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PROFESSIONAL LIABILITY INSURANCE OF MEDICAL WORKERS IN THE REPUBLIC OF KAZAKHSTAN

2023· article· en· W4395667788 on OpenAlexaboutno aff
Dinara Bagdatovna Razieva, Y.M. Aytkazin, Meruyert Askarovna Amirova

Bibliographic record

VenueBulletin of Institute of Legislation and Legal Information of the Republic of Kazakhstan · 2023
Typearticle
Languageen
FieldHealth Professions
TopicMedical Malpractice and Liability Issues
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessLiabilityLiability insuranceActuarial scienceAccounting

Abstract

fetched live from OpenAlex

The article is devoted to a close analysis of the legal prerequisites of the system of professional liability insurance of medical workers being introduced in the Republic of Kazakhstan. To achieve this goal, the authors conducted a review of the best world practices, foreign legal models of the use of insurance for legislative protection of medical workers from the risks of professional responsibility. The article summarizes the material related to the legal basis of this type of insurance in the country, the procedure for insurance and compensation for damage caused, the scope of the powers and responsibilities of the parties involved in insurance. According to the plan, starting from 2023, it is proposed to introduce compulsory insurance at the expense of employers, and from 2025 – joint insurance, which provides for the distribution of the amount of the insurance premium between a medical organization and a medical worker, which will lead to general professional responsibility, will have a positive impact on improving the quality of services provided, will become an effective tool for reducing conflict in medical organizations. Considerable attention is paid in the article to the models of professional liability insurance of medical workers in Turkey, Canada, Sweden. In this regard, the authors investigated the role of mutual insurance societies and specialized medical associations in concluding professional liability insurance contracts in these countries. This approach allows the authors to consider the possibilities of applying successful foreign practices in Kazakhstan and identify promising areas of their legal support. The article reveals the problems of10.52026/2788-5291_2023_73_2_53 determining the maximum amount of the insurer's liability for an insured event at the initial stage of the introduction of the insurance system, procedural provision of insurance payments and other guarantees provided by law. As a result of the study, the authors put forward a hypothesis about the need to consolidate the joint responsibility of a medical worker and a medical institution, which will ensure the mutual interest of all subjects of the healthcare system in providing quality services to the population.

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)0.010
metaresearch head score (Gemma)0.014
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.432
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.040
GPT teacher head0.375
Teacher spread0.335 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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