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Record W2000250401 · doi:10.12927/whp.2012.22817

A Qualitative Assessment of the Iraqi Primary Healthcare System

2012· article· en· W2000250401 on OpenAlexvenueno aff
Nazar P. Shabila, Namir Al-Tawil, Tariq S. Al-Hadithi, Egbert Sondorp

Bibliographic record

VenueWorld health & population · 2012
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsThematic analysisHealth carePublic healthQualitative researchEconomic shortagePrimary health careQualitative propertyMedicineNursingQuality (philosophy)Medical educationPolitical scienceGovernment (linguistics)Environmental healthPopulationSociology

Abstract

fetched live from OpenAlex

With the limited availability of empirical and documented knowledge about the Iraqi primary healthcare (PHC) system, this study aimed to identify the main problems facing the Iraqi PHC system and the priorities for change. A qualitative study based on a self-administered questionnaire survey involving 46 primary care managers, public health professionals and academics was conducted in Erbil, Iraq. The questionnaire addressed participants' views on positive aspects, problems, priorities and barriers to change of the PHC system through seven open questions. The qualitative data analysis comprised thematic analysis. The survey revealed significant impediments to delivering PHC services, including problems in organization and management of the system, shortage of and poor quality of medications, and inadequate or uneven distribution of manpower and expertise. Priorities for improving the primary healthcare system included reorganization of the services and leadership involving adoption of family practice and regulation of public-private practice, placing emphasis on prevention and health education, and provision of continuing professional training and development. The enormous problems facing the system might signal the need for important and comprehensive improvements based on more in-depth assessment.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.430
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
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 head0.144
GPT teacher head0.536
Teacher spread0.392 · 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

Citations28
Published2012
Admission routes1
Has abstractyes

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