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Record W4312368474 · doi:10.15584/ejcem.2022.3.15

Comparative analysis of patients’ satisfaction level, hospitalized before and during the COVID-19 pandemic

2022· article· en· W4312368474 on OpenAlexaboutno aff
Rena Wójcik, Anna Adam, Ewa Golonka

Bibliographic record

VenueEuropean Journal of Clinical and Experimental Medicine · 2022
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 and healthcare impacts
Canadian institutionsnot available
Fundersnot available
KeywordsPandemicMedicineQuarter (Canadian coin)Coronavirus disease 2019 (COVID-19)Health careStatistical significancePatient satisfactionFamily medicineQuality (philosophy)NursingMedical emergencyDiseaseInternal medicineGeography

Abstract

fetched live from OpenAlex

Introduction and aim. Measurement of the satisfaction level with health services is the most frequently used indicator, mainly because of its importance for determining the quality of the care offered. It is the key to succeed in achieving high-quality healthcare. The purpose of this study was to create a retrospective comparative analysis of the satisfaction level amongst patients hospitalized before and during the COVID-19 pandemic. Material and methods. The study covered a total of 966 patients in 19 hospital wards, in the fourth quarter of 2019 (before the pandemic) and in the second quarter of 2021 (during the pandemic) at the Masovian Specialist Hospital in Radom. The level of patient satisfaction was assessed based on the questionnaire prepared and approved by the Quality Assurance Team in the Masovian Specialist Hospital. The statistical analysis was carried out on the basis of the STATISTICA 10.1 program, using the Pearson’s chi square test, for the significance level at p<0.05. Results. The high level of satisfaction of patients staying in the hospital during the pandemic applied to the widely understood medical and nursing care as well as sanitary conditions in wards, especially the cleanness of rooms, bed linens and sanitary facilities. Conclusion. The biggest dissatisfaction of hospitalized patients during the COVID-19 pandemic involved certain restrictions of visitations and using pastoral services.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.008
Threshold uncertainty score0.368

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.198
GPT teacher head0.477
Teacher spread0.279 · 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.

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

Citations0
Published2022
Admission routes1
Has abstractyes

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