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Record W2213610248 · doi:10.1186/s12913-015-1223-3

Point-of-care testing in India: missed opportunities to realize the true potential of point-of-care testing programs

2015· article· en· W2213610248 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

VenueBMC Health Services Research · 2015
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 detection and testing
Canadian institutionsMcGill University Health CentreRoyal Victoria Regional Health CentreRoyal Victoria HospitalMcGill University
FundersBill and Melinda Gates Foundation
KeywordsMedicinePoint-of-care testingReferralHealth administrationContext (archaeology)Health carePublic healthTest (biology)Health informaticsFocus groupPoint of careNursingFamily medicineNursing researchMedical emergencyMarketingPathology

Abstract

fetched live from OpenAlex

BACKGROUND: The core objective of any point-of-care (POC) testing program is to ensure that testing will result in an actionable management decision (e.g. referral, confirmatory test, treatment), within the same clinical encounter (e.g. POC continuum). This can but does not have to involve rapid tests. Most studies on POC testing focus on one specific test and disease in a particular healthcare setting. This paper describes the actors, technologies and practices involved in diagnosing major diseases in five Indian settings - the home, community, clinics, peripheral laboratories and hospitals. The aim was to understand how tests are used and fit into the health system and with what implications for the POC continuum. METHODS: The paper reports on a qualitative study including 78 semi-structured interviews and 13 focus group discussions with doctors, nurses, patients, lab technicians, program officers and informal providers, conducted between January and June 2013 in rural and urban Karnataka, South India. Actors, diseases, tests and diagnostic processes were mapped for each of the five settings and analyzed with regard to whether and how POC continuums are being ensured. RESULTS: Successful POC testing hardly occurs in any of the five settings. In hospitals and public clinics, most of the rapid tests are used in laboratories where either the single patient encounter advantage is not realized or the rapidity is compromised. Lab-based testing in a context of manpower and equipment shortages leads to delays. In smaller peripheral laboratories and private clinics with shorter turn-around-times, rapid tests are unavailable or too costly. Here providers find alternative measures to ensure the POC continuum. In the home setting, patients who can afford a test are not/do not feel empowered to use those devices. CONCLUSION: These results show that there is much diagnostic delay that deters the POC continuum. Existing rapid tests are currently not translated into treatment decisions rapidly or are not available where they could ensure shorter turn-around times, thus undermining their full potential. To ensure the success of POC testing programs, test developers, decision-makers and funders need to account for such ground realities and overcome barriers to POC testing programs.

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)0.004
metaresearch head score (Gemma)0.003
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: Empirical
Teacher disagreement score0.609
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.286
GPT teacher head0.442
Teacher spread0.157 · 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