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Record W2740162871 · doi:10.1080/16549716.2017.1350452

How patients navigate the diagnostic ecosystem in a fragmented health system: a qualitative study from India

2017· article· en· W2740162871 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.

Bibliographic record

VenueGlobal Health Action · 2017
Typearticle
Languageen
FieldMedicine
TopicClinical Reasoning and Diagnostic Skills
Canadian institutionsMcGill UniversityMcGill University Health Centre
FundersBill and Melinda Gates Foundation
KeywordsMedicineFocus groupQualitative researchHealth careTest (biology)NursingFamily medicineBusinessEconomic growthMarketingSociology

Abstract

fetched live from OpenAlex

BACKGROUND: Depending on a country's diagnostic infrastructure, patients and providers play different roles in ensuring that correct and timely diagnosis is made. However, little is known about the work done by patients in accessing diagnostic services and completing the 'test and treat' loop. OBJECTIVE: To address this knowledge gap, we traced the diagnostic journeys of patients with tuberculosis, diabetes, hypertension and typhoid, and examined the work they had to do to arrive at a diagnosis. METHODS: This paper draws on a qualitative study, which included 78 semi-structured interviews and 13 focus group discussions with patients, public and private healthcare providers, community health workers, test manufacturers, laboratory technicians, program managers and policymakers. Data were collected between January and June 2013 in rural and urban Karnataka, South India, as part of a larger project on barriers to point-of-care testing. We reconstructed patient diagnostic processes retrospectively and analyzed emerging themes and patterns. RESULTS: The journey to access diagnostic services requires a high level of involvement and immense work from patients and/or their caretakers. This process entails overcoming cost and distance, negotiating social relations, continuously making sense of their illness and diagnosis, producing and transporting samples, dealing with the social consequences of diagnosis, and returning results to the treating provider. The quality and content of interactions with providers were crucial for completion of test and treat loops. If the tasks became overwhelming, patients opted out, delayed being tested, switched providers and/or reverted to self-testing or self-treatment practices. CONCLUSION: Our study demonstrated how difficult it can be for patients to complete diagnostic journeys and how the health system works as far as diagnostics are concerned. If new point-of-care tests are to be implemented successfully, policymakers, program officers and test developers need to find ways to ease patient navigation through diagnostic services.

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)0.002
metaresearch head score (Gemma)0.022
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.081
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.049
GPT teacher head0.454
Teacher spread0.405 · 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