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Record W2972560762 · doi:10.1136/bmjgh-2019-001669

Use of standardised patients for healthcare quality research in low- and middle-income countries

2019· review· en· W2972560762 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueBMJ Global Health · 2019
Typereview
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Systems and Reforms
Canadian institutionsMcGill University
FundersGrand Challenges CanadaWorld Bank GroupBill and Melinda Gates Foundation
KeywordsLow and middle income countriesHealth careQuality (philosophy)Health services researchMedicineEnvironmental healthPublic healthPublic economicsNursingEconomic growthDeveloping countryEconomics

Abstract

fetched live from OpenAlex

The use of standardised patients (SPs)-people recruited from the local community to present the same case to multiple providers in a blinded fashion-is increasingly used to measure the quality of care in low-income and middle-income countries. Encouraged by the growing interest in the SP method, and based on our experience of conducting SP studies, we present a conceptual framework for research designs and surveys that use this methodology. We accompany the conceptual framework with specific examples, drawn from our experience with SP studies in low-income and middle-income contexts, including China, India, Kenya and South Africa, to highlight the versatility of the method and illustrate the ongoing challenges. A toolkit and manual for implementing SP studies is included as a companion piece in the online supplement.

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.

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)0.008
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.919
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.465
GPT teacher head0.523
Teacher spread0.058 · 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