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Record W3196621467 · doi:10.9778/cmajo.20210004

Patient navigation programs in Alberta, Canada: an environmental scan

2021· article· en· W3196621467 on OpenAlexaffvenueabout
Karen Tang, Jenny Kelly, Nishan Sharma, William A. Ghali

Bibliographic record

VenueCMAJ Open · 2021
Typearticle
Languageen
FieldMedicine
TopicGlobal Cancer Incidence and Screening
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMental healthIntervention (counseling)Health careFamily medicineMedicinePsychologyGeographyMedical educationNursingPolitical sciencePsychiatry

Abstract

fetched live from OpenAlex

<h3>Background:</h3> Patient navigation is a complex intervention that has garnered substantial interest and investment across Canada. We conducted an environmental scan to understand the landscape of patient navigation programs within the health care system in Alberta, Canada. <h3>Methods:</h3> We included patient navigation programs within Alberta Health Services (AHS) and Alberta’s Primary Care Networks (PCNs). Key informants were asked in October 2016 to identify existing programs and their corresponding program contacts. These program contacts were invited to complete a telephone-based survey from October 2016 to July 2017, to provide program descriptions and eligibility criteria, and to identify gaps in navigation. Programs were included if they engaged patients on an individual basis, and either facilitated continuity of care or promoted patient and family empowerment. We tabulated results and calculated summary statistics for program characteristics. <h3>Results:</h3> Ninety-five potentially eligible programs were identified by key informants. The response rate to the study survey was 73% (<i>n</i> = 69). After excluding programs not meeting inclusion criteria, we included a total of 58 programs in the study: 43 AHS programs and 15 PCN programs. Nearly all programs (93%, <i>n</i> = 54) delivered navigation via an individual acting as a navigator. A minority of programs also included nonnavigator components, such as Web-based resources (7%, <i>n</i> = 4) and process or structural changes to facilitate navigation (22%, <i>n</i> = 13). Certain patient subgroups were particularly well-served by patient navigation; these included patients with cancer, substance use disorders or mental health concerns, and pediatric patients. Gaps identified in navigation fell under 4 domains: awareness, resources, geographic distribution and integration. <h3>Interpretation:</h3> Patient navigation programs are common and have extended beyond cancer care, from which the construct originated; however, gaps include a lack of awareness and inequitable access to the programs. These findings will be of interest to those developing and implementing patient navigation interventions in Alberta and other jurisdictions.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.186
Threshold uncertainty score0.255

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.056
GPT teacher head0.306
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 teacher head, 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

Citations16
Published2021
Admission routes3
Has abstractyes

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