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Record W4395456401 · doi:10.1186/s13690-024-01279-4

“We’re sinking”: a qualitative interview-based study on stakeholder perceptions of structural and process limitations to the Canadian healthcare system

2024· article· en· W4395456401 on OpenAlexafffundabout
Jeanna Parsons Leigh, Stephana J. Moss, Sara J. Mizen, Cynthia Sriskandarajah, Emily A. FitzGerald, Amity E. Quinn, Fiona Clement, Brenlea Farkas, Alexandra Dodds, M. Columbus, Henry T. Stelfox

Bibliographic record

VenueArchives of Public Health · 2024
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsUniversity of CalgaryDalhousie University
FundersDalhousie University
KeywordsHealth careHealth administrationStakeholderThematic analysisSnowball samplingPublic relationsHealth informaticsHealth services researchHealth care reformHealth policyQualitative researchPublic healthPoliticsSociologyNursingPolitical scienceMedicineEconomic growthEconomics

Abstract

fetched live from OpenAlex

BACKGROUND: Despite longstanding efforts and calls for reform, Canada's incremental approach to healthcare changes has left the country lagging behind other OECD nations. Reform to the Canadian healthcare system is essential to develop a higher performing system. This study sought to gain a deeper understanding of the views of Canadian stakeholders on structural and process deficiencies and strategies to improve the Canadian healthcare system substantially and meaningfully. METHODS: We conducted individual, ~ 45-minute, semi-structured virtual interviews from May 2022 to August 2022. Using existing contacts and snowball sampling, we targeted one man and one woman from five regions in Canada across four stakeholder groups: (1) public citizens; (2) healthcare leaders; (3) academics; and (4) political decision makers. Interviews centered on participants' perceptions of the state of the current healthcare system, including areas where major improvements are required, and strategies to achieve suggested enhancements; Donabedian's Model (i.e., structure, process, outcomes) was the guiding conceptual framework. Interviews were audio-recorded, transcribed verbatim, and de-identified, and inductive thematic analysis was performed independently and in duplicate according to published methods. RESULTS: The data from 31 interviews with 13 (41.9%) public citizens, 10 (32.3%) healthcare leaders, 4 (12.9%) academics, and 4 (12.9%) political decision makers resulted in three themes related to the structure of the healthcare system (1. system reactivity; 2. linkage with the Canadian identity; and 3. political and funding structures), three themes related to healthcare processes (1. staffing shortages; 2. inefficient care; and 3. inconsistent care), and three strategies to improve short- and long-term population health outcomes (1. delineating roles and revising incentives; 2. enhanced health literacy; 3. interdisciplinary and patient-centred care). CONCLUSION: Canadians in our sample identified important structural and process limitations to the Canadian healthcare system. Meaningful reforms are needed and will require addressing the link between the Canadian identity and our healthcare system to facilitate effective development and implementation of strategies to improve population health outcomes.

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)0.002
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.605
Threshold uncertainty score0.850

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.395
GPT teacher head0.403
Teacher spread0.008 · 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 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

Citations4
Published2024
Admission routes3
Has abstractyes

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