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Record W2070456883 · doi:10.1177/106286060001500303

Patient Satisfaction as an Indicator of Quality Care in Independent Health Facilities: Developing and Assessing a Tool to Enhance Public Accountability

2000· article· en· W2070456883 on OpenAlexaff
Christel A. Woodward, Truls Østbye, Joy Craighead, Gerald Gold, Elizabeth Wenghofer

Bibliographic record

VenueAmerican Journal of Medical Quality · 2000
Typearticle
Languageen
FieldHealth Professions
TopicPatient Satisfaction in Healthcare
Canadian institutionsWestern UniversityCollege of Physicians and Surgeons of OntarioMcMaster University
Fundersnot available
KeywordsMedicineQuality (philosophy)Patient satisfactionAccountabilityScale (ratio)Health careQuality managementFamily medicineMEDLINEHealth care qualityNursingMedical emergencyOperations management

Abstract

fetched live from OpenAlex

The objective of this research was to examine the performance of a brief patient survey about quality of care received in community-based diagnostic and therapeutic facilities. The survey was administered to patients in 44 facilities that were also scheduled for a formal external assessment. The response rate was 53%. Patients generally rated their care positively; 18.5% of patients rated at least 1 item as fair or poor. The amount of information received about risks and complications was rated least favorably; concern and caring shown by staff was rated most favorably. The 10 items which patients rated regarding aspects of quality formed an internally consistent scale (alpha = .93). Patients' ratings were not useful predictors of assessor ratings. Although patients' ratings cannot substitute for expert on-site assessments, they are an important part of a quality management program. The patient survey provides additional, complementary information about components of quality care that are important to them.

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)0.012
metaresearch head score (Gemma)0.035
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 score0.012
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.035
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.094
GPT teacher head0.522
Teacher spread0.428 · 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

Citations37
Published2000
Admission routes1
Has abstractyes

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