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Record W2363246293 · doi:10.1097/jhq.0000000000000036

Collection of Patients' Disability Status by Healthcare Organizations: Patients' Perceptions and Attitudes

2016· article· en· W2363246293 on OpenAlexaboutno aff
Megan A. Morris, Megan E. Schliep, Juliette Liesinger, Kenzie A. Cameron

Bibliographic record

VenueJournal for Healthcare Quality · 2016
Typearticle
Languageen
FieldHealth Professions
TopicPatient Satisfaction in Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)Health careFamily medicineMedicineRehabilitationDeskNursingPsychologyPhysical therapy

Abstract

fetched live from OpenAlex

Recent policies call for healthcare organizations to consistently document patients' disability status for the purpose of tracking the quality of care experienced by patients with disabilities. The purpose of the study was to explore patients' attitudes toward healthcare organizations collecting disability status. We surveyed a convenience sample of patients in three outpatient clinics, including primary care and rehabilitation clinics. A total of 303 patients participated; 49% self-identified as disabled, 59% were female and the mean age was 52 years. The majority of participants (88%) either agreed or strongly agreed that it is important for healthcare organizations to collect information about disabilities; 77% stated that they were comfortable or very comfortable with healthcare organizations collecting this information. By contrast, we found that almost a quarter of participants had concerns with front desk staff collecting disability status information. When we presented disability questions endorsed by the Health and Human Services Department, over a quarter of participants (28%) felt that the questions were not inclusive of all disability categories. Although patients are supportive of healthcare organizations collecting disability status information, concerns exist regarding how the information is collected and which categories are included, suggesting the need for continued development of evidence-based, patient-centered methods and questions.

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)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0030.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.073
GPT teacher head0.475
Teacher spread0.401 · 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

Citations12
Published2016
Admission routes1
Has abstractyes

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