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Record W2903060863 · doi:10.1186/s12875-018-0878-3

Procedures performed by general practitioners and general internal medicine physicians - a comparison based on routine data from Northern Germany

2018· article· en· W2903060863 on OpenAlexaboutno aff
Christoph Strumann, Kristina Flägel, Timo Emcke, Jost Steinhäuser

Bibliographic record

VenueBMC Family Practice · 2018
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineWorkforceFamily medicinePrimary careHealth careEconomic shortageQuarter (Canadian coin)

Abstract

fetched live from OpenAlex

BACKGROUND: In response to a rising shortage of general practitioners (GPs), physicians in general internal medicine (GIM) have become part of the German primary care physician workforce. Previous studies have shown substantial differences in practice patterns between both specialties. The aim of this study was to analyse and compare the application of procedures by German GPs and GIM physicians based on routine data. METHODS: -test. The selection of procedures was based on international and own preliminary studies on primary care procedures. RESULTS: In the first quarter of 2013/2015 respectively, 1228/1227 GPs and 447/484 GIM physicians provided services in Schleswig-Holstein. Significant differences were found for 20 of the 46 procedures. GPs had higher application rates of procedures concerning health screening (e.g. adolescent health examination, well-child visits) and minor surgery. GIM physicians more often applied technology-oriented procedures, such as ultrasound scans, electrocardiograms (ECG), and 24-h ambulatory blood pressure measurements. The treatment patterns of both specialities did not vary much during the study period. Cardiac stress testing was the only significantly increased GP procedure in that time. CONCLUSIONS: Our results suggest substantial differences in the application of procedures between GPs and GIM physicians with potential consequences for the overall primary healthcare provision. The findings could foster a discussion about training needs for procedures in primary care to ensure its comprehensiveness. The results reflect scope for changes in vocational training in the future for an effective and efficient re-allocation of primary healthcare.

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)0.001
metaresearch head score (Gemma)0.002
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.218
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.111
GPT teacher head0.457
Teacher spread0.346 · 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
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

Citations11
Published2018
Admission routes1
Has abstractyes

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