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Record W2794777250 · doi:10.1186/s12875-018-0802-x

How well do public sector primary care providers function as medical generalists in Cape Town: a descriptive survey

2018· article· en· W2794777250 on OpenAlex
Renaldo Christoffels, Robert Mash

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueBMC Family Practice · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicHealthcare Systems and Technology
Canadian institutionsnot available
FundersFaculty of Medicine and Health, University of SydneyUniversiteit Stellenbosch
KeywordsMedicineWorkforcePrimary careFamily medicineDescriptive statisticsMedical diagnosisNursingPhysician assistantsGeneralist and specialist speciesPublic healthHealth careNurse practitioners

Abstract

fetched live from OpenAlex

BACKGROUND: Effective primary health care requires a workforce of competent medical generalists. In South Africa nurses are the main primary care providers, supported by doctors. Medical generalists should practice person-centred care for patients of all ages, with a wide variety of undifferentiated conditions and should support continuity and co-ordination of care. The aim of this study was to assess the ability of primary care providers to function as medical generalists in the Tygerberg sub-district of the Cape Town Metropole. METHODS: A randomly selected adult consultation was audio-recorded from each primary care provider in the sub-district. A validated local assessment tool based on the Calgary-Cambridge guide was used to score 16 skills from each consultation. Consultations were also coded for reasons for encounter, diagnoses and complexity. The coders inter- and intra-rater reliability was evaluated. Analysis described the consultation skills and compared doctors with nurses. RESULTS: 45 practitioners participated (response rate 85%) with 20 nurses and 25 doctors. Nurses were older and more experienced than the doctors. Doctors saw more complicated patients. Good inter- and intra-rater reliability was shown for the coder with an intra-class correlation coefficient of 0.84 (95% CI 0.045-0.996) and 0.99 (95% CI 0.984-0.998) respectively. The overall median consultation score was 25.0% (IQR 18.8-34.4). The median consultation score for nurses was 21.6% (95% CL 16.7-28.1) and for doctors was 26.7% (95% CL 23.3-34.4) (p = 0.17). There was no difference in score with the complexity of the consultation. Ten of the 16 skills were not performed in more than half of the consultations. Six of the 16 skills were partly or fully performed in more than half of the consultations and these included the more biomedical skills. CONCLUSION: Practitioners did not demonstrate a person-centred approach to the consultation and lacked many of the skills required of a medical generalist. Doctors and nurses were not significantly different. Improving medical generalism may require attention to how access to care is organised as well as to training programmes.

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)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.664
Threshold uncertainty score0.964

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.003
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 head0.074
GPT teacher head0.274
Teacher spread0.200 · 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