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Record W3121535806

Exploring the Relationship between Accreditation and Patient Satisfaction – The Case of Selected Lebanese Hospitals

2014· article· en· W3121535806 on OpenAlexaff
Wissam Haj-Ali, Lama Bou Karroum, Nabil Natafgi, Kassem Kassak

Bibliographic record

VenueResearch Information System of Ardabil University of Medical Sciences (Ardabil University of Medical Sciences) · 2014
Typearticle
Languageen
FieldHealth Professions
TopicHealthcare Quality and Management
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAccreditationSERVQUALPatient satisfactionHospital accreditationMedicineFamily medicineNursingQuality (philosophy)Medical educationQuality assuranceDemographicsEmpathyReliability (semiconductor)PsychologyService qualityService (business)BusinessMarketingDemographyExternal quality assessment
DOInot available

Abstract

fetched live from OpenAlex

Background: Patient satisfaction is one of the vital attributes to consider when evaluating the impact of accreditation 
\nsystems. This study aimed to explore the impact of the national accreditation system in Lebanon on patient satisfaction.
\nMethods: An explanatory cross-sectional study of six hospitals in Lebanon. Patient satisfaction was measured using the 
\nSERVQUAL tool assessing five dimensions of quality (reliability, assurance, tangibility, empathy, and responsiveness). 
\nIndependent variables included hospital accreditation scores, size, location (rural/urban), and patient demographics. 
\nResults: The majority of patients (76.34%) were unsatisfied with the quality of services. There was no statistically 
\nsignificant association between accreditation classification and patient satisfaction. However, the tangibility 
\ndimension – reflecting hospital structural aspects such as physical facility and equipment was found to be associated 
\nwith patient satisfaction. 
\nConclusion:This study brings to light the importance of embracing more adequate patient satisfaction measures 
\nin the Lebanese hospital accreditation standards. Furthermore, the findings reinforce the importance of weighing 
\nthe patient perspective in the development and implementation of accreditation systems. As accreditation is not the 
\nonly driver of patient satisfaction, hospitals are encouraged to adopt complementary means of promoting patient 
\nsatisfaction.

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)0.036
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.448
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0360.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0030.005
Scholarly communication0.0000.001
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 head0.351
GPT teacher head0.438
Teacher spread0.087 · 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; both teacher heads agree on what is shown here.

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

Citations1
Published2014
Admission routes1
Has abstractyes

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