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Record W4413787993 · doi:10.1186/s12913-025-13316-1

Evaluation of a pilot outreach program to support point-of-care screening for individuals with diabetes who are experiencing homelessness in Alberta, Canada: results of a mixed methods study

2025· article· en· W4413787993 on OpenAlexafffundabout
Sara Scott, Eshleen Grewal, Malavika Varma, David J.T. Campbell

Bibliographic record

VenueBMC Health Services Research · 2025
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsUniversity of Calgary
FundersCumming School of Medicine, University of CalgarySuncor Energy IncorporatedUniversity of Calgary
KeywordsOutreachMedicineNursing researchHealth informaticsHealth administrationPublic healthFamily medicineNursingHealth psychologyGerontologyHealth services research

Abstract

fetched live from OpenAlex

BACKGROUND: Accessing diabetes care requires effort and time. Homelessness often forces individuals to prioritize securing shelter and safety over medical appointments, particularly for the screening and prevention of long-term diabetes complications. We evaluated the effectiveness and costs associated with a point-of-care screening program with expedited referral pathways within two inner-city community sites in Calgary, Canada serving individuals experiencing homelessness. METHODS: We conducted a non-randomized concurrent-convergent mixed methods pilot study of the program. Adults experiencing homelessness and diabetes were recruited through the host sites and attended two separate visits. At the initial visit, screening for microvascular complications, glycemic monitoring (glycated hemoglobin testing), and footcare were offered. At the follow-up visit, the nurse shared the screening results and arranged specialist referrals. The quantitative strand of the study was comprised of a pre-post assessment, comparing screening completion rates after our program to historical screening over the past two years, based on chart review and patient reports. We used a qualitative descriptive approach to report on patient reflections of the program. RESULTS: Nearly all participants (n = 40) completed the screening tests offered: foot/peripheral neuropathy (n = 39), retinopathy (n = 30), and diabetic kidney disease (n = 38). This is compared to the previous two years, where only n = 10, n = 11, and n = 20 completed these tests, respectively. While n = 23 had their glycated hemoglobin measured in the past year, n = 40 completed it with our program. Most participants (83%) attended both clinic visits. Despite this unique and well received model, getting participants to see specialists remained challenging, with fewer than half of referred patients attending follow-up visits. The cost of the pilot ($846/visit) illustrates this model requires modifications to provide even better value. Four main themes emerged from the participant interviews regarding the program that include: improved accessibility to services, positive experiences, ideal locations of service, and willingness to return. CONCLUSIONS: This point-of-care screening model significantly increased screening rates from the pre-period and participants indicated interest in and support for the program. However, innovative approaches to enhance the program are required. Potential adjustments include partnering with more community sites servicing this population and expanding the scope of care offered as well as reaching a broader population.

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)0.014
metaresearch head score (Gemma)0.010
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 score0.127
Threshold uncertainty score0.342

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0070.002
Scholarly communication0.0020.001
Open science0.0040.002
Research integrity0.0020.001
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 head0.161
GPT teacher head0.561
Teacher spread0.400 · 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

Citations0
Published2025
Admission routes3
Has abstractyes

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