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Record W3138461708 · doi:10.7172/1644-9584.89.4

The Financial Situation of the Hospital After the Introduction of the Law on the Hospital Network

2020· article· en· W3138461708 on OpenAlexaboutno aff
Aleksandra Sierocka, Dariusz Kostrzewa, Tomasz Leśniak, Michał Marczak

Bibliographic record

VenueProblemy Zarządzania - Management Issues · 2020
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Care Issues
Canadian institutionsnot available
Fundersnot available
KeywordsPayrollRevenueAuditBusinessHealth careFinanceWork (physics)Actuarial scienceFinancial AuditFinancial institutionQuarter (Canadian coin)InstitutionAccountingEconomicsEconomic growthPolitical science

Abstract

fetched live from OpenAlex

Purpose: Changes in the health care system introduced in the fourth quarter of 2017 with the entry into force of the so-called “Hospital networks” constituted a huge challenge for managers of medical entities. The assumption of this work is to present, based on the example of the provincial hospital in Łódź, how the changes in legal regulations introduced over the last few years have influenced the financial condition of the institution and its organization. Design/methodology/approach: The financial results of the audited entity were analysed from 2014 to 2019. The most important legal changes (mainly the implementation of the hospital network) as well as their impact on the income from the National Health Fund (NFZ) are presented. The probable (expected) financial result for 2019 is estimated. Findings: From 2014 to 2016, there was a systematic increase in revenues from the NFZ and a positive financial result (about 10 million a year). From 2017, along with the Act on basic hospital security, there was a reduction in profits. Medical staff strikes (payroll claims) in the second half of 2018 additionally contributed to the reduction of revenues from the NFZ. As a consequence, it was necessary to implement, from 2019, a series of corrective actions aimed at reducing costs and increasing savings (employment reduction, organizational changes). Research limitations/implications: Implementation of cost-reducing measures.

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)0.002
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.762
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.015
GPT teacher head0.304
Teacher spread0.289 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

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