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Record W2164431323 · doi:10.1186/1475-9276-10-38

Enhancing measurement of primary health care indicators using an equity lens: An ethnographic study

2011· article· en· W2164431323 on OpenAlexafffund
Sabrina T. Wong, Annette J. Browne, Colleen Varcoe, Josée G. Lavoie, Victoria Smye, Olive Godwin, Doreen Littlejohn, David Tu

Bibliographic record

VenueInternational Journal for Equity in Health · 2011
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsUniversity of Northern British ColumbiaVancouver Native Health SocietyUniversity of British Columbia HospitalUniversity of British Columbia
FundersCanadian Institutes of Health ResearchMichael Smith Health Research BC
KeywordsThematic analysisDisadvantagedHealth equityPublic healthEquity (law)Health careHealth services researchSocial determinants of healthHealth policyPovertyContext (archaeology)Focus groupPublic relationsHealth indicatorNursingMedicineSociologyQualitative researchEconomic growthBusinessPolitical scienceMarketingGeographySocial scienceEconomics

Abstract

fetched live from OpenAlex

INTRODUCTION: One important goal of strengthening and renewal in primary healthcare (PHC) is achieving health equity, particularly for vulnerable populations. There has been a flurry of international activity toward the establishment of indicators relevant to measuring and monitoring PHC. Yet, little attention has been paid to whether current indicators: 1) are sensitive enough to detect inequities in processes or outcomes of care, particularly in relation to the health needs of vulnerable groups or 2) adequately capture the complexity of delivering PHC services across diverse groups. The purpose of this paper is to contribute to the discourse regarding what ought to be considered a PHC indicator and to provide some concrete examples illustrating the need for modification and development of new indicators given the goal of PHC achieving health equity. METHODS: Within the context of a larger study of PHC delivery at two Health Centers serving people facing multiple disadvantages, a mixed methods ethnographic design was used. Three sets of data collected included: (a) participant observation data focused on the processes of PHC delivery, (b) interviews with Health Center staff, and (c) interviews with patients. RESULTS: Thematic analysis suggests there is a disjuncture between clinical work addressing the complex needs of patients facing multiple vulnerabilities such as extreme levels of poverty, multiple chronic conditions, and lack of housing and extant indicators and how they are measured. Items could better measure and monitor performance at the management level including, what is delivered (e.g., focus on social determinants of health) and how services are delivered to socially disadvantaged populations (e.g., effective use of space, expectation for all staff to have welcoming and mutually respectful interactions). New indicators must be developed to capture inputs (e.g., stability of funding sources) and outputs (e.g., whole person care) in ways that better align with care provided to marginalized populations. CONCLUSIONS: The current emphasis on achieving greater equity through PHC, the continued calls for the renewal and strengthening of PHC, and the use of monitoring and performance indicators highlight the relevance of ensuring that there are more accurate methods to capture the complex work of PHC organizations.

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)0.016
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.263
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.488
GPT teacher head0.578
Teacher spread0.089 · 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 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

Citations36
Published2011
Admission routes2
Has abstractyes

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