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Record W4401824170 · doi:10.1016/s2214-109x(24)00118-9

Delivering non-communicable disease services through primary health care in selected south Asian countries: are health systems prepared?

2024· review· en· W4401824170 on OpenAlexaff
Syed Masud Ahmed, Anand Krishnan, Obaida Abdul Karim, Kashif Shafique, Nahitun Naher, Sanjida Ahmed Srishti, Aravind Raj Elangovan, Sana Ahmed, Lal Rawal, Alayne M. Adams

Bibliographic record

VenueThe Lancet Global Health · 2024
Typereview
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Public Health Policies and Epidemiology
Canadian institutionsMcGill University
FundersJohns Hopkins UniversityWorld Health Organization
KeywordsPreparednessNon-communicable diseaseMedicineSustainabilityPsychological interventionHealth careBusinessCommunicable diseaseEconomic shortageEconomic growthNursingEnvironmental healthPolitical scienceGovernment (linguistics)Public health

Abstract

fetched live from OpenAlex

In the south Asian region, delivering non-communicable disease (NCD) prevention and control services through existing primary health-care (PHC) facilities is urgently required yet currently challenging. As the first point of contact with the health-care system, PHC offers an ideal window for prevention and continuity of care over the life course, yet the implementation of PHC to address NCDs is insufficient. This review considers evidence from five south Asian countries to derive policy-relevant recommendations for designing integrated PHC systems that include NCD care. Findings reveal high political commitment but poor multisectoral engagement and health systems preparedness for tackling chronic diseases at the PHC level. There is a shortage of skilled human resources, requisite infrastructure, essential NCD medicines and technologies, and dedicated financing. Although innovations supporting integrated interventions exist, such as innovations focusing on community-centric approaches, scaling up remains problematic. To deliver NCD services sustainably, governments must aim for increased financing and a redesign of PHC service.

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)0.004
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: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.465
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.000
Bibliometrics0.0000.003
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.001
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 head0.049
GPT teacher head0.382
Teacher spread0.333 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations38
Published2024
Admission routes1
Has abstractyes

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