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Record W1532518845

Die Einführung der Praxisgebühr und ihre Wirkung auf die Zahl der Arztkontakte und die Kontaktfrequenz: eine empirische Analyse

2005· preprint· de· W1532518845 on OpenAlexaboutno aff
Markus M. Grabka, Jonas Schreyögg, Reinhard Busse

Bibliographic record

VenueEconstor (Econstor) · 2005
Typepreprint
Languagede
FieldHealth Professions
TopicHealth and Medical Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPaymentHealth insuranceQuarter (Canadian coin)Statutory lawConsolidation (business)Actuarial scienceMedicineBusinessPolitical scienceDemographyAccountingHealth careSociologyLawHistoryFinance
DOInot available

Abstract

fetched live from OpenAlex

As part of the Statutory Health Insurance Modernization Act a co-payment of €10 per quarter for the first contact at a physician's or a dentist's office has been introduced with effect of 1stJanuary 2004. Apart from contributing to the financial consolidation of the Statutory Health Insurance the co-payment aimed at changing the patients' behaviour towards more selfresponsibility. This article shows that physician contacts declined in the year 2004 compared to 2003. However the share of those patients who at least had one physician contact in both years remained stable. Two Logit-models point out that necessary physician contacts still take place e.g. in case of disabled persons and persons with poor health. In addition no discrimination of persons of low social status could be observed. The results are also approved by other studies. Therefore it seems plausible, that the introduction of this co-payment has contributed to a reduction of unnecessary and redundant physicians visits.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.022
metaresearch head score (Gemma)0.051
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.118

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.051
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.007
Bibliometrics0.0020.004
Science and technology studies0.0010.002
Scholarly communication0.0050.003
Open science0.0020.002
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0180.002

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 head0.071
GPT teacher head0.401
Teacher spread0.331 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations10
Published2005
Admission routes1
Has abstractyes

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