integrated interprofessional care models.

2015· article· en· W2162709815 on OpenAlexaffabout
Linda Lee, George Heckman, Robert S. McKelvie, Philip Jong, Teresa D’Elia, Loretta M. Hillier

Bibliographic record

VenuePubMed · 2015
Typearticle
Languageen
FieldMedicine
TopicChronic Disease Management Strategies
Canadian institutionsLawson Health Research InstitutePopulation Health Research InstituteMcMaster University Medical CentreResearch Institute for AgingInstitute for Work & HealthCentre for Family Medicine
Fundersnot available
KeywordsStaffingMedicineGeriatricsNursingHealth careChronic careFamily medicineMultiple Chronic ConditionsChronic diseaseQualitative researchPsychiatry
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: To explore the barriers to and facilitators of adapting and expanding a primary care memory clinic model to integrate care of additional complex chronic geriatric conditions (heart failure, falls, chronic obstructive pulmonary disease, and frailty) into care processes with the goal of improving outcomes for seniors. DESIGN: Mixed-methods study using quantitative (questionnaires) and qualitative (interviews) methods. SETTING: Ontario. PARTICIPANTS: Family physicians currently working in primary care memory clinic teams and supporting geriatric specialists. METHODS: Family physicians currently working in memory clinic teams (n = 29) and supporting geriatric specialists(n = 9) were recruited as survey participants. Interviews were conducted with memory clinic lead physicians (n = 16).Statistical analysis was done to assess differences between family physician ratings and geriatric specialist ratings related to the capacity for managing complex chronic geriatric conditions, the role of interprofessional collaboration within primary care, and funding and staffing to support geriatric care. Results from both study methods were compared to identify common findings. MAIN FINDINGS: Results indicate overall support for expanding the memory clinic model to integrate care for other complex conditions. However, the current primary care structure is challenged to support optimal management of patients with multiple comorbidities, particularly as related to limited funding and staffing resources. Structured training, interprofessional teams, and an active role of geriatric specialists within primary care were identified as important facilitators. CONCLUSION: The memory clinic model, as applied to other complex chronic geriatric conditions, has the potential to build capacity for high-quality primary care, improve health outcomes,promote efficient use of health care resources, and reduce healthcare costs.

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)0.006
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.076
GPT teacher head0.325
Teacher spread0.249 · 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 designQualitative
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

Citations17
Published2015
Admission routes2
Has abstractyes

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